System integration involves connecting applications, databases, cloud platforms, legacy systems, and devices so they operate as a single coherent, secure, and reliable ecosystem.

It is a strategic business process that transforms data fragmentation into a competitive advantage. It goes beyond making two pieces of software communicate — it enables a digital organization to react quickly, innovate, and serve customers effectively.

System integration therefore represents the fundamental prerequisite for digital transformation. Without solid integration, it is impossible to achieve a 360° view of the customer, enable subscription-based or ecosystem-driven business models, or adopt technologies such as generative AI and hyper-personalization without delays and excessive costs.

A company with disconnected systems suffers operational delays, frequent errors, and duplicated work. Conversely, effective integration eliminates information silos, ensures interoperability between heterogeneous systems, creates a continuous and bidirectional flow of data, and establishes a single source of truth.

This makes it possible to reduce time-to-market, decrease operational errors, improve the customer experience across all touchpoints, and rapidly experiment with new business hypotheses.

At SparkFabrik, we have delivered system integration projects that transformed fragmented IT landscapes into scalable ecosystems, always starting from the business question: how can we better leverage existing data to generate immediate and future value?

The concrete benefits of system integration: how integration improves efficiency and agility

System integration, when executed with a structured and strategic approach, can generate direct and measurable benefits, such as:

1. Silo reduction: before, departments work on misaligned data with continuous manual reconciliations; after, everyone accesses information updated in real time. Result: time spent on information retrieval and corrections reduced by 60-80%, and operational errors significantly decreased.
2. End-to-end automation: before, processes like order-to-shipment and warehouse stock synchronization require manual steps between systems; after, an order automatically triggers stock updates, documents, and notifications. Impact: cycle time from days to hours, reduced operational costs.
3. Real-time customer view: before, marketing, sales, and after-sales service use outdated data; after, every touchpoint sees the same up-to-date customer profile.
4. Accelerated time-to-market: before, new channels or services require months of custom integrations; after, they can be connected in weeks through reusable APIs.

These benefits, measured in real projects, transform integration from an IT cost into a strategic lever for efficiency, revenue, and competitiveness.

Methods and architectures: how to choose the right approach to integration

The evolution of integration architectures reflects the shift from rigid, centralized solutions to flexible, scalable, and cloud-oriented models.

In practice, when we talk about “integration methods and architectures,” we are not just referring to different technologies, but to different ways of circulating data within the organization: from point integrations designed to solve a single problem, to actual “connective fabrics” that link departments, on-premise applications, SaaS, and cloud services. Understanding these differences is essential for choosing an approach that is sustainable over time relative to your current IT landscape and the strategic direction you want to take.

Let’s start with the foundational methods. Vertical integration connects systems within a specific domain, creating deep but isolated flows that meet specialized needs without easily extending to other departments.

Horizontal integration, on the other hand, connects cross-functional systems through a common layer, promoting the reuse of services and data.

Over time, various integration architectures have been built on these methods, implementing them in more or less centralized and scalable ways.

Traditional architectures begin with SOA (Service-Oriented Architecture), which organizes applications into reusable services exposed via standards like SOAP (an XML messaging protocol used for data exchange between applications). SOA then evolves into the ESB (Enterprise Service Bus), a centralized hub that handles routing, transformation, orchestration, and protocol conversion between heterogeneous systems, often on-premise.

These solutions guarantee strong control in complex legacy environments, but present significant limitations:

• Centralization creates a single point of failure, with costly vertical scalability (adding resources to a single node)
• Complex maintenance as the number of connections grows
• Low agility in handling rapid changes or integrations with external SaaS.

It is precisely to overcome these constraints that more distributed and API-oriented integration architectures have emerged in recent years.

The modern approach is based on API-led connectivity combined with microservices. Here, systems expose reusable RESTful APIs, organized in layers (System APIs for core data access, Process APIs for business logic, Experience APIs for front-end consumers). This decentralized model promotes rapid service composition, reduces dependencies, and supports cloud-native horizontal scalability.

API-led connectivity surpasses the ESB in flexibility because it avoids the central bottleneck, accelerates the adoption of new tools, and enables open ecosystems with external partners. iPaaS (Integration Platform as a Service) represents the Cloud Native evolution: managed platforms that offer pre-built connectors, low-code/no-code capabilities, integrated monitoring, and subscription-based pricing, ideal for hybrid or full-cloud environments.

SparkFabrik favors API-led and iPaaS approaches, often on open source stacks and Kubernetes-native solutions, because they guarantee code control, freedom from vendor lock-in, an active community, and predictable long-term costs.

The choice depends on context: heavy legacy favors a hybrid ESB, while cloud growth and the need for speed point toward API-led with open source iPaaS.

Integration challenges: common risks and strategies to mitigate them

System integration introduces real risks that, if not properly managed, can impact security, timelines, costs, and overall operational reliability. Below are the main risks and the most effective, proven mitigation strategies.

Security and data protection

Connections increase the attack surface and multiply the points where sensitive data can be exposed or compromised. The risk is introducing new vulnerabilities every time an additional system is connected. It is recommended to adopt a zero-trust approach: mutual TLS, OAuth 2.0, limited-scope tokens, end-to-end encryption, managed identity, immutable logging, and continuous vulnerability scanning.

If you want to go deeper into hardening strategies in distributed environments, we cover the topic in detail in our Cloud Native Security Guide

Complexity and technical debt

Without structure, “spaghetti” flows emerge (ungoverned point-to-point connections) that are opaque, fragile, and costly to modify over time. The risk is accumulating technical debt with every new integration, eventually making system evolution prohibitively expensive. It is recommended to use an API-led approach with defined layers (System, Process, Experience), domain-driven design, contract-first (OpenAPI), semantic versioning, and observability (Prometheus, Grafana, distributed tracing).

Performance and resilience

Spikes or failures propagate rapidly if systems are connected synchronously without protection mechanisms, with the risk of turning a single malfunction into a cascading outage. Strategies include circuit breaker, retry with backoff, rate limiting, distributed caching, horizontal scalability on Kubernetes, and chaos engineering, with SLA monitoring via synthetic monitoring.

Governance and data quality

Data risks inconsistencies and duplications when copied and transformed at multiple points without clear rules, with direct impacts on reporting, decisions, and compliance. It is useful to define clear ownership, use event sourcing or change data capture (Kafka, Debezium), schema validation, periodic reconciliation jobs, and a data catalog with automated lineage (which provides a detailed, traceable map of the data lifecycle, supports debugging, and strengthens governance and security).

These risks can be effectively managed through an accurate initial assessment and a mitigation plan calibrated to the company’s specific context. With a structured approach and the practices described, potential obstacles can be transformed into elements of greater robustness and long-term reliability.

The role of the system integrator: a strategic partner for transformation

The modern system integrator has moved beyond the traditional role of a simple technical implementer. Today it acts as a strategic partner that supports the company in digital transformation, combining advanced technical skills with a solid understanding of business objectives.

In the past, the activity was limited to executing client-defined projects: developing connectors, installing middleware, migrating data. The evolution now requires a consultative approach: the system integrator must analyze business processes, identify bottlenecks caused by fragmented data, propose solutions that generate measurable value (cost reduction, revenue growth, greater agility), and accompany the company toward a sustainable integrated architecture.

This is the approach we also adopt at SparkFabrik: we don’t just “connect systems” — we start from business objectives, design the most suitable architecture, and stand alongside the client throughout the entire transformation journey.

How to choose the right partner

To identify a system integrator that represents a true strategic ally, it is helpful to ask some key questions:

1. Does the partner deeply understand our business model and growth objectives, or does it focus exclusively on technical aspects? An effective approach always starts from business objectives before moving to technology.
2. Does it have concrete experience with modern architectures (API-led, microservices, cloud-native iPaaS) and with open source stacks, avoiding rigid and expensive proprietary solutions? A preference for flexible, lock-in-free approaches reduces future costs and increases autonomy.
3. Can it show real cases similar to our context, with measurable success metrics (time-to-market reduction, error reduction, ROI achieved)? References must be backed by concrete numbers, not generic descriptions.
4. Does it propose a transparent method: independent assessment, shared roadmap, joint governance, and continuous results monitoring? Partnership requires visibility and shared responsibility.
5. Does it offer comprehensive capabilities: not just development and integration, but also change management, internal staff training, and post-go-live support to ensure effective adoption? Technical integration loses value if people don’t use it correctly.
6. Does it adopt a collaborative model with mixed client-vendor teams and progressive knowledge transfer, instead of a closed approach? The goal is to make the company increasingly autonomous, not dependent on the partner.

A system integrator that responds positively to these questions transforms integration from a technical project into a strategic lever for growth. Choosing the right partner largely determines whether digital transformation will produce real value or remain a hidden cost.

From theory to practice: examples and use cases of system integration

The introduction of AI agents in companies does not replace system integration but increases its value and complexity: for these agents to read documents, query databases, comply with regulations, or orchestrate processes, they must be securely and governedly connected to existing systems. In other words, agentic AI only truly works when it rests on a solid integration architecture (API-led, event-driven, iPaaS, MCP) that exposes data and functionality in a controlled manner.

The result is application scenarios that are already achievable today and deeply transformative for processes and operating models. We analyzed them in detail in the white paper “Agentic AI: 6 application scenarios achievable now”

Below are some system integration examples, inspired by actually implementable scenarios, that show how integration between systems and AI agents can translate into concrete business benefits.

The future of integration: the impact of cloud, APIs, and artificial intelligence

Today, three main trends are redefining how companies manage data and processes.

1. First, artificial intelligence applied to integration: AI is no longer limited to processing data — it makes integration predictive and autonomous. Machine learning models detect anomalies in flows, suggest automatic optimizations, prevent failures, and configure dynamic routing rules based on real usage patterns.
2. Second, event-driven architectures and real-time data: thanks to platforms like Apache Kafka or cloud-native solutions, systems shift from periodic polling to instant reactions to events. This enables reactive processes, drastically reducing end-to-end latency.
3. Third, the consolidation of iPaaS platforms: companies are migrating toward integration-platform-as-a-service solutions that offer ready-made connectors, low-code/no-code capabilities, automatic scalability, and centralized management.

In this scenario, the value of the open source stack becomes strategic. Open source technologies (Kafka, Camel, Kubernetes, OpenAPI, Debezium) eliminate vendor lock-in, guarantee greater control over code, transparency on security, and predictable costs over the long term.

The establishment of the Agentic AI Foundation by the Linux Foundation further strengthens this approach: for agentic AI (autonomous agents that interact with enterprise systems), it is fundamental to rely on open source protocols, standards, and tools. Only in this way can integration with enterprise data evolve transparently, securely, and interoperably, without proprietary dependencies that limit innovation.

The system integrator of the future will no longer be just a “system connector,” but a knowledge integrator: a partner that helps companies transform connected data flows into actionable knowledge.

How to measure the ROI of a system integration project

For business decision-makers, measuring the ROI of a system integration project is straightforward and concrete. The basic formula is:

ROI (%) = [(Net benefits - Total cost) / Total cost] × 100

Benefits fall into three key categories.

1. Cost savings: reduction in manual hours and reconciliations (60-80%), decrease in operational errors (40-70%), lower IT maintenance costs, and tool consolidation.
2. Revenue growth: improved cross-sell/up-sell conversion (+15-35%), reduced churn (-10-25%), new channels or subscription models enabled faster.
3. Agility: reduced time-to-market (from months to weeks), ability to test 3-5 times more hypotheses per year.

First steps: how to launch a successful integration project

To start a system integration project with a high success rate, it is essential to follow a structured and pragmatic path and be supported by an experienced partner. Below are the 4 key phases to follow.

Phase 1: Business requirements analysis

Start by clearly defining business objectives: which processes need to be accelerated, which pain points eliminated, which KPIs improved (time-to-market, error reduction, customer experience). Involve business decision-makers (CEO, CMO, Operations) to align integration with business strategy, preventing it from becoming a purely technical exercise.

Phase 2: Mapping current systems and data flows

Perform a comprehensive assessment of the IT landscape: list applications, databases, existing APIs, manual flows, data volumes, and critical issues (latencies, duplications, silos). Identify critical data entities and priority integration points. This phase produces a clear map of current “bottlenecks.”

Phase 3: Choosing the technology and architecture

Based on the assessment, select the most suitable approach: API-led connectivity, cloud-native iPaaS, hybrid with open source. Evaluate factors such as degree of legacy, cloud presence, internal teams, budget, and future scalability needs. Also define governance principles (security, versioning, monitoring).

Phase 4: Agile planning and implementation

Translate the roadmap into concrete sprints: start with an MVP (Minimum Viable Integration) on one or two high-impact processes, validate results, gather feedback, and scale progressively. Use agile methodologies with short iterations, continuous testing, and constant client involvement. Monitor real KPIs from the very first sprint.

If you are evaluating a system integration project and want to avoid the most common mistakes, we are at your disposal. Together we will analyze your current context, identify business priorities, and chart a personalized and realistic roadmap to transform your systems into a concrete competitive advantage.

A brand’s digital presence is no longer limited to a website or an app: every user experience spans different channels, different devices and ever-evolving contexts of use. From smartphones to smart TVs, from mobile apps to wearables, users expect consistency, fluidity and accessibility at every touchpoint.

Without a shared system, the risk is creating inconsistent interfaces, redundant processes and a fragmented experience that is difficult for teams to manage and unintuitive for people.

A design system exists precisely for this reason: to bring order, ensure consistency, optimize workflows and improve the experience, both within and beyond teams.

In this guide, we will look at how to build one, evolve it over time and integrate accessibility criteria from the very start — not as a constraint, but as added value.

You will find key principles, practical examples and strategies for evolving your design system in a continuous and collaborative way. Whether you need to create one from scratch or improve what you already have, you are in the right place.

What is a design system and why is it the pillar of your digital strategy

An integral part of a UX Strategy , a design system is a structured set of guidelines , components, shared assets, documentation and code used to design and develop (and subsequently maintain) digital products in a consistent, scalable and inclusive way. Think of it as a living set of shared rules, stylistic choices, patterns and code that helps teams design and develop in a consistent, scalable and accessible manner.

Compared to a style guide or a pattern library, a design system goes deeper: it accompanies the entire product lifecycle , from wireframe to deployment. And when well thought out, it plants the seeds of accessibility from the earliest design phases, translating them into interfaces that are inclusive by design and by default, exactly as required by the European Accessibility Act.

But it is not just a matter of compliance: a design system is also a collaboration tool and a long-term business asset . It helps teams speak the same language, work more fluidly and share reusable solutions without duplicating effort. It reduces technical debt and makes it easier for different roles to work together: designers, developers, QA, content specialists.

Adopting and evolving your design system: a path towards continuous improvement

A design system is not designed once and then shelved. It is a living ecosystem. For many organizations, the first step is not starting from scratch, but building on what already exists : a Figma library, an incomplete style guide, a partial set of components. A design system often starts this way, from an imperfect foundation that takes shape over time, as roles, processes and responsibilities become clearer.

Adoption strategies

There is no single way to have a design system: you can adopt an existing one, adapt one to your needs or design one from scratch . In any case, a good design system is never static : it grows with projects, evolves with technologies and is nourished by the contributions of those who use it. Its value lies precisely in this: holding together aesthetics, technology and inclusion, turning every vision into concrete practice.

A well-adopted design system is not only documented: it is understood and used by those working on different projects, at different times. That is why it is worth starting small , with an initial version composed of a core set of essential, high-impact components for the user experience (e.g. buttons, forms, typography), shared across a few teams. From there, you can then scale gradually , collecting feedback, adjusting guidelines and creating practical use cases.

The golden rule : better to have less that is used well, than everything at once and forgotten. Even the most technically elegant design system fails if it is not actually adopted by the organization. A pragmatic and incremental approach allows you to deliver value quickly, encourage internal adoption and validate successive choices and evolutions based on real feedback.

Every new feature is an opportunity to improve the system. Every project can become a test to verify its robustness. Every team request is a useful signal to understand whether something needs updating, adding or simplifying.

Governance: clarity first

A system grows well if it has clear governance. Who can update the system? How are new solutions proposed? Who decides in the case of exceptions? Defining roles and processes prevents chaos and makes the system more stable over time, even when projects and teams change.

A component’s ability to endure and adapt lies in its governance, not in its supposed initial perfection. A well-governed component can evolve over time; a component that is excellent today but ungoverned is destined to become obsolete and a source of inconsistency in the future.

Team culture: this is where a design system grows in a healthy way

No design system truly works if it is not supported by team culture. It requires collaboration between design and development, between UX and content, between those who design and those who test . It requires continuous training, opportunities for discussion and spaces where the system is communicated, updated and understood. A shared, maintained and living system is also the one that can most easily integrate fundamental aspects over time, such as accessibility, efficiency and innovation.

This is why it is never a job that is finished once and for all. It is a continuous process of improvement, listening and collaboration. Every new feature, every piece of feedback received, every bug fixed can become an opportunity to evolve.

Design system and the European Accessibility Act: how to turn obligation into opportunity

If until recently a well-structured design system was the foundation for consistent and scalable digital products , today it is also something more: it is a strategic tool for complying with the European Accessibility Act.

Indeed, since 28 June 2025, accessibility is no longer just a best practice, but a regulatory requirement for companies operating in the European market, as established by EU Directive 2019/882 , better known as the European Accessibility Act (EAA) .

The objective is clear: to make digital products and services — such as e-commerce sites, apps, platforms or software, as well as downloadable documents like PDFs and presentations — genuinely usable by all people, including those with disabilities.

The technical reference standard is EN 301 549 , which requires conformity with WCAG 2.1 Level AA . The obligation applies to both new and existing products. Only micro-enterprises and cases where compliance would be disproportionate to available resources are exempt.

And this is where the design system comes into play. Why wait until the last moment to “fix” a website or an app when you can build a system that integrates accessibility from the very beginning — in the design, in the code, in the content? An accessible design system is the tool that allows you to do this because it documents components, patterns and best practices. And one more thing: it will be the single point of reference for the entire team right from the start, but also for the future as the product evolves.

When well structured, a design system helps you to:

• comply with regulations;
• ensure consistency and conformity across the entire product;
• make teamwork simpler;
• improve the user experience for all people, not just those with a recognized disability.

It is a matter of compliance, certainly. But it is also an opportunity to do better and engage an audience segment that often remains invisible.

That is why we have created specific resources to accompany you on this journey: a white paper on the Accessibility Act and the design system that explores strategies and methodologies in depth, and an operational accessibility compendium with checklists and practical tools to prepare for the change.

The concrete benefits of a design system

Building better, more robust and more competitive products? It all starts with a good design system: the most effective way to turn this vision into daily practice.

The concrete advantages

• Consistency across every touchpoint A design system helps create a uniform visual and behavioral identity. Components, interactions, tones and patterns speak the same language, from website to app, from e-commerce to chatbot. The result? A recognizable, fluid and reliable experience.
• More speed, less duplicated work Ready-made patterns, components and guidelines mean less time spent reinventing and more time for innovation. Teams can focus on solutions, not on repetitive details. This accelerates development cycles, reduces errors and increases scalability, while also facilitating and reducing maintenance costs.
• Collaboration and alignment across teams A design system enables the alignment of cross-functional teams. It creates a “unified language” that reduces communication, design and development errors. This is a truly valued advantage when teams become geographically distributed, and it also facilitates the onboarding of new team members.
• Less technical debt, more quality Thanks to a design system, it is possible to modify components and propagate updates to all instances that use them. This reduces bugs and inconsistencies, simplifies maintenance and improves overall quality. And when accessibility is built into the components, it contributes to the accessibility of your entire digital ecosystem.
• A UX that works for more people Accessible does not just mean for those with a recognized disability. It means designing for the greatest possible number of people: those browsing on mobile, those with a slow connection, those using only the keyboard, or those in a temporarily disadvantaged situation — such as sun glare on the screen or a broken arm.
• Inclusivity that opens new markets Over 20% of people in Europe live with a disability. But inclusivity is not just an ethical issue: it is a strategic choice that broadens the user base and strengthens brand positioning.
• Stronger brand + more solid reputation = competitive advantage A design system also becomes an asset for strengthening the brand, improving recognizability, establishing consistency in the experience, contributing to the perception of professionalism, creating value and long-term competitive advantage. Furthermore, being accessible means being reliable, forward-thinking and attentive to people: an inclusive design system thus becomes a communication asset as well.

Why you (might) think you don’t need a design system

Does creating a design system seem like too big a project? Too rigid? Not suited to your organization? It is a common thought. Many teams get stuck before they even start: they fear it is only for big tech companies, or that it will slow down creative processes.

In reality, a good design system adapts to its context : it can start small, grow with projects and evolve based on needs. This is also confirmed by insights from Figma and Nielsen Norman Group — there is no single way to adopt and implement it. You can start with little, test, evolve. What matters is building a shared foundation.

Components and fundamental principles of a design system

Beyond principles and strategies, a design system rests on a concrete foundation: its components . These are the fundamental building blocks with which we create consistent and scalable interfaces. We are not just talking about buttons or form fields, but complete modular blocks with logic, style and behavior, ready to be reused. Alongside them are patterns , recurring combinations of components that solve specific problems (for example, an advanced search module or an e-commerce shopping cart), and templates , which give shape to complete pages or flows.

To organize and maintain all of this, two key tools are used: the component library , which describes individual elements and their variants, and the pattern library , which explains how to combine them in different contexts. This is where the bridge between design and development, between interface and code, is built. Many teams choose to structure their systems according to the atomic design approach, starting from basic elements (atoms) such as buttons and labels, aggregating them into more complex molecules and organisms until they create templates and pages. This helps maintain scalability and order even as the system grows.

Another crucial piece of the puzzle are design tokens : abstract values for colors, spacing, typography and other styles. They are the glue that allows design choices to be applied consistently and updated across all platforms without rewriting code each time. In fact, by modifying a value just once, it is possible to automatically propagate updates to all components that use that token, enabling scalability and eliminating inconsistencies.

But having libraries and tokens is not enough. To truly work, every component must be well documented : what it does, how it behaves in different states (hover, focus, disabled), how it adapts to various breakpoints and what accessibility rules it follows. This documentation is the compass that guides content designers, UX and UI designers, developers and QA, making work faster and more precise.

It therefore becomes clear why we emphasize that a good design system is not just a static repository, but a strategic infrastructure that integrates components, patterns and governance to support teams over time, ensuring consistency and innovation. And this is where the space opens up for new challenges and opportunities.

What makes a design system accessible

As we have seen, accessibility can now be considered a new foundational principle of a design system. To be truly accessible, a design system must consider from the very start:

• adequate color contrast , at least 4.5:1 for normal text, paying attention also to states such as hover, focus and active;
• readable typography , with clear fonts, accessible sizes and generous line height;
• visible focus , the user must always know where they are when navigating by keyboard;
• text alternatives , to provide the ability to interpret every meaningful image;
• clear and stable form labels , never replaced by placeholders;
• responsive and flexible layouts , usable even on small screens or with magnification;
• semantic code , with native and well-structured HTML tags, to help screen readers interpret the page.

All these elements are mapped to WCAG 2.1 AA criteria and described in a practical way in our white paper and in our operational guide for accessibility according to the European Accessibility Act (EAA).

Designing with accessibility in mind

To make accessibility an organic part of the design system, you need to start right away: already in Figma, components should be annotated with the relevant WCAG requirements. This helps those who design and develop to keep an eye on accessibility, usability and consistency from the earliest stages.

But inserting technical rules is not enough: what is needed is an approach guided by inclusive design principles , which place at the center the needs of the greatest possible number of people, not only those with recognized disabilities.

UX developer as a key role

The bridge between design and code is fundamental. This is where the UX developer role comes into play — a key role for transforming components created in Figma into real, accessible and maintainable elements over time.

The UX developer works side by side with UX designers, UI designers and front-end developers to:

• implement accessible components according to WCAG standards;
• validate focus, ARIA roles and semantic structure;
• clearly document how a component is used and what accessible features it contains.

Well-crafted documentation allows anyone — designer, developer or QA — to reuse components with awareness and continuity, avoiding errors and inconsistencies.

READ ALSO: UX Developer: who they are and what they do

Design system and Drupal: consistency and accessibility even on complex platforms

A well-structured design system also finds fertile ground in enterprise CMS platforms like Drupal. In these contexts, the architectural complexity and content modularity can pose challenges for visual and functional consistency. Integrating a design system into a Drupal ecosystem instead enables maintaining uniformity across components, patterns and layout logic, reducing inconsistencies between front-end and back-end.

But it is not just a matter of visual order. Thanks to the adoption of accessible and documented components, the design system also facilitates the creation of Drupal themes that comply with WCAG 2.1 AA, simplifying compliance with the European Accessibility Act.

In particular, through dedicated tools such as Figma, Storybook and ZeroHeight (as well as through the mapping between design components and Twig templates, Drupal’s templating engine), it is possible to create a solid and traceable flow between design and development. This translates into greater efficiency, less technical debt and a consistent UX, even on complex and multi-site platforms.

READ ALSO: Design System and Drupal CMS: the link between designers and developers

AI tools for the design system: smart support for efficiency and accessibility

Artificial intelligence can offer concrete support in the creation and management of an accessible design system. It is not about automating the entire process — which remains profoundly human — but about integrating tools capable of simplifying, verifying and optimizing.

Today, AI tools exist that help to:

• perform rapid accessibility checks , such as color contrast, the presence of alt text or text readability;
• suggest more inclusive variants of existing components , evaluating criteria such as clarity, font size or keyboard interaction;
• detect inconsistencies in the design system , analyzing visual or behavioral patterns that do not follow shared standards;
• streamline cross-functional workflows , suggesting consistent naming, generating baseline documentation or automating synchronization between design and development.

A key point for us: AI can simplify, speed up and suggest, but it cannot fully replace the work of those who design, test and maintain a system . Decisions must remain conscious, and manual testing — including testing with people with disabilities — is irreplaceable. As already highlighted in our white paper on the EAA and design systems, AI tools (including widgets) are valuable instruments, but they must be embedded within a solid and well-governed design process. Therefore, AI tools are useful allies, but the responsibility remains in the processes, in the teams and in shared decisions.

When the design system works: examples of success

At SparkFabrik, we support enterprise organizations in developing or evolving their own design systems, tackling challenges of consistency, scalability and accessibility in complex digital contexts.

Among our case studies are projects where the design system served as the lever for unifying the user experience across multiple platforms, drastically reducing development time and costs and maximizing brand consistency. Structured companies, including those operating on an international scale, have achieved greater efficiency, stronger governance of brand identity and shared documentation that simplifies the onboarding of new team members.

• Take, for example, Caleffi : a multinational for which we developed and evolved an extensive design system, capable of covering every need, from atomic elements to complex templates. The result? Brand consistency guaranteed across an articulated ecosystem consisting of 12 catalogs, over 20,000 listed products, more than 5,000 technical files, a presence in 12 countries and 18 languages, and approximately 8,000 daily page views.
• For Bocconi , the new design system involved many stakeholders and led to the creation of a shared set of guidelines. The most appreciated result is documentation accessible to both development and editorial teams — an element that facilitates governance and ensures continuity in content production among people with different roles and distinct university departments.
• Another significant experience is the project carried out for La Scuola , where we followed the entire process of redefining the brand identity. The work started from an initial assessment and concluded with the final release. The full correspondence between the design system and the CMS editorial tools enabled simple and fast onboarding for all new editors.
• Finally, for Zambon we built a navigable system using Fractal, which allows all layout and interaction elements to be viewed immediately. The site is fully shareable, with reading levels designed for both technical and non-technical stakeholders, and enables effective and inclusive communication across all business areas.

The design system that grows with you

Every design system is unique, because the context in which it is born is unique: priorities, constraints, people, objectives.

At SparkFabrik, we start from here, helping you gain clarity on what you already have, what you need and how to build (or evolve) a system that truly works, within and beyond your teams. We work alongside you to define governance, tools, processes and components, with an approach that holds together accessibility, efficiency and sustainability over time. Our goal is to deliver a design system that does not remain on paper, but becomes part of your teams’ daily work and brings real value to your digital projects.

This is just one example of the concrete benefits that the Cloud Native approach can offer to businesses operating in the digital space.

What Does Cloud Native Mean?

Cloud Native is an approach to developing and managing applications designed to fully leverage the cloud environment, whether public or private. It’s not just about “moving” traditional applications to a remote infrastructure, but about building them so they are inherently scalable, resilient and capable of adapting rapidly to change. This paradigm is based on key concepts such as the use of microservices, deployment via containers like Docker, and automated orchestration.

The true strength of Cloud Native lies in its ability to reduce development times and improve business agility. Netflix is often cited as a prime example: thanks to an entirely Cloud Native infrastructure, it manages to introduce hundreds of updates per day while ensuring a flawless user experience for millions of people. This level of innovation would be unthinkable with a traditional approach.

READ ALSO: Cloud Native application definition: understanding Cloud Native Why and how to build a Cloud Native application

How Does a Cloud Native Architecture Work?

A Cloud Native architecture is based on distributed components orchestrated on cloud infrastructures, with microservices at the centre. These small, independent modules communicate via APIs and handle specific functions, such as user management or data processing. Each microservice is isolated, allowing for separate development, updates and scalability.

Portability is ensured by containers, which package code and dependencies into a standard unit, enabling microservices to run on any infrastructure. Similarly to a box containing all the ingredients needed for a dish, containers prepare the software for execution.

Container orchestration ensures their proper distribution, monitoring - to prevent errors - and automatic scaling based on demand. All of this is supported by CI/CD (Continuous Integration/Continuous Delivery), which enables rapid and continuous updates and deployments, ensuring high reliability. This allows companies like Spotify or Airbnb to release new features frequently, keeping the platform stable even under heavy loads.

Why Adopt Cloud Native?

Adopting Cloud Native enables companies to tackle modern challenges with agility, resilience and speed. The main motivation is the ability to accelerate innovation, allowing for the rapid development, testing and deployment of new features - essential in dynamic sectors such as fintech and e-commerce.

Another advantage is automatic scaling, which allows resources to adapt to demand. During high-traffic events, such as Black Friday, e-commerce platforms can handle spikes without over-provisioning their infrastructure.

Resilience is another crucial factor: Cloud Native applications isolate failures to individual microservices, preventing systemic outages. For example, Netflix simulates failures with Chaos Monkey to test the robustness of its infrastructure.

Finally, the pay-as-you-go model optimises costs, charging only for resources actually used, reducing waste and enabling gradual growth, especially for startups.

Difference Between Cloud and Cloud Native

The difference between cloud and Cloud Native lies mainly in how applications are designed, developed and managed, as well as in the underlying strategic approach. Using the cloud means leveraging computing, storage and networking resources provided by a provider such as AWS, Azure or Google Cloud. This model is often used to host existing applications without necessarily modifying them: this is referred to as “lift and shift”, where software is moved from a local server to a cloud environment to reduce costs or increase availability.

Cloud Native, on the other hand, goes further. It doesn’t just transfer traditional applications to the cloud, but rethinks them from scratch to fully exploit the advantages of the cloud’s distributed and scalable infrastructure. Cloud Native applications are modular, designed as microservices contained in containers and orchestrated through dedicated tools. This makes them more flexible, scalable and resilient than traditional applications, even when the latter are hosted in the cloud.

READ ALSO: Cloud Transformation: the benefits for businesses Cloud vs Cloud Native: what are they? An introductory guide

What Are the Main Tools for a Cloud Native Ecosystem?

The tools in the Cloud Native ecosystem optimise the design, development, deployment and management of cloud applications. Among the main ones, we find containers, orchestration platforms, observability systems and development process automation tools.

Containers, such as Docker, are fundamental, as they provide an isolated and portable environment that encapsulates the application and its dependencies, enabling uniform operation on any infrastructure. This allows developers to create software that works the same way on a laptop as it does on a cloud cluster.

Managing containers at scale is handled by orchestrators such as Kubernetes, which we will examine in detail in the next section.

Observability is an equally important element in a Cloud Native ecosystem. Tools include, for example, Prometheus, which collects metrics from microservices, and Grafana, which visualises them in dashboards. This helps teams monitor system health and resolve issues proactively.

Continuous Integration and Continuous Delivery (CI/CD) tools, such as Jenkins and GitLab CI, automate the testing and release process, reducing errors and accelerating development cycles. Solutions like Terraform, which defines cloud resources through code, and Istio, which optimises and secures communication between microservices, complete the landscape, enabling the Cloud Native paradigm and providing companies with a technological foundation for navigating the digital world.

Kubernetes and Container Orchestration in Cloud Native

Kubernetes is the beating heart of container orchestration in the Cloud Native ecosystem, designed to manage the deployment, monitoring and scaling of container-based applications in an automated way. In a world where applications are made up of dozens or hundreds of microservices, Kubernetes offers a platform to coordinate these modular units, ensuring reliability and resource optimisation.

One of the most revolutionary aspects of Kubernetes is its ability to automatically scale resources based on demand. For example, if during an online film premiere millions of users simultaneously access the platform, Kubernetes can launch additional instances of the most heavily loaded microservices to handle the traffic. When traffic decreases, these instances are terminated to save resources and reduce operational costs.

Another key feature is load balancing. Kubernetes automatically directs user requests to active containers, preventing overloads and optimising request distribution. This is particularly useful for global applications, where traffic can vary significantly across geographical regions.

Kubernetes architecture is based on concepts such as pods, which are the smallest execution units and can contain one or more containers, and deployments, which define how pods should be created, updated or deleted. Through declarative configuration, developers specify the desired state of the application, and Kubernetes takes care of achieving and maintaining it, constantly monitoring the system’s state.

READ ALSO: Kubernetes: what it is, how it works, pros and cons, when to use it What is container orchestration and how to do it with Kubernetes

What Are the Benefits of Microservices in a Cloud Native Environment?

Microservices, as mentioned, represent one of the foundational elements of a Cloud Native environment, offering benefits that transform how applications are designed, developed and managed. Adopting a microservices architecture allows organisations to overcome the limitations of monolithic systems, offering flexibility and scalability that are perfectly suited to the needs of the cloud.

One of the main advantages of microservices is their modularity. Each microservice is autonomous and responsible for a specific function, such as order management or user authentication. This modularity simplifies development, as teams can work in parallel on different services without tight dependencies.

A further advantage is the ability to choose different technologies for each microservice. Since microservices communicate with each other via standard APIs, each team can use the programming language or database best suited to the specific needs of the service. This level of freedom allows teams to make the most of technological innovations and create tailored solutions.

READ ALSO: Microservices: what they are and why use them

How Does DevOps Support Cloud Native?

DevOps is a fundamental pillar for the success of Cloud Native applications, as it promotes a culture of collaboration between development and operations teams, enabling automated and continuous processes that align perfectly with the scalability, modularity and agility inherent to Cloud Native. This approach not only bridges the gap between development and operations, but transforms how software is created, deployed and managed.

A practical example of the link between DevOps and Cloud Native is the aforementioned Continuous Integration and Continuous Delivery (CI/CD), a practice that automates testing, integration and code deployment. In a Cloud Native environment, where applications are composed of many microservices, updating individual components safely and quickly is essential. DevOps makes this possible through CI/CD pipelines that ensure every change is tested and deployed without disruption, allowing companies to release new features at a frequency unthinkable in traditional systems.

READ ALSO: Platform Engineering vs DevOps: what are the differences? Agile and DevOps: what they are (NOT) and how they interact

What Is Serverless Computing in the Cloud Native Context?

Serverless computing, in the Cloud Native context, represents an execution model in which developers can focus exclusively on code and application logic, without worrying about the underlying infrastructure. It doesn’t mean that servers are absent, but that their management, scaling and provisioning are completely delegated to the cloud provider, making them invisible to users. This approach aligns perfectly with the Cloud Native philosophy, which values agility, automation and efficiency.

In serverless computing, developers write small units of code, often called functions, that are executed in response to events. A typical example might be a function that is triggered when a user uploads an image to an application, automatically resizing it for different devices. With services like AWS Lambda, Azure Functions or Google Cloud Functions, these operations are automatically scaled based on demand, without the team having to manually size the infrastructure.

One of the distinctive aspects of serverless is the usage-based payment model. Companies pay only for the actual execution time of functions, measured to the millisecond, eliminating the fixed costs associated with idle servers. This is particularly advantageous for applications with intermittent or unpredictable workloads.

TO LEARN MORE: What is serverless computing and what are its benefits?

What Are the Security Challenges in Cloud Native?

Finally, the security question is an aspect of Cloud Native that should not be overlooked. The security challenges in this context stem primarily from the distributed and dynamic nature of applications based on microservices, containers and serverless. Managing the attack surface is complex, as each component (microservice, container, function) is a potential vulnerability point.

Managing configurations through code (Infrastructure as Code) can introduce errors, accidentally exposing resources. Identity and permissions management is essential to prevent unauthorised access, while container security requires attention to using secure and up-to-date images. Log management and distributed monitoring are critical for detecting anomalies, but they increase complexity. Finally, protecting sensitive data is more difficult in such fragmented environments, requiring encryption and secure key management. Some useful resources that address this topic include: The Cloud Native Security Guide, and the deep dives on DevSecOps and Cloud Security.

This journey is not limited to simply transferring data and applications from on-premise environments to cloud-based ones — it involves a deeper shift in business strategies and operations. Fundamentally, cloud transformation entails a restructuring of the entire IT infrastructure and business processes. Only in this way is it possible to fully leverage the benefits offered by cloud technology, such as scalability, flexibility and advanced security.

What is cloud transformation?

Cloud transformation can be defined as the process by which a company restructures its IT operations and infrastructure in order to integrate and leverage cloud technologies. This process involves migrating data, applications and services to cloud platforms, but goes further by also transforming business processes to maximize the benefits of adopting cloud computing.

The benefits of cloud transformation for large enterprises — and for all businesses, really — are numerous and significant. First, cloud transformation improves operational agility, enabling companies to respond more quickly to market demands and adapt to technological changes. The elastic scalability of cloud services allows companies to easily scale IT resources up or down as needed, improving operational efficiency and reducing infrastructure costs. Of course, all of this depends on following a sound Cloud Management strategy that takes FinOps principles into account to maximize the financial management of the Cloud.

READ ALSO: GreenOps and FinOps for efficient Cloud management — Green Cloud Computing: what it is and why it matters

Different approaches to cloud transformation

There are several approaches to cloud transformation, including:

• Private Cloud Transformation: This approach involves creating a private cloud environment within the company’s own infrastructure. It is particularly suited for businesses that require greater control over data and security.
• Public Cloud Transformation: In this case, companies use public cloud services offered by providers such as AWS, Microsoft Azure, Google Cloud or Alibaba Cloud. It is characterized by greater scalability and flexibility, making it ideal for businesses looking to reduce infrastructure and management costs.
• Hybrid Cloud Transformation: This approach combines elements of private and public cloud, allowing companies to leverage the best of both worlds. It is suited for businesses that want to keep certain critical applications on-premise while using the public cloud for other services.

Benefits of cloud transformation

Cloud transformation offers a range of significant advantages for businesses that decide to fully adopt cloud technologies. As previously mentioned, these benefits include aspects such as scalability and flexibility, and are not limited to the technological side — they also positively influence the overall business and operational strategy. The key benefits include:

• Scalability and flexibility: Companies can easily scale IT resources up or down based on current needs, without having to invest in additional hardware or go through lengthy upgrade procedures.
• Cost reduction: Cloud transformation enables companies to reduce infrastructure and operational costs. By eliminating the need to constantly maintain and upgrade on-premise hardware, businesses can save on the purchase, maintenance and management costs of IT infrastructure.
• Greater efficiency: Companies can automate complex processes, improve collaboration between teams that are increasingly working remotely or distributed across different locations, and reduce application development and deployment times.
• Improved security: Cloud service providers invest heavily in infrastructure security and protection against cyber threats, offering customers security tools and technologies that often exceed the capabilities of on-premise infrastructure.
• Access to new technologies: Cloud transformation fosters innovation through simplified access to advanced technologies such as artificial intelligence, data analytics and the Internet of Things (IoT), which are among the top current trends. These technologies enable companies to improve business processes, develop new products and services, and optimize the customer experience.

Challenges of cloud transformation

While it offers numerous benefits, cloud adoption by businesses also presents significant challenges. These challenges must be addressed during the process of implementation, integration into business structures and introduction into business operations. Key challenges to consider include:

• Security and compliance: Ensuring data security is an essential priority during cloud transformation. Companies must tackle challenges related to protecting sensitive data and managing cybersecurity risks during the transformation process. However, once the transformation is complete, they can benefit from the higher security levels guaranteed by cloud service providers.
• Organizational changes: Cloud transformation often requires significant changes to processes and organizational structures. These changes can affect company culture, employee responsibilities and workflows.
• Skills and training: The skills required to manage a cloud environment can differ from traditional IT skills. Companies must invest in staff training to develop the skills needed to manage, monitor and optimize cloud resources.
• Dependency on cloud providers: Companies that entrust their operations and data to cloud service providers must manage their dependency on these providers. This can involve risks related to service availability, pricing policies and changes in contractual terms.

What are the phases of cloud transformation?

Cloud transformation is a complex process that requires method and experience. At SparkFabrik, through our Cloud Migration Service, we offer a structured and proven approach to support companies through every phase of the transformation, which we describe below to provide an overview of what the correct steps in the process should be:

1. Assessment

In this phase, business needs and the applications to be migrated are evaluated. Our experts carry out an in-depth analysis from both a technical and business perspective, identifying potential risks and challenges. This step helps outline the priorities for cloud migration, establishing the foundations for a successful cloud transformation. The needs assessment makes it possible to identify goals and priorities, evaluate security and compliance requirements, analyze organizational impacts and plan resource migration. This initial phase not only mitigates risks but also tailors solutions to the company’s real needs, ensuring an effective and efficient cloud transformation process.

2. Plan

Next, a detailed action plan is defined for executing the migration, taking into account business priorities and operational continuity. In this phase, experience in designing cloud infrastructure is essential, as it enables the adoption of market-leading best practices.

3. Migrate

In the third phase, the actual migration is carried out, coordinating the entire process and working alongside the company’s internal IT team. With the Spark approach, every artifact produced for the migration — such as Terraform manifests and Packer AMIs — will be available to and owned by the client. Furthermore, once the migration is complete, we take over infrastructure management and focus on optimizing processes, applications and cost management. Thanks to this structured method, it is possible to make the right decisions and reduce costs and uncertainties.

Tools and technologies for cloud transformation

Adopting advanced tools and technologies is essential for facilitating an effective migration and successfully managing cloud resources. Here is an overview of the key tools, platforms and technologies:

Orchestration Services

• Kubernetes: One of the most widely used platforms for container orchestration and management, offering automatic scaling, service management and application rollouts.
• Docker Swarm: Another popular tool for orchestrating Docker containers, simplifying the distribution and management of containerized applications.

Automation and Container Management

• Ansible: Used to automate the configuration and management of IT infrastructure, including containers.
• Terraform: For infrastructure-as-code management, it facilitates the creation and management of cloud resources in a declarative and scalable way.

Examples of public cloud platforms

• Amazon Web Services (AWS): Offers a wide range of cloud services, including compute, storage, databases and AI/ML services through a global network of data centers.
• Microsoft Azure: A cloud platform with integrated services for application management, storage, data analytics and other enterprise features.
• Google Cloud Platform (GCP): Provides compute, storage, database, machine learning and other advanced services to support digital innovation and scalability.

Monitoring and management tools

• Prometheus: An open-source system for monitoring and alerting based on metrics.
• Grafana: Used for visualizing and analyzing data from monitoring systems, integrable with Prometheus and other tools.

Cloud computing services

In cloud transformation processes, it is essential to understand the different cloud service models and how they can be applied to optimize business operations. The main models are Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS), each of which offers specific characteristics and unique advantages.

• IaaS provides virtualized IT resources over the Internet. It includes compute, storage and networking services, allowing companies to rent resources instead of purchasing them physically.
• PaaS offers a complete development and deployment environment hosted in the cloud, which includes tools for developing, testing and managing applications without managing the underlying infrastructure.
• SaaS provides cloud-based applications that users can access via the Internet. This model eliminates the need to install and manage software locally, as all software and data are hosted and maintained by the service provider.

What are the emerging technologies?

In the context of cloud transformation, several emerging technologies are playing a crucial role in shaping the future of business operations and technological innovation. These technologies not only enhance the capabilities of cloud infrastructure but also promote new business models and improve the user experience. The main emerging technologies include:

• Edge Computing: This technology moves computation and data processing closer to the data source, improving response speed and reducing latency. It is particularly useful in sectors such as IoT, automotive and telecommunications, where speed is critical.
• Artificial Intelligence (AI): The integration of AI into cloud computing enables advanced data analytics, process automation and improvements in user experience through predictive systems and machine learning.
• Blockchain: This technology offers a secure and transparent way to record transactions and share data between different parties without the need for intermediaries. It finds applications in supply chain management, digital payments and data security.

Best practices for cloud transformation

During the cloud transformation process, following certain best practices can make a significant difference for an effective and secure implementation of cloud technologies. Drawing on the experience we have accumulated working alongside numerous businesses, we have gathered some practical tips that may be useful:

• Risk assessment: Before getting started, it is always a good idea to carry out a detailed risk assessment to uncover potential vulnerabilities and define mitigation strategies.
• Establishing guidelines: Setting clear guidelines and governance processes helps manage the use of and access to cloud resources in an orderly and secure manner.
• Stakeholder engagement: Involving the right people at every stage of the transformation process ensures support and collaboration.
• Training and skill development: Investing in staff training is essential. New cloud technologies require new skills, and the team must be ready.
• Performance monitoring: Implementing performance monitoring systems helps identify potential areas for improvement and optimize cloud resource usage.
• Technology updates: Staying up to date with new technologies and best practices (or partnering with those who are) is essential to continue improving and innovating.

It is no coincidence that security is now at the top of corporate priorities, with numerous facets. While the term “cybersecurity” is generally associated with safeguarding networks, systems, and digital data, and “cloud security” specifically focuses on security strategies within the cloud environment, “software security” concentrates specifically on protecting applications and source code from various threats and vulnerabilities. more

Despite their differences, cybersecurity, cloud security, and software security are all essential: negligence in these areas can lead to devastating consequences for organizations. In this article, we will explore the best practices for strengthening application security and shielding enterprise software from dangers and attacks. Before diving into best practices, let’s examine the core principles of IT security for an organization.

The Principles of Information Security

Information security is built on several fundamental pillars, each of which plays an essential role in the overall protection of data and digital resources. Below are the main pillars of information security:

• Confidentiality: Confidentiality refers to the ability to protect information from unauthorized access. This pillar aims to ensure that only authorized individuals or entities can access certain data or resources.
• Integrity: Integrity concerns the protection of the accuracy and reliability of information. This pillar aims to prevent unauthorized modifications to data, ensuring that information maintains its precision and consistency over time.
• Availability: Availability refers to ensuring that information is accessible and usable when needed. This pillar ensures that digital resources are available to authorized users, guaranteeing operational continuity and the ability to respond to unforeseen events.
• Authentication: Authentication refers to verifying the identity of individuals or entities accessing information or digital resources. This pillar aims to ensure that users are who they claim to be and that transactions are not tampered with.

You might also be interested in: Cloud Security: Protecting Data in the Cloud Era Container Security: What It Is and How to Achieve It

What Is Software Security?

Software security is a discipline dedicated to protecting applications and source code from threats and vulnerabilities. The main objectives of software security are to ensure the integrity, availability, and confidentiality of the software’s data and functionality.

To achieve these objectives, various security strategies and tools are employed, including:

• Risk analysis: Identification and assessment of potential risks and threats to the software, including code vulnerabilities, unauthorized access, and cyberattacks.
• Implementation of security controls: Integration of security measures directly into the source code and application architecture, such as user authentication, authorization, encryption of sensitive data, and session management.
• Security testing: Execution of regular security tests to identify and fix potential vulnerabilities in the software. These tests can include penetration testing, static code analysis, dynamic code analysis, and code reviews.
• Updates and patches: Timely application of security updates and patches to fix known vulnerabilities and protect the software from the latest cyber threats.
• Training and awareness: Training and awareness on software security best practices for developers, system administrators, and end users, to promote a culture of cybersecurity within the organization.

You might also be interested in: DevSecOps: 6 Principles for Introducing It in Your Company Cloud DevSecOps: What It Is, Benefits and Tools

Software Security: Why Is It Important?

Why should companies pay special attention to the security of their software? Software security holds an increasingly predominant importance in today’s IT landscape, where growing interconnection and digitalization expose organizations to increasingly sophisticated and pervasive risks. Ensuring application security is not just a priority, but an imperative to protect access to sensitive data, business information, and user trust.

Software security acts as a bulwark against data breaches and cyberattacks, providing a proactive approach to protecting applications and source code. Through the implementation of security practices and controls, such as robust authentication, data encryption, and monitoring of anomalous activities, organizations can significantly reduce the risk of compromise and damage to their digital assets.

The importance of software security is further underscored by the European Cyber Resilience Act (CRA), a legislative initiative aimed at strengthening cyber resilience in the European Union. This regulatory act highlights the institutional recognition of the importance of cybersecurity and underscores the need to adopt adequate measures to protect digital infrastructures and sensitive data.

Read also The Cyber Resilience Act and Concerns for Open Source

Now that we have highlighted the importance of software security, we are ready to dive into the best practices — the practical recommendations for enjoying secure and reliable software.

Software Security Best Practices

How can you ensure an optimal level of data and application protection? Below we share a series of proven recommendations, drawn from our daily experience in designing and managing secure software solutions.

Security by Design

Adopting an approach that integrates security from the earliest stages of the software lifecycle proves to be an effective strategy for ensuring security. This approach, known as “security by design”, treats security as a fundamental element from the very beginning of the development process. By doing so, it is possible to detect and mitigate vulnerabilities already during system design, improving overall security.

Keep Software Updated and Apply Regular Patches

It is essential to consistently keep software up to date and regularly apply security patches. Every piece of software has potential vulnerabilities that can be exploited by hackers. Keeping software updated significantly reduces the risk of cyberattacks and effectively protects the system.

The Principle of Least Privilege

Applying the principle of least privilege means granting users only the minimum levels of access necessary to perform their duties. By limiting access to unnecessary features, rights, and controls, the risk of unauthorized access and accidental or malicious manipulation is reduced.

Automation of Software Protection Activities

Automation is a valuable ally in reducing workload and ensuring greater consistency in security operations. Automating regular tasks such as security configurations and firewall change analysis helps reduce the risk of human error and ensures continuous and reliable system protection.

Employee Training

Raising employee awareness of software security risks is also fundamental to promoting a security culture within the organization. Scheduling regular training sessions to educate employees about cyber risks, signs of attacks, and best practices for protecting themselves and the company is essential to mitigating vulnerabilities.

Developing a Software Security Plan

What happens if, despite all precautions taken, a problem occurs? There is no reason to panic if you are proactive and have developed a solid security plan. Having a well-defined action plan prepares us to respond effectively to potential security breaches or cyberattacks. To ensure maximum efficiency in these situations, it is crucial to define precise emergency procedures and conduct constant monitoring of system activities.

Software Security and Open Source

After exploring best practices, let us now look at how the Open Source dimension fits within application security. Open Source offers a wide range of advantages, but it also presents specific security challenges, particularly regarding software dependency management.

Software dependencies are components or code libraries used in applications, often developed by third parties and integrated into software projects. While these dependencies can accelerate development and improve application functionality, they can also pose a security risk if not properly managed and monitored.

The dependency problem can be addressed through the adoption of robust software security practices and the implementation of tools and processes dedicated to dependency management. In this context, the Open Source Security Foundation (OpenSSF) plays a fundamental role in providing guidelines, tools, and resources to improve Open Source software security.

You might also be interested in: The article Software Supply Chain: What It Is and What Are Its Vulnerabilities? Paolo Mainardi’s video at the recent DevSecOpsDay discussing the Supply Chain of our cloud infrastructure

SparkFabrik and Software Security

At SparkFabrik, we place software security at the top of our priorities. This is reflected not only in our commitment as members of the Open Source Security Foundation, but also in the range of services we have designed to help companies tackle software security challenges together.

Here is how we can help you keep your software secure:

• Software Supply Chain Audit: Our team can conduct a comprehensive analysis of your software supply chain to identify potential vulnerabilities. This analysis includes evaluating package dependencies, identifying outdated or vulnerable versions, detecting components with known security issues, and analyzing vendor management procedures.
• Regular component updates: We can help you keep your software components up to date — identifying the latest released versions, reviewing release notes for security patches, and planning and executing the necessary updates to eliminate potential vulnerabilities.
• Threat monitoring: We can implement threat monitoring systems to promptly detect new vulnerabilities that could affect your software supply chain.
• Training: We offer training on cybersecurity best practices for personnel involved in the software supply chain: an overview of the most common threats, the importance of security in the software development process, and the promotion of solid security practices, especially in the Cloud Native domain.
• SLSA framework implementation: We can collaborate to implement up to level 3 of the SLSA framework. These controls include package integrity verification, digital signing of software components, software registry audits, SBOM and provenance attestation production, and the creation of review and approval processes for new components.

We can turn your software security into a strength: contact us to start a journey together.

We live in an era where cyberattacks are constantly on the rise . Clusit — the Italian Association for Information Security — recorded 1,141 serious incidents in the first half of 2022 alone, marking an 8.4% increase compared to the previous year. Threats now extend to critical infrastructures, leading 67% of companies to perceive an increase in attacks and 14% to suffer tangible consequences such as service disruptions or reputational damage.

These figures emerge from the analysis conducted by the Cybersecurity & Data Protection Observatory at the School of Management of Politecnico di Milano, presented at the conference “Cybersecurity: towards a common front.” Gaining a thorough understanding of Cloud risk and security factors is therefore becoming increasingly essential for businesses. Not coincidentally, cybersecurity awareness is growing, becoming the top digital investment priority in Italy in 2023, for both large enterprises and SMEs.

What is Cloud Security?

Cloud Security represents a fundamental pillar in the Cloud Computing landscape. A new way of thinking about cybersecurity , extending the role of security across the entire lifecycle of Cloud Native applications.

Cloud Security follows the same standards as traditional security models — what changes is the approach to security. This is because traditional security models are built on outdated assumptions. Cloud Native applications, with their frequent changes, extensive use of open source tools and libraries, and execution on hyperscaler-controlled infrastructures, render traditional code review and quality assurance practices inadequate.

To address these challenges, Cloud Security revolutionizes the approach to security . It introduces a new way of operating that involves security at every stage of the software release cycle. Manual audits are replaced by automated scans, and rapid code release pipelines are integrated with tools that analyze code for vulnerabilities before compilation. Open source libraries are carefully monitored for potential vulnerabilities, and rather than hindering change, the Cloud Native security model embraces frequent updates of vulnerable components or regular replacement of infrastructure. This approach, closely tied to the practice of DevSecOps , serves as an innovative response to security needs in modern Cloud environments.

Read also: DevSecOps: 6 principles for introducing it in your company Container Security: what it is and how to achieve it

Why is Cloud Security important?

The growing adoption of Cloud Computing by businesses imposes an urgent need to pay the utmost attention to Cloud Security . Companies, increasingly relying on Cloud infrastructures for data and resource management, find themselves exposed to significant risks that require a proactive approach to cybersecurity.

As highlighted in the introduction, cyberattacks are constantly increasing. This means that the vulnerability of companies entrusting sensitive data and operational processes to Cloud services is growing. The solution cannot and should not be to boycott the Cloud. Instead, the solution lies in Cloud Security — not just as a best practice, but as a genuine corporate mindset .

In other words: with the continuous increase in attacks, data protection in the Cloud is no longer a choice, but a critical necessity. And confirmation comes from the cybersecurity market . According to research by the Cyber Security & Data Protection Observatory of Politecnico di Milano, in Italy 61% of organizations with more than 250 employees have increased their cybersecurity budget over the past year.

Tackling the security challenge in the Cloud requires a comprehensive and strategic approach , involving all phases of the lifecycle of Cloud applications and resources, from development through to production. In this context, Cloud Security becomes a fundamental element for ensuring operational continuity and preserving the reputation of companies that rely on Cloud Computing.

What are the benefits of Cloud Security?

In the Cloud Computing landscape, a Cloud Security strategy proves particularly advantageous when compared to the traditional approach . The latter, focused on firewalls and network perimeter protection, becomes insufficient in the face of the dynamic nature of Cloud Computing, which dynamically leverages shared resources and automates the provisioning of storage, networking, and on-demand computing.

On the other hand, while dynamism offers advantages, it also expands the attack surface , making a new security perspective necessary. Below are the main benefits of a Cloud Security strategy.

• Protection against attacks: Cloud Security stands as a bulwark against cyberattacks and DDoS attacks, defending businesses from increasingly sophisticated threats.
• Data security: A central element of Cloud Security is the protection of sensitive data through advanced practices such as encryption, preventing critical information from falling into the wrong hands.
• Greater resource availability: Many Cloud Security services offer real-time monitoring and support, increasing resource availability and promptly resolving security issues.
• Greater reliability: A sound Cloud Security approach implies built-in redundancy, ensuring a more reliable experience for users and preventing unwanted disruptions.
• Regulatory compliance: Cloud Security helps ensure regulatory compliance, which is particularly important in a complex Cloud architecture. Cloud providers offer security and support to ensure that organizations meet compliance requirements.

What are the principles of Cloud Security?

When addressing and mitigating security risks in Cloud environments, it becomes essential to adopt specific security activities and follow principles that guide strategic decisions in this area. Let us examine the main areas of Cloud security intervention.

Data protection

Data protection plays a fundamental role. Various technologies are used to create technical barriers between access and the visibility of sensitive data. Encryption , in particular, involves converting data into an encoded format, making it readable only through decryption.

Identity and Access Management

Controlling access is fundamental to ensuring Cloud security. Tools for managing passwords , as well as multi-factor authentication and Identity & Access Management (the management of identities and access), play a key role. These tools limit the compromise of data and systems by controlling access to resources to prevent intrusion by unauthorized or malicious users.

DevSecOps

We have already mentioned DevSecOps , the security approach that integrates tools and controls from the development phase onward to ensure application security. It is indeed one of the core principles of Cloud Security. In Hybrid & Multi Cloud environments , the DevSecOps pipeline requires the integration of threat protection tools at various levels, often supported by Artificial Intelligence algorithms and techniques.

Read also: Cloud DevSecOps: what it is, benefits and tools

Business Continuity and Disaster Recovery

A company must also equip itself with measures and tools that can ensure operational continuity in the event of security incidents. Cloud Security solutions include backup tools that enable the restoration of normal operations after unforeseen events, avoiding business interruptions and data loss.

Governance and training

Beyond technological aspects, it is essential to devote equal attention to organizational and governance aspects . This includes the adoption of security rules and policies, raising staff awareness of cyber threats, and clearly defining relationships with the Cloud provider through the evolution of contractual tools, to ensure the clear definition of practices, responsibilities, and service availability levels. Cloud security, therefore, requires a synergy between technology, organization, and corporate governance .

What are the threats related to Cloud security?

The threats related to Cloud security are diverse and require an in-depth understanding to ensure adequate resource protection. SparkFabrik, as an active member of the OpenSSF (Open Source Security Foundation), is actively committed to pursuing the same goals as the organization — namely, making open source software (OSS) simpler to use while ensuring its sustainable development and proper maintenance.

To protect against Cloud security threats, it is indeed essential to also manage open source project dependencies , particularly in Software Supply Chain (SSC) management. Below is a list of the main security threats in the Cloud context.

Software Supply Chain Attacks

As mentioned, SSCs can become the target of malicious attacks. An increasingly complex supply chain exposes a higher number of attack points. In a recent OpenSSF article , our CTO Paolo Mainardi highlights a key point: the annual report conducted by Sonatype, which examines the state of the software supply chain, reveals an average increase in attacks on this chain of 742% per year since 2019.

READ ALSO: Secure Software Supply Chain for OCI Artifacts on Kubernetes

Lack of visibility

The loss of traceability in data access is also a significant threat, especially considering the vast number of Cloud services accessible by third parties. Lack of visibility can compromise the ability to detect and respond to unauthorized activities.

Multitenancy

Public Cloud environments host multiple client infrastructures under the same protection, making it possible for one company’s services to be compromised as a side effect of attacks targeting other companies. Resource sharing can expose organizations to unexpected risks.

Access management and Shadow IT

Managing access points in Cloud environments can be complex, especially when BYOD (Bring Your Own Device) policies are not implemented. Unfiltered access to Cloud services from various devices and geographic locations can create opportunities for malicious activities.

Regulatory compliance

Managing regulatory compliance in public or hybrid Cloud environments can create confusion. The responsibility for data security and privacy remains with the company, and consequently, excessive reliance on third-party solutions can cause costly compliance issues.

Misconfigurations

Misconfigurations represent a significant threat, with 86% of breached records in 2019 caused by misconfigured assets. Unintentional access by internal staff can result from default administrative passwords or inadequate privacy settings.

Best practices for Cloud Security

To ensure robust Cloud Security and therefore a secure and resilient Cloud environment, companies should adopt the following best practices.

1. Clarify responsibilities

Knowing exactly which aspects of Cloud Security companies are responsible for is fundamental. Never assume that the Cloud provider handles everything automatically. Clarity on shared responsibilities helps avoid security gaps and ensures effective risk management.

2. Cloud architecture visibility

Ensuring complete visibility of the organization’s Cloud architecture is fundamental. Lack of visibility can lead to ineffective threat management and a slow response to security incidents. Actively monitoring the Cloud environment enables a prompt response to anomalous behavior.

3. Full awareness of Cloud architecture

A solid understanding of Cloud architecture is essential to avoid configuration errors that could compromise security. It is necessary to increase knowledge of Cloud architectures through training, so that teams fully understand the Cloud environment and are able to correctly implement security policies.

4. Eliminate unnecessary elements

Deactivate unused ports and remove unnecessary resources. To reduce vulnerabilities, it is advisable to remove unnecessary instances and processes. Superfluous elements can constitute potential entry points for attackers. Implementing efficient resource management helps maintain a clean and secure environment.

5. Software Supply Chain Security (SSCS)

As we have seen, integrating software supply chain security is crucial. Ensuring that software components are secure and trustworthy is fundamental to preventing supply chain attacks.

Shared responsibility between the Cloud provider and the company requires careful management of best practices, also integrating third-party security solutions when necessary. Awareness , continuous training , and active monitoring are key elements for maintaining a secure and resilient Cloud environment.

Open source and Cloud Security

The use of open source software (OSS) is widespread in the Cloud ecosystem, but this practice is not without significant security risks. Addressing these risks requires an in-depth understanding and the implementation of preventive measures, with particular attention to the integrity of OSS software. Below are some risks associated with the OSS landscape.

• Third-party dependency: The use of open source libraries and frameworks implies a dependency on third parties. Vulnerabilities present in these components can be exploited by attackers to compromise the entire system.
• Maintenance and updates: Managing patches and updates in a complex Cloud environment can be challenging. Delays in fixing known vulnerabilities can expose applications and data to significant risks.
• Lack of visibility: Once again, lack of visibility can compromise security. In a distributed Cloud environment, it can be difficult to gain complete visibility over the open source libraries in use. This lack of visibility increases the risk of using components with known vulnerabilities.
• Lack of software integrity: Another extremely relevant point is maintaining software integrity. Sigstore is an example of a tool that plays a key role in preserving the integrity of open source software. It provides a platform for digital signing and verification of all software, facilitating the creation of a secure and transparent software supply chain. Using Sigstore helps mitigate the risks associated with OSS software compromise, ensuring that only verified and intact code is used in Cloud projects.

Cloud Security and legislation: the Cyber Resilience Act

The European Union has placed strong emphasis on cybersecurity through the Cyber Resilience Act. This legislation aims to strengthen digital defenses , promoting common standards and collaboration among member states.

In this context, SparkFabrik is concretely involved. We are active members of the Linux Foundation Europe and promoters of the #FixTheCRA initiative, of which Paolo Mainardi is an Advisory Board Member. This commitment reflects the desire to ensure that regulations take into account the specificities of the open source environment, thereby contributing to shaping a secure and balanced future for cybersecurity in Europe.

The evolution of Cloud security in Italy

Exploring the vast world of Cloud security, we have outlined the growing importance of CyberSecurity, highlighting the challenges and risks that companies face in the digital era and in the context of Cloud Computing. We have emphasized the need for an integrated security approach , constant awareness, and collaboration between institutions, companies, and the open source community to address the ever-growing challenges of a continuously evolving digitalized world.

The rapid growth in cyberattacks underscores the urgency of advanced protection strategies . There are encouraging signs showing growing corporate awareness around Cloud security. The increase in cybersecurity investments, including in the Italian market, indicates a growing focus on the need to defend against increasingly sophisticated threats.

The Italian cybersecurity market reached a value of 1.86 billion euros in 2022, recording a notable 18% increase compared to 2021. Despite this growth, the ratio of cybersecurity spending to GDP stands at just 0.10%, placing Italy last among G7 countries . In other words, significant progress has been made, but there is still a very long road ahead.

The need therefore arises to understand not only how to fully leverage Cloud resources, but also to master the art of management and control within this environment. This in-depth guide aims to explore the crucial role of Cloud Management , shedding light on its benefits, best practices and useful tools.

What is Cloud Management?

Cloud Management refers to the set of practices, technologies and tools used to manage and control a Cloud infrastructure environment . It involves the administration and orchestration of Cloud resources, including the management of virtual machines, storage services, networks, applications and other resources.

Cloud Management enables the efficient and scalable management of Cloud resources and services, improving operational efficiency, reducing Cloud costs and simplifying overall management of the Cloud environment. Additionally, to ensure data protection and regulatory compliance, it offers monitoring capabilities, report generation, access control and security planning (going so far as to protect applications not only through secure coding practices and Supply Chain Security , but also at the runtime environment level).

• The benefits of proper enterprise Cloud management

What problems does Cloud Management solve?

Adopting a proper Cloud Management strategy is essential for businesses that want to maximise the benefits of Cloud infrastructure and mitigate associated risks. Without adequate management, businesses can encounter a range of issues.

Resource waste can lead to high costs , while the lack of automation and control can result in operational errors, service outages and prolonged response times. Data security can be compromised, opening the door to attacks, sensitive data loss or regulatory violations . Furthermore, the absence of solid governance can make it difficult to manage permissions, monitor resources and ensure compliance with internal and external requirements. Finally, a poor Cloud Management strategy can slow down innovation and business scalability , preventing organisations from fully seizing the opportunities offered by the Cloud.

Cloud Management across Cloud Computing models

Cloud Management applies to all Cloud Computing models to provide resource management, operations automation, performance monitoring, security, governance and compliance capabilities. However, specific management requirements may vary depending on the service model adopted. The choice of a public, private or hybrid Cloud strategy and the advantages of choosing the latter are topics covered in these articles:

• Hybrid vs public vs private Cloud: a business guide
• What is Hybrid Cloud? When to choose it, examples and benefits

Infrastructure as a Service (IaaS)

Returning to Cloud Management across the different models, in the case of IaaS , Cloud Management focuses on managing the infrastructure resources provided by the Cloud provider . This includes the management of virtual machines, networks, storage and computing resources.

Platform as a Service (PaaS)

In the PaaS model, Cloud Management extends beyond infrastructure management to cover the platforms and development environments offered by the Cloud provider. This includes the configuration and management of runtimes, databases, development services and automation resources . Cloud Management in a PaaS environment focuses on application lifecycle management, horizontal scalability, version management and development resource control.

Software as a Service (SaaS)

In the case of SaaS , Cloud Management is primarily the responsibility of the service provider . However, end users can benefit from management features such as configuration customisation, account and access management, licence management and integration management with other applications.

What is Multi-Cloud Management?

Multi-Cloud Management refers to the simultaneous and coordinated management of multiple Cloud environments from different Cloud providers . In practice, it involves using different platforms to meet the specific needs of the business, such as using services from AWS, Microsoft Azure and Google Cloud Platform simultaneously.

Multi-Cloud Management is concerned with integrating and coordinating these different Cloud infrastructures so they can be managed as a single entity . This includes activities such as resource provisioning, performance monitoring, security management, capacity planning and cost management. The goal is to provide a unified interface to simplify Multi-Cloud environment management, improve operational efficiency and enable maximum business flexibility and agility.

What are the benefits of Multi-Cloud Management?

Multi-Cloud Management enables businesses to make the most of the different features and services offered by various Cloud providers , avoiding dependency on a single vendor and gaining advantages such as workload optimisation, security and more integrated cost management. However, it requires a dedicated strategy and management tools to effectively and consistently manage the entire Multi-Cloud environment.

Workload optimisation

Through balanced distribution of workloads across multiple Cloud environments, efficient resource utilisation is ensured. Additionally, through redundancy and resilience, it enables workload migration in the event of outages or malfunctions on a Cloud provider. Geographic distribution of workloads improves accessibility and reduces latency, while flexibility in service selection allows adaptation to business needs.

Security

By distributing workloads across multiple Cloud providers, the risk of dependency on a single vendor is reduced. Furthermore, diversifying security measures across different Cloud environments helps strengthen the overall system. Centralised monitoring and vulnerability management simplify the detection of suspicious activity and the adoption of appropriate security measures. Finally, regulatory compliance and sensitive data management are facilitated by the ability to choose Cloud providers that meet specific regulations and security requirements.

Cost management

A well-planned and executed Cloud Management strategy enables cost control in several ways. Through monitoring, forecasting and optimising Cloud resources, it is possible to identify and mitigate waste, eliminate underutilised resources and scale resources based on actual needs. Additionally, cost governance, budget allocation and continuous monitoring allow organisations to maintain a clear view of ongoing costs and take timely action to avoid surprises.

Cloud Management, FinOps and GreenOps

Cloud Management, FinOps and GreenOps are related concepts that focus on different dimensions of Cloud usage. These three disciplines work together to create a comprehensive approach to Cloud environment management. Cloud Management provides the tools and expertise needed for managing and optimising Cloud resources. FinOps adds a financial perspective , enabling accurate cost control and alignment with business objectives. GreenOps, on the other hand, integrates a sustainability vision into Cloud resource usage, helping to reduce the overall environmental impact.

• FinOps: what is it? Why switch to financial Cloud management
• GreenOps and FinOps for efficient Cloud management
• Green Cloud Computing: what is it and why is it gaining attention

Cloud Management tools: choosing the right platform

Choosing the right Cloud Management platform requires analysing several criteria. First, it is essential to evaluate the features and capabilities offered by the platform, such as resource provisioning, operations automation, performance monitoring and security management. Additionally, the platform should integrate with existing Cloud environments and support the necessary scalability and flexibility . Security and regulatory compliance are crucial aspects, as are usability and an intuitive user interface . The support and assistance provided by the vendor, along with the costs associated with implementation and usage, are also factors to consider carefully. Below is a brief description of some market-leading Cloud Management platforms.

Flexera RightScale

RightScale is a Cloud Management solution that offers a wide range of features for managing and optimising infrastructure. With its centralised interface, users can orchestrate, monitor and automate provisioning operations and Cloud resource management across multiple providers. Security is a priority for RightScale, which offers advanced features such as access and permission management, threat monitoring and regulatory compliance. This enables businesses to protect their sensitive data and ensure a secure Cloud environment. The RightScale platform is designed to be intuitive and easy to use, enabling users to manage resources efficiently and automate complex operational tasks.

Scalr CMP

Scalr is a Cloud management platform recognised as a leader in the sector according to the Gartner Magic Quadrant. Its strength lies in the comprehensive range of features offered, which enable both self-service use and integration with other environments via API. Among Scalr’s strengths are the completeness of its features, excellent support for policy enforcement and self-service usage. Additionally, the solution can handle up to 1,000 concurrent users for application requests and distribution. The interface is simple to use, providing an intuitive user experience.

Morpheus Data

Morpheus Data, also recognised as a leader in the Gartner Magic Quadrant, is a CMP (Cloud Management Platform) that can be installed on-premise at client data centres or provided in hosted mode by an MSP. According to analysts, Morpheus Data has several significant strengths: a wide range of features covering all major areas, a user interface that is simple to use and manage, the ability to be completely infrastructure-agnostic and an extensive catalogue of integrations with public and private Cloud providers, as well as third-party applications. Additionally, Morpheus Data includes integrated services such as monitoring, logging, backup, load balancing and file sharing. The Morpheus Data Cloud management platform is fully agnostic and supports more than 80 pre-configured integrations with third-party software. It offers an excellent user experience thanks to its intuitive interface.

VMware CloudHealth

CloudHealth is software designed to monitor, optimise and automate workloads in both Multi-Cloud systems and traditional data centres. The platform offers a wide range of pre-configured integration components for common infrastructures, as well as monitoring, automation and application management tools. It is widely recognised for its excellent cost management, ease of policy creation and quality of supported processes. Key CloudHealth features include advanced reporting, Cloud resource usage forecasts for weeks and months ahead, performance management, migration assessment, policy management and Cloud automation. The platform also provides real-time analysis to enable proactive security and compliance management.

Micro Focus

The Micro Focus Hybrid Cloud Management platform is the result of the transformation and redesign of certain components of the HPE offering, acquired in 2017. Micro Focus HCM stands out for its automation, orchestration and governance capabilities for hybrid and Multi-Cloud environments, as well as its data analysis, monitoring and protection functions, which are undeniable strengths of the solution. Among the advantages that led Micro Focus HCM to be included in the Gartner Magic Quadrant are its quality in provisioning and orchestrating complex and heterogeneous environments, along with a high-level support service. The product architecture is container-based, offering an agile and scalable infrastructure.

Cloud Management Platform: what is it and which one to choose?

The benefits of the Cloud, without its complexity

Originating at Google in the early 2000s, SRE is an increasingly adopted approach to ensure reliability and continuous improvement of web products. We understand together what it is, what its pillars are and the benefits for companies.

What is SRE (Site Reliability Engineering)?

Site Reliability Engineering, SRE for short, is one of the ‘hottest’ acronyms in the development world.

The aim of the SRE approach is to increase the reliability of systems: it is a set of principles, practices and organisational constructs that allows both to make existing systems work and to innovate them . This second aspect is fundamental, because one of the objectives of SRE is not only to keep the promises made about the management of systems, but also to do so while services are constantly being improved incrementally with new functionalities.

Let us start immediately with an important specification: the word ‘Site’ in the definition should not lead us to think that this approach is only applicable to the creation and management of sites. The same principles are in fact suitable for improving the performance of any software system (sites, web or mobile applications, etc.). Any system administrator can therefore aspire to bring the SRE approach into his or her team.

Check out this video for a complete overview of Site Reliability Engineering (in Italian only):

SRE and Google: from birth to today

SRE practices originated and developed within Google, starting around 2003. More recently, Google has decided to make public the approach that has enabled the company to build, monitor, improve and maintain some of the most widely used online services in the world.

To understand the SRE philosophy even before the more practical aspects, we can quote Ben Treynor Sloss, the man who coined the term SRE and who is now vice-president of engineering at Google.

“SRE is what happens when you ask a software engineer to design the Operations function,” the manager said in an interview .

The SRE team or manager thus performs a job that has historically been done by the Operations team, but does so by adding the mindset and skills of software engineering: the cornerstone is the (typically engineering) ability to replace human work with automation .

With these premises, it is immediate to perceive the value of the key principles defined by Google for SRE practices, namely:

• Neutral’ risk management . i.e. do not pretend that errors will never occur in the life of an application workload. Rather, accept this fact and be prepared.
• According to the intuition that those who use the system and those who keep it operational have different service objectives at heart, a careful definition and shared evaluation is necessary for these to converge from the outset and for the value delivered to be correctly perceived by each stakeholder.
• Minimise non-value-creating and repetitive activities.
• Set up monitoring to keep the situation under control even in distributed contexts.
• Design releases that do not jeopardise the operability of the platform or system.
• Keep the overall complexity of the system low, allowing it to increase physiologically over time

In addition to the principles of SRE, Google also has a set of practices that implement the various principles and try to keep the system up and running. An SRE team must organise itself to respect what Google considers to be the hierarchy of a reliable service .

1. At the base of the hierarchical pyramid we find monitoring and the ability to identify a problem before users notice it.
2. Immediately above we have the team’s ability to respond to a problem with a root cause analysis and easily testable and applicable corrective fixes.
3. Finally, at the top of the pyramid is the focus on design and the computational resources that a reliable product requires.

Reliability as a basic principle of good architecture

Reliability, or dependability, is the ability of an application to operate correctly and consistently when expected. According to AWS, reliability is one of the core principles of the Well-Architected framework . It is a manual of best practices and checklists that should be kept in mind when designing any Cloud application.

AWS lays down a number of guidelines that can increase the reliability of a workload, among them:

• the ability to recover a workload from an abnormal situation automatically, thanks to appropriately tested monitoring tools and recovery procedures;
• increase horizontal scalability to decrease the impact of failures on the individual node or instance;
• finally, a more diligent analysis and tuning of the computational capacity allocated on the Cloud, with the aim of avoiding the saturation of available resources and keeping costs under control. By observing and adapting the sizing of resources, it is possible to avoid over-provisioning, i.e. the use of oversized resources that are wasted most of the time for which they are paid .

SRE and DevOps: similar but not equal approaches

Having reached this point, we cannot avoid mentioning another approach that favours collaboration between Operations and Development teams: we are talking, of course, about DevOps . There is an undeniable closeness between SRE and DevOps, despite the fact that the two practices developed independently. Both aim to bridge the gap between the two teams, with the objective of improving the life cycle (i.e. release) and product quality.

Although the two approaches have similar goals, they are not mutually exclusive: on the contrary, we can see SRE as a concretisation of the DevOps approach . SRE embraces the DevOps philosophy, but focuses its attention on the development and consolidation of practices to measure and achieve reliability.

In other words, SRE sets operational rules for success in the various DevOps areas. If DevOps focuses on the ‘What’, SRE is decidedly unbalanced towards the ‘How’.

Tools to support SRE

SRE is a technology-intensive practice, which is why a reference technology stack for SRE engineers has been defined over time.

As mentioned above, SRE is very close to DevOps, so it is possible to liken the tools used by this type of professional to those of a DevOps Engineer.

Specifically, they are needed:

• tools enabling work planning (Jira, Azure Boards);
• software implementation (Eclipse, Visual Studio Code);
• the packaging of build artefacts, (Jenkins, Azure Pipelines);
• the configuration of the installed software (Terraform, Ansible);
• an installation environment - preferably containerised (OpenShift or Azure Kubernetes Service);
• Finally, a monitoring suite capable of collecting, aggregating and presenting metrics and KPIs derived from the application (Grafana, Azure Monitor) is essential for each SRE team.

What does an SRE team or engineer do?

The SRE manager (or SRE team) is in charge of a very wide range of functions, including system availability, latency, performance, efficiency, monitoring, change management, emergency response and capacity planning.

To understand how crucial this figure is in some projects, one only has to read the first sentence of Benjamin Treynor Sloss’ LinkedIn profile: ’ If Google stops working, it’s my fault ‘. Ironic, but not without a kernel of truth.

The importance of the SRE role lies not so much in the activities and skills (which are not unique, and could also be taken over by other teams) as in the modus operandi adopted. The SRE team works with data, which it learns to collect, read and exploit, and with process automation, which allows it to increase control and normalise code. This approach reduces repetitive task overload (the so-called ’toil’) and errors.

If you are interested in frameworks that exploit a data-driven approach and team collaboration, DevSecOps might be of interest to you.

The Error Budget: what it is and why it is important

The SRE team is also in charge of calculating and managing the error budget . This is a fundamental strategic concept, which we could define as the tool used by SRE to balance service reliability with innovation .

The assumption of this approach is that systems are dynamic objects that develop and change over time , evolving positively but also bringing a downside: changes are a major source of instability. The error budget provides a control mechanism to shift the focus from innovation to stability when necessary.

The SRE team defines an error budget based on a set of metrics (we will look at these in a moment) and a time frame in which to measure it. If incidents increase significantly compared to the available error budget, the SRE team’s priority immediately becomes to help solve the problems by bringing the development and operations teams together and collaborating .

Thanks to the error budget, therefore, it is possible to plan and schedule change without sacrificing too much availability.

Service Levels: SLI, SLO and SLA

In order to align all stakeholders on the objectives of service reliability and availability, SRE introduces three key concepts: SLI, SLO and SLA.

• SLI, Service Level Indicators. These are the metrics used to measure the performance or general behaviour of the application. In other words, we could call them the KPIs to be taken into consideration. These are often particularly relevant KPIs for users, such as response time or error rate.
• SLOs, Service Level Objectives. These are the objectives to be achieved for each metric, i.e. for each SLI. The objectives set must wisely balance quality, to be assessed according to business needs, and the cost of achieving it.
• SLA, Service Level Agreement. It includes the legal aspects that come into play if the system does not achieve its SLOs.

It should be noted that one of the basic elements of the SRE philosophy is that errors are expected and accepted by all involved . SLIs, SLOs and SLAs serve to set a goal and make it achievable: not by avoiding errors altogether, but by analysing them afterwards in order to improve the entire process (and without ever pointing fingers).

ABOUT IT : 6 SRE best practices to know

Site Reliability Engineering: the benefits

Investing one’s time in the development of SRE practices can be very cost-effective. The advantages are easy to see:

• Higher quality
• Constant product evolution
• Reduction of errors and malfunctions

Let us try to break down these benefits in more detail and see what the positive consequences are for business and work teams.

CONSTANT MONITORING OF THE PROJECT

The complexity of some projects is such that it requires a top-down view, clear and focused on the really relevant aspects. This is precisely what happens with the advanced monitoring system that SRE requires to be implemented: selected metrics allow key parameters to be measured without ever losing sight of the project as a whole.

What you get is a concise and timely view of what is happening throughout the project, with valuable information for other business areas as well . We think of marketing, sales, support, but also of the main company stakeholders who require to be aligned on the status of work and performance.

TIMELY ERROR RESOLUTION

SRE practices have the great advantage of favouring the proactive detection and resolution of software bugs and vulnerabilities . In the absence of a monitoring and automation system such as that fostered by SRE, it often happens that errors enter production causing delays, malfunctions and downtime of services.

The consequences for business and turnover can be very heavy; that is why the selection of the most relevant KPIs and the setting of an achievable and considered target for each SLI is so important.

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CLARIFY AND MEET CUSTOMER EXPECTATIONS

Another great advantage of using SLAs, SLOs and SLIs is the ability to focus on the end-user’s expectations at an early stage and to draw up a plan to meet them .

Having clearly defined targets and service thresholds allows one to constantly judge the status of work and proactively align actions against predefined KPIs. All of this while keeping the end user and his expectations in mind (with all the benefits this brings in terms of digital services offered, and therefore turnover generated).

INCREASED FOCUS ON VALUE CREATIONORE

A more efficient system, with fewer problems and where repetitive tasks are automated, is a system that leaves more free time for the teams working on it . And that time should be invested productively, for example by creating new functionalities or improving existing ones. The Operations team, on the other hand, has the opportunity to work more on improving the configuration and creating tests that can identify possible defects in the system.

The greater availability of time and less stress due to mistakes and delays also leads to greater collaboration between teams , together with the ability to discuss priorities and objectives more responsibly and creatively.

CONTINUOUS CULTURAL IMPROVEMENT

There is a final and very important benefit of SRE: the creation of a culture of collaboration between people and between teams, where decisions are made with not only one’s own work in mind, but above all with the consequences for the user and colleagues in mind.

SRE fosters an open and trusting mentality among the teams, which results in a better business climate on the one hand, and a high quality output on the other.

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In recent years, Kubernetes has gained positions among the most talked-about technologies in the IT universe. Developed by Google for internal use and launched in an open source version in 2014, today the well-known platform for container orchestration is of interest to more and more companies because it allows them to automate application management, contributing to the resilience of IT services.

What is Kubernetes?

In the official documentation , Kubernetes (abbreviated to K8s or simply Kube ) is defined as an open and flexible platform that allows workloads and containerised services to be managed , enabling both automation and declarative configuration.

Kubernetes is the direct evolution of Borg , the cluster management system designed by Big G and used internally. It thus inherits from its predecessor the characteristics of architecture and operation, which are continuously updated and enriched by members of the rapidly expanding international community.

The project is currently maintained by the Cloud Native Computing Foundation (CNCF) , part of the non-profit organisation Linux Foundation, which brings together more than two hundred start-ups together with the world’s largest Cloud solution providers. These include not only the Mountain View multinational, but also Microsoft, IBM, Amazon Web Services and Alibaba Cloud.

What is Kubernetes used for?

In ancient Greek, the noun ‘Kubernetes’ means ‘helmsman’ : the parallelism with the platform’s main function of ‘piloting’ the container ecosystem, ensuring scalability, failover and efficient deployment is therefore obvious.

In order to understand how Kubernetes intervenes in the management of the enterprise application ecosystem by conferring elasticity and continuity of services, it is first necessary to clarify the concept of containers starting from the evolution of information systems.

Evolution of IT systems and containerisation

1. Physical Servers Under the traditional infrastructure model, applications run on physical servers, competing for resources without the possibility of rational allocation. If a peak of requests were to be generated, one application could take away resources without limit , compromising the functionality and performance of others running on the same server.
2. Virtual machines Virtualisation has overcome this problem by adding a level of abstraction, segregation and control of assets. Applications are isolated within several virtual machines (guests) that reside on the same physical computer (host) , sharing the different components. Using specific software (hypervisor) , hardware resources are distributed dynamically between the guest systems, according to application needs and ensuring proper balancing.
3. Container Containerisation represents a further step forward compared to virtual machines. Whereas VMs are complete systems, which abstract all components of the underlying hardware system, containers virtualise only the runtime environment , which is necessary for running applications. Containers are therefore ’lighter’ than VMs and, since they are decoupled from the infrastructure, they work in any development, test or production environment. They can therefore guarantee greater portability of software across modern multi-cloud ecosystems and favour the use of microservice architectures, whereby applications are designed as a set of independent, combinable functional units.

Kubernetes simplifies container management

Despite the many advantages of containerisation, from more efficient use of resources to consistency of operation on different hardware systems, there is a downside. Containers in the order of tens of thousands can also circulate within corporate IT infrastructures and the biggest challenge is the complexity of orchestration .

Kubernetes intervenes by automating container management operations, ensuring continuity of services and efficient allocation of resources.

Going into more technical detail, Kubernetes performs a rich set of functions:

• workload balancing : in the event of traffic peaks to a container, Kubernetes allows requests to be distributed evenly among several containers while keeping the service stable;
• Dynamic resource allocation : Kubernetes can be instructed to automatically provide each container with an appropriate and predefined level of computational resources and memory;
• Automated rollout and rollback : Kubernetes can create and remove containers by rebalancing the allocated resources to achieve the desired state;
• management of critical information : Kubernetes stores, distributes and updates the configurations and sensitive data (e.g. passwords and OAuth tokens) of applications, guaranteeing high levels of security.

READ ALSO : Orchestration vs Choreography, which one should you use? The pros and cons

How does Kubernetes work?

Having clarified the purposes, to fully understand how Kubernetes works, it is necessary to delve into the main components underlying its architecture.

• Master : This is the machine that controls the Kubernetes nodes and dynamically allocates containers according to available resources and predefined parameters;
• Nodes : controlled by the master system and grouped in clusters, they represent the virtual or physical machines tasked with performing the assigned tasks;
• Pod : indicates the set of containers that reside on the same node, sharing computing, storage and network resources in addition to the IP address.
• Kubelet : this is a software agent running on the nodes which, upon receiving orders from the master machine, initiates container management according to instructions.

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The advantages of Kubernetes

Kubernetes represents a valuable opportunity for companies that want to streamline application management within hybrid and multi-cloud ecosystems.

The use of the open source orchestration platform in fact makes it possible to achieve a number of advantages such as the possibility of orchestrating containers on different hardware systems, optimising resources while guaranteeing application performance, ensuring the proper functioning of containers and continuity of service , automating the distribution and updating of software, and setting different levels of security.

This results in five main business benefits :

1. First of all, thanks to automation, the development, release and deployment processes of containerised applications are simplified and accelerated;
2. Dynamic container management and intelligent resource allocation enables new efficiency gains and cuts in IT expenditure ;
3. The ability to rapidly scale containers and handle peak demands increases application availability and service continuity;
4. The portability of containerised applications increases freedom with respect to infrastructure choices;
5. Containerisation can be a shortcut to migrate legacy applications to the cloud, guaranteeing functionality and performance in any environment.

The challenges of Kubernetes

Kubernetes offers a particularly attractive range of opportunities, but before deciding on a possible adoption, one must also assess the possible criticalities of implementation and use.

The Kubernetes universe moves very quickly: continuous innovation is among the most appreciated features of open source technologies and, thanks to the large community, updates to the platform are very frequent. On the other hand, all this can be confusing for a company approaching this technology for the first time.

Kubernetes adoption initiatives can require a significant commitment in terms of time and resources. Business decision makers are not always willing to invest in new projects when budgets are barely sufficient to maintain the status quo. Moreover, IT personnel are not always inclined to embrace change and take risks.

Kubernetes is a relatively recent technology that requires specific skills that are not always present in the company. Instead, professionals with up-to-date knowledge of application development, operations management and data governance are needed for successful adoption.

TO DIVE DEEP: 3 mistakes to avoid when adopting Kubernetes

When and why to use Kubernetes

Putting pros and cons on the scales, does Kubernetes pay off? And under what circumstances? In the light of the above, containerisation and the use of the open source orchestrator can bring significant advantages to companies, in terms of technological efficiency, organisation and business benefits.

Any enterprise wishing to improve the flexibility of its application fleet, accelerate the development and release process, ensure continuity of services, and optimise IT costs, should consider the alternative of containers and Kubernetes. The option becomes particularly compelling in the case of heterogeneous and distributed ecosystems, in order to facilitate the portability of software from one environment to another.

However, the adoption path can be complex and one has to start off on the right foot, in light of a few considerations. First of all, the roadmap must be customised and gradual: it requires time and foresight, but above all it needs multidisciplinary skills and established expertise.

It also requires the ability to change mindset and organisation : containers presuppose a completely new way of designing and managing IT architecture, so the approach to work and technical knowledge must also evolve. This is why the consultancy and support of a specialised partner can make all the difference, filling the skills gap and transferring a new way of working.

The microservice architecture allows a Web application to be structured as a collection of small services loosely coupled together .

The term was officially born in 2005, originally as “Micro-Web-Services.” Although there is no single definition of micro-services, the goals and mode of operation of this architecture are clear. The modular approach allows for the independent development of a series of services , each with a specific function and able to communicate with others via API.

This approach then transforms the application into an aggregation of smaller, independent functional units in which a component and its data are considered a single unit with as few external dependencies as possible .

Microservices and Cloud Native

Microservices are often associated with another term, Cloud Native, but a distinction must be made. Microservices are a software engineering architecture, while Cloud Native is a true paradigm for creating modern applications. Cloud Native methods and tools enable the enterprise to react quickly to changing market demands by proactively adapting its IT services.

Operationally, Cloud Native applications are applications that can run on a private, public, or hybrid cloud. The microservices approach is one of the paradigms for building Cloud Native applications. Alongside them we find containers, container orchestrators (such as Kubernetes) and the use of declarative APIs, as well as Agile development methodology and DevOps practices based on Continuous Integration and Continuous Delivery (CI/CD).

A microservice architecture finds containers the perfect technology to express its full potential. Containers allow a microservice to run independently of the underlying infrastructure.

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• Kubernetes: what are the key benefits for companies?
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Why did microservices arise?

Microservices are simultaneously the evolution and logical development in the history of software engineering. The path has been long and took its first steps from monolithic applications.

Monolithic architecture

The monolith architecture provides, simplifying the concept, that the user interface (the frontend) and the interfaces for accessing and manipulating data (the backend) are contained in a single, independent, indivisible, modularity-free piece of software.

A monolithic application must contain everything needed to complete a particular task . Today this perspective is potentially outdated: thanks to the modular approach of software, it becomes possible to use, update or modify a series of small components independently without the need to deploy or deploy the entire application.

Monolithic applications are functional in a circumscribed environment, as the early mainframes were and as personal computers have long been as well, and provide integration of functions in nonstandard environments.

Over time, however, the complexity of the problems to be solved and the increasing power of computers led to the creation of increasingly large and heavy monolithic applications. Such structures have become very expensive to update quickly and o maintain properly: they can be said to have outgrown the ability of programmers to exploit them effectively.

“As long as there were no machines, programming was no problem at all; when we had a few weak computers, programming became a mild problem, and now we have gigantic computers, programming has become an equally gigantic problem.” — Edsger Dijkstra, computer scientist

Here the IT world had to identify new development methodologies and processes to improve the quality of software and its management. First came procedural and object-oriented programming to manage large, complex projects with undefined specifications in detail. Later, with the development and growing importance of the Internet, various architectures emerged among which the most widely used is SOA, Service-Oriented Architecture .

• FOR MORE: Microservices and Cloud Native Applications vs. Monolithic Applications

SOA: Service-Oriented Architecture

Rather than a revolution, SOA is considered an evolution of existing development practices that allows the enterprise to build its applications with a holistic and nonrigid approach. SOA is an architecture in which some components of an application provide services to components of other applications through a communication protocol that operates independently and nonproprietarily over a network.

Multiple SOAs, joined by a dedicated hardware or software infrastructure, can become the functional equivalent of a larger, more complex monolithic application, without many of the associated disadvantages. SOA encourages the sharing of individual software components and their reuse.

In the service orientation that underlies SOA, we can already glimpse what will be the future development of the architecture. We are clearly talking about microservices, which make the modular approach their strong point.

From SOA to microservices

The differences between the two approaches are numerous . Architecturally, SOA is designed to share resources through services; microservices, on the other hand, are services that run independently.

SOA is organized on larger and more modular services than microservices that are centered on a single function. In addition, the Service-Oriented Architecture shares data storage space while each microservice has its own independent data storage .

As a communication system, SOA uses ESBs (enterprise service buses) and microservices use APIs ; for remote services, SOA uses protocols such as SOAP and AMQP, while microservices rely on REST and JMS.

Finally, while SOA is more efficient for projects involving large-scale integration, microservices are designed for Cloud Native web applications that are easier and faster to design and put into production.

Finally, while SOA is more efficient for projects involving large-scale integration, microservices are designed for Cloud Native web applications that are easier and faster to design and put into production.

READ ALSO: Why and how to make a Cloud Native application

What are the advantages of microservices?

Implementing a project based on microservices brings a number of advantages:

• Microservices make it possible to reduce the architectural complexity of an application by deconstructing it into a series of point services that are faster to develop and maintain.
• Each feature can be scaled up quickly and deployed across multiple environments independently of the rest.
• The time to develop and then to put the application into production is greatly reduced, which positively impacts time to market.
• The application is more resilient because individual services do not impact the operation of the entire application, and maintenance operations are faster.
• Development teams are smaller and very specialized in a single part of the application that has a smaller code base.
• Agile methodology and DevOps development practices can be used more easily, enabling collaboration between Developers and Operations with a Continuous Integration and Continuous Delivery approach.

When (not) to choose microservices?

There is no “one size fits all” approach to application development that solves all problems . As much as microservices are the new market standard, the monolithic approach may actually be the most cost-effective solution for some companies.

For example, it is advisable to opt for traditional architecture if:

• you have little time and budget to make an MVP (Minimum Viable Product);
• one needs a very simple application that does not require special scalability and flexibility;
• you do not have the necessary skills to develop in microservices (and you do not intend to rely on a specialized partner, which is still a recommended choice if you are dealing with new and inherently complex technologies).

In most cases, however, the choice of microservices turns out to be better suited to meet business demands because it provides more flexibility, speed and scalability .

Evidence of the growing popularity of this approach also comes from data. For example, Statista’s 2021 surveys show that 71% of companies use microservices at least partially . O’Reilly’s 2020 survey found that 28 percent of respondents have been using microservices for at least 3 years, while 61 percent have been using them for a year or more. At the level of liking, 92% expressed that they have benefited from the introduction of microservices.

Challenges and complexities of microservices

Beyond specific cases, it is important to consciously assess the challenges that microservices bring to the enterprise.

A microservices-based architecture requires a different hosting infrastructure than traditional monolithic applications , which must be tailored to the needs of the business, made secure and maintained. And it works best for companies that need to innovate quickly to a very diverse user base.

Microservices have a different complexity than monolithic applications, but one that should not be underestimated. The focus is on communication between individual services in the application , which can include several dozen to several hundred different services for larger projects.

In addition, debugging a microservice-based application is more complex because one has to trace the source of each individual problem through the logs of tens or hundreds of small components. Still, the testing phase of microservices integration presents some difficulties because they are distributed in different environments and it becomes complex to replicate them in a local testing environment.

Finally, since the operation of a microservices-based application is achieved through the use of APIs , constant attention must be paid to the evolution of APIs . Indeed, if new versions of APIs are defined, it can be very complex to understand how they will impact the microservices that use them.

Net of these considerations, microservices architecture proves to be the most innovative and advantageous choice for those companies that are able to cope with the added complexity because of the many benefits that can be achieved

From monolith to microservices: the stages of modernization

A microservices-based project can be developed from scratch or, more likely, will be the result of a transformation starting with a legacy application .

There are two popular refactoring strategies for managing the transformation from a monolithic to a microservice-based application: implementing all new functionality as services and extracting individual services from the monolithic application.

The first case is the easiest to deal with as it does not require fragmenting the entire legacy application. And it also has the advantage of showing a greater speed in getting new software into production than the traditional monolithic model.

However, the only way to completely modernize the monolithic application is to extract one module after another from the application and convert it into a service. This is done with a preliminary analysis and mapping phase: the individual services that will replace the different modules in the monolithic application must be defined. This is followed by the development, testing and deployment phases to redirect traffic to the new services. At this point, the functionality transformed into microservices can be removed from the monolithic application.

In conclusion, migrating a monolithic application to a microservices-based architecture requires a preliminary activity of analyzing and then converting the individual mapped components iteratively.

Being competitive today means being able to respond promptly and without errors to the growing and increasingly complex demands of users . Companies that are unable to offer the best will progressively see customers turn to other players on the market. This is where Cloud Native applications come in .

Cloud Native means changing the way applications are designed and built, focusing on speed and agility . Cloud Native applications are designed to change quickly, at scale and to be resilient.

New development models involve the use of technologies such as microservices , containers and APIs, but also DevOps practices, with the aim of accelerating time-to-market, aligning digital services with business needs and ensuring software portability in distributed IT systems.

Traditional applications VS Cloud Native applications

We have already emphasised the importance of having flexible and high-performance applications, a goal that is difficult to achieve today with traditional applications designed according to a monolithic approach . They do not allow for rapid evolution, they cannot keep up with new technologies and, as a result, the company using them will probably struggle to remain competitive.

In the case of using one or more legacy applications with monolithic architecture, it is therefore advisable to start migrating to a Cloud Native architecture. This process is based on breaking down monoliths and highly coupled applications into simpler components.

Why take this path? Adopting Cloud Native principles, whether in the context of ex-novo development or modernisation, enables significant results to be achieved:

• From a strategic perspective, Cloud Native realises benefits such as speed of delivery and optimised user experience that enable the business to work better and increase profits;
• from an operational perspective, it enables developers to support collaboration with Operations and the organisation of work in agile mode.

To develop and design modern applications and/or to modernise existing ones, the best practice is to follow the methodology called 12Factor, which includes a set of principles and best practices to make the application Cloud Native (more on this later).

The 4 pillars of Cloud Native applications: Microservices, Containers/Orchestrators, APIs, DevOps

The application architectures, technologies and methodological frameworks underlying Cloud Native development jointly support the needs of enterprises that demand flexibility, speed of response, performance and efficiency from IT.

To summarise, there are four pillars underpinning Cloud Native solutions:

• ARCHITECTURE: Microservices
• INFRASTRUCTURE: Containers / Orchestrators
• COMMUNICATION: APIs / Service Mesh
• PROCESSES: DevOps, CI/CD

Below we briefly look at them, if you want to go deeper you can read this article: why Cloud Native is the answer to a modern, changing market .

ARCHITECTURE: Microservices

The microservice architecture suggests a new model for building applications, based on individual, independent functional units . Each function can thus be compiled, implemented or modified without affecting the functioning of the entire application. A small, dedicated and specialised team works on each microservice.

The advantages? Definitely worth mentioning is the reduction of architectural complexity and the possibility of scaling and distributing single functionality across different environments. It also increases the overall resilience of the application, since a disruption on one microservice will not affect the functioning of the other services.

Another benefit stems from the reduction of development time and time-to-market , as one can act on individual components without stopping or slowing down operations related to other microservices. Also to be considered is the improvement of the developers’ responsiveness and software quality (due to focused skills and know-how).

INFRASTRUCTURE: Containers / Orchestrators

Containers are virtual instances of a complete runtime environment that host the entire application (built in Cloud Native mode or according to a monolithic architecture) or microservices (individually or in clusters), allowing them to run independently of the underlying infrastructure.

Containerisation , which can be realised with specific tools such as Docker , therefore proves to be an extremely effective technique in hybrid and multi-cloud environments: the decoupling of hardware and software components guarantees the full portability of applications on different systems, without distinction between on-premise data centres and cloud infrastructures.

Containerising applications means eliminating the inefficiencies in functionality and performance that may arise when moving between heterogeneous environments. The flip side of the coin is the increased complexity of container management, especially when the number of applications to be deployed, distributed and maintained is particularly high. The use of container orchestration platforms, such as Kubernetes , proves to be the ideal solution.

COMMUNICATION: APIs / gRPC, Service mesh

When designing and building a Cloud Native application, communication becomes a significant design decision .

There are many questions to be answered: how does a front-end client application communicate with a back-end microservice? How do microservices communicate with each other? What are the principles, patterns and best practices to consider when implementing communication in Cloud Native applications?

The strategies to be implemented are manifold and must be carefully considered at the design stage. We can rely on established patterns such as: API Gateway / Management, gRPC, Service mesh.

The use of a modular microservice architecture allows all communication between the various application components to be based on lightweight, technology agnostic protocols. This constitutes a further step towards reducing the complexity of deployment , allows architectural complexity to be governed and increases the level of independence of developers who can concentrate their efforts on business value rather than on infrastructural aspects.

PROCESSES: DevOps, CI/CD, GitOps

DevOps is a methodological framework that facilitates collaboration between Developers and Operations, enabling efficient and effective processes for managing the software lifecycle. DevOps follows the same principles as Agile development methodologies (e.g. Scrum), emphasising the creation of synergies between teams.

The purpose of DevOps practices is simple: to eliminate the traditional lack of communication between those who develop the application and those who manage it once it is released, by encouraging a sharing of responsibilities.

How? For instance through CI/CD practices and GitOps , methods for frequent app distribution to users in which automation plays a central role.

• CI - Continuous Integration :
• changes to the code made by different teams are constantly channelled to a central repository, allowing the alignment of parallel activities within a single project.
• CD - Continuous Delivery : releases are made with a very high level of frequency.
• GitOps is a way of implementing Continuous Deployment / Continuous Delivery for Cloud Native applications. It focuses on a developer-centred experience also with regard to infrastructure activities, using tools with which developers are already familiar, such as Git and Continuous Deployment tools. To learn more, have a look at our talk and slides .

But what are the concrete benefits of the framework? These include the possibility of streamlining and agile processes , with a consequent increase in release speed; the increased quality of the application , due to automation that reduces human errors and continuous feedback between the two teams; and the increased reliability and scalability of the application.

Moving to Cloud Native: how to modernise a legacy application

Having stated the basic principles of Cloud Native development, however, it must be borne in mind that companies have built up a wealth of legacy applications over the years that today must also be able to function in modern Cloud environments. To completely rewrite the entire application park in a Cloud Native key would be a titanic and foolhardy undertaking. There are in fact several ways to modernise an application by bringing it to the Cloud, and the correct approach must be weighed up on a case-by-case basis.

Here is a brief overview of the viable options:

• rehosting (also called Lift&Shift ) consists of simply migrating the application to the Cloud, without making any changes. To be used if the loss of functionality and performance is zero or minimal;
• refactoring involves small changes to the source code to eliminate inefficiencies or malfunctions in the application, ensuring optimal or otherwise adequate performance even on the Cloud;
• rearchitecting introduces a number of properties and techniques typical of Cloud Native design, from containers to APIs, deeply intervening in the structure of the application;
• rebuilding a more drastic operation, which involves rewriting the application from scratch, according to Cloud Native practices and with the aim of rebuilding all functionality. Since it is a complex and costly procedure, it is only recommended for business-critical applications and in the presence of serious malfunctions;
• replacing finally corresponds to the replacement of the software with a ready-to-use SaaS solution, equivalent in functionality and use.

Development of a Cloud Native Application

In order to correctly develop a Cloud Native application, we recommend proceeding according to the Twelve-Factor methodology, which defines twelve general principles for building next-generation software or modernising legacy software, guaranteeing performance, portability and scalability in Cloud environments. The Twelve-Factor model aims to optimise development time and speed up software deployment, adding quality, flexibility and code portability.

We see three good practices to follow: replicability of dependencies, separation of code and configurations, stateless approach .

The benefits for the company in choosing a Cloud Native application

Enterprises that opt for Cloud Native applications achieve significant results in terms of business and competitiveness. First of all, they can have applications optimised for hybrid and multi-cloud environments, providing users with more effective services and a better user experience .

DevOps practices accelerate time-to-market and returns on development activities. Frequent releases allow users to benefit immediately from the improvements made to the application, without having to wait months for the final release. Very often, in fact, designing an application or finalising a required change can take months, with the risk that business needs have changed in the meantime.

Finally, the Cloud Native design is future-proof : the scalability and portability of modern applications allows optimal utilisation over time, regardless of the evolution of the underlying infrastructure. progettare un applicativo o fi

The advantages of the Cloud Native approach for the development team

Convenient for the entire organisation, Cloud Native applications also add specific benefits for development teams.

For example, the use of APIs makes it possible to reuse functionality already developed without having to rewrite the code from scratch, saving hours of work. Containers ensure the migration of applications to different environments without the need to make changes , thanks to decoupling with the underlying hardware, thus reducing developers’ effort. Automation tools (for container orchestration or CI/CD process management) minimise the repetitive and time-consuming activities of developers, who can then focus on indispensable tasks.

Collaboration between highly specialised multidisciplinary teams, as well as the adoption of DevOps practices, ultimately leads to an increase in software quality. This contributes to raising the company’s perception of the IT function, which is increasingly seen as a business enabler and not just a cost centre.

Cloud Native Applications: where to start?

Implementing a Cloud Native application or modernising the application pool using the Cloud Native approach is not trivial: these operations require in-depth knowledge of the necessary processes and technologies . Otherwise, there is a risk of losing efficiency and money.

Our experience with our customers has led us to realise that the path to Cloud Native is marked by 4 precise stages :

1. Preparatory phase of data collection and initial definition of the Cloud Native strategy.
2. Strategy definition phase, including timelines, methodologies, tools and KPIs to be monitored.
3. Implementation phase of the Cloud Native strategy at both methodological and technological levels.
4. Delivery and implementation phase of the solutions and periodic check-up to validate the implemented strategy and defined KPIs.

Born over 20 years ago, Drupal is one of the most adopted and appreciated Open Source CMS.

Its founder, Dries Buytaert, is also the creator of Acquia, which is to Drupal what RedHat is to Linux: it demonstrates that it is possible to generate tangible value from Open Source software. A noble intention also recognized by Gartner, which has positioned Acquia, and therefore Drupal, in the most important sector of the Magic Quadrant for Digital Experience Platforms , alongside names such as Adobe and Sitecore.

The importance of Drupal

More than 3% of websites in the world use Drupal , which is one of the largest Open Source projects on the market.

Today Drupal is the engine of a series of very different sites and applications: from personal blogs to large corporate and institutional platforms, public administration included.

It is widely believed that Drupal can also be defined as a CMF (content management framework) due to its high flexibility: to all intents and purposes, it is a system that facilitates the use of reusable components or customised software for web content management. In other words said, Drupal is the foundation of a powerful Digital Platform Experience that can be listed in the MarTech technologies landscape .

The basic installation, Drupal Core , already provides all the features of an advanced and modern CMS, such as:

• WYSIWYG editing tools and in-place content editing

Drupal In-Place editing - Credits: Drupal.org

• granular management of users, roles and permissions
• structure content in a flexible and personalised way with content types, taxonomies and menu structures
• SEO tools to manage for example metadata, URLs and sitemap generation
• a powerful integrated and fully customisable search engine

But these are just some of the features provided by the core. The other advantage of Drupal is its vocation for extensibility: Drupal’s modular approach allows not only to develop new features and custom integrations internally but also to access the work of a very large community of independent developers all over the world .

11 advantages of Drupal

After being in the spotlight for the Drupal 9 release , the CMS has continued to evolve with the Drupal 10 release in December 2022, followed by Drupal 11 in 2024.

Despite the misconception that it is more complex than other CMSs, Drupal can be a winning choice for organizations. In particular, it is able to fully satisfy the needs of medium and large companies. Organizations looking for a modern and flexible platform to be accompanied towards a complete digital transformation.

On the other hand, the advantages of Drupal for corporate sites are many and it is worth going over the main ones: we have identified more than ten. Let’s see them below.

ADVANTAGE 1: OPEN SOURCE

The first advantage of Drupal is that it is an Open Source project: its large developer community is made up of over 1 million members , with 118K developers actively contributing to the development of the project on a daily basis and from all over the world.

This means that, in addition to the absence of licensing costs and the absence of vendor lock-in typical of proprietary platforms , everyone can benefit from over 44K free modules to extend Drupal functionality and integrate with third-party platforms.

The diffusion of Drupal in the world is capillary. There are more than 30 communities that revolve around drupal.org and that offer support in more than 40 different languages, not counting the several mailing lists and discussion groups. Drupal is a universe populated by tens of thousands of developers and designers around the world. That’s why those who choose to install Drupal can benefit from the constant support of a network of experts and users.

ADVANTAGE 2: RELIABLE AND WIDESPREAD

In the CMS selection phase, companies look for reliability, historicity and support . Drupal fully fits this description:

• is in the top 3 of the most used CMS in the world
• has been around for over 20 years
• it is continuously updated without ever losing stability
• after new releases, it guarantees support for previous versions for at least 5 years

We must also consider the availability of resources : here we return to the theme of the community, one of Drupal’s strengths. Thanks to the work of the members of the community it is possible to take advantage of free and clearly Open Source contrib modules , unlike other CMS where the additional features are often paid.

In other words, the Drupal ecosystem also works because everyone can benefit from the work and experience of other members , without having to invent the wheel every time. This allows you to find modules that integrate with almost any type of service.

There are many companies that already benefit from this CMS . Among these there is no shortage of large institutions, starting from the NASA site up to the NBC. But there are many other examples, such as the Economist, Warner Music Group, the Australian Government, Tesla, Pfizer, the Oxford University and Lush.

ADVANTAGE 3: SECURITY

Drupal is recognized as one of the most secure CMS in the world, this means that it is infinitely less likely that attackers will be able to penetrate a site made in Drupal compared to one that uses another type of CMS.

What makes Drupal a secure CMS? And how come we can define its quality codebase as not particularly vulnerable? The reasons are several:

1. Its organisational mode l. The large Drupal community works proactively to improve the platform and review the code . The community also includes large companies and organizations that frequently conduct security audits by internal policy.

Every error identified by the members is reported to the Security Team , made up of about forty security experts, who intervene promptly. The same team also takes care of carefully reviewing the modules created by the community to ensure that the codebase is safe and stable, before making them available to everyone. 2. The way it’s made. Drupal is in fact secure “by design” as it reflects all the security criteria established by the Open Web Application Security Project (OWASP) . 3. The security mechanisms. Many precautions have been taken to ensure access security and permission control. To name a few: specific contrib modules to increase password security and strength, or enable two-factor authentication mechanisms; the management of user permissions is designed to minimize errors by limiting the actions of specific figures. For example, it is possible to set different permissions for authors, editors and publishers; there is a complete and advanced notification system for updates and any anomalies.

ADVANTAGE 4: MANAGES EDITORIAL FLOWS AND COMPLEX WORKFLOWS

Drupal proves to be flexible, complete and adaptable in the phase of uploading, editing and publishing content . From version 8, in fact, it offers the management of editorial workflows directly in core, thanks to the Workflow and Content Moderation modules .

The latter is particularly useful for organizations where multiple people, with different roles and permissions, have to collaborate on content: in fact, it allows, for example, to keep content in draft to be reviewed, approved and published by those responsible, without affecting in any way on the already live version. It also tracks who changed what and when through a comprehensive content review system.

The same module then allows you to create customized workflows , for example with intermediate states between the classic “review”, “approve” and “live”, and to create To-do lists for the people responsible for review and approval.

Drupal 10 introduced even more features to enhance the content creation experience. Any examples?

• Layout builder : a new tool to create and edit pages easily thanks to drag-and-drop and without having to frequently call on the development team.

Drupal Layout Builder - Credits: Drupalize.me

• WYSIWYG media library : We’ve further enhanced media management, a feature that allows editors and designers to collaborate on images, videos, and other assets. Like all components of Drupal it is fully configurable.

Drupal Media Library - Credits: Drupal.org

• Claro : is the new base theme for admin interfaces, it is more accessible, responsive, intuitive and visually appealing than the previous Seven theme. Adheres to the new Drupal Design System .

Claro admin theme - Credits: Drupixels.com

ADVANTAGE 5: HAS ADVANCED MULTILINGUAL MANAGEMENT INTEGRATED IN THE CORE

Drupal 8 represents a milestone in the evolution of the platform. Among the many innovations introduced - and then further improved with release 10 - there is the introduction of the multilingual functionality in the core, previously available with an independent contrib module.

Thanks to four built-in modules (Language, Content Translation, Configuration Translation, and Interface Translation), Drupal allows you to:

• Choose the language to use already during the installation
• Choose your language from a very comprehensive list featuring a hundred options
• Take advantage of existing interface translations (and possibly contribute to their completion, if they are not currently 100% translated)
• Granularly configure which site elements can be translated and which not, and f or each element indicate the default language
• Easily switch from one language to other thanks to language switchers and consequently improve the user experience

Language switcher - Credits: Drupal.org

Among the languages ​​supported by Drupal there are also 8 with RTL (right-to-left) writing . This translates into the possibility of using a single company CMS to create content that can be translated and declined in markets that are even radically different from the point of view of linguistic structure, such as China, Japan, Korea, India, the Middle East or North Africa .

ADVANTAGE 6: NATIVELY MANAGES MULTISITE FEATURES

There are many realities that need a central system capable of governing a small galaxy of websites . Using the same instance of a CMS to manage different sites completely separate from each other on the one hand reduces maintenance costs and increases maintenance simplicity over time, and on the other it also allows you to optimize and reuse the assets already available .

Thanks to Drupal’s Multisite feature, all sites can share the same codebase or part of it , and consequently related themes and modules. The platform is in fact a shared library of integrations, features, UI and workflow components that can be used at will across different sites .

At the same time, there is also great scope for the customisation of individual sites . In fact, for each instance it is possible to independently manage domains or URLs, databases, enabled modules, enabled themes, configurations, files and user profiles.

The great advantage of this feature is certainly the time savings : for example, updates and upgrades do not have to be repeated for all websites, it is enough to do it only once and for all. Thanks to Multisite, the introduction of new features is also simplified, since each new feature created for a single instance can be propagated to all the sites belonging to the ecosystem.

ADVANTAGE 7: EXCELLENT PERFORMANCE

A fast website contributes significantly to improving user experience, usability and engagement. Not to mention that speed is also an important ranking factor for the Google algorithm. Drupal is one of the most efficient CMS in ensuring high performance and scalability .

Let’s see some of the features that allow for greater speed of use:

• Cache optimization : from Drupal 8 onwards it is possible to take advantage of both an already widely cache-friendly core and ad hoc contrib modules to improve performance. Among the core modules we mention: Sessionless BigPipe , Quicklink .
• CDN module: it alters the URLs of the files thus allowing the download of the assets like CSS, JavaScript, images, videos and fonts from the CDN instead of the web server. Consequently it allows to reduce the loading time of the page.
• Lazy load : allows you to load images and content as the user scrolls through the page, rather than pre-loading them all at the request stage.
• Image Optimization : Drupal allows you to set image compression ratio and improve page performance. It also allows you to configure specific strategies to optimize the size of images according to different screen sizes or devices, to provide the correct image
• Bandwidth optimization : all CSS and JavaScript files can be aggregated to be loaded in one file, in order to speed up page loading. With the tax form Advanced CSS/JS Aggregation it is then possible to go on to define more advanced aggregation strategies.

ADVANTAGE 8: API-FIRST

One of the most interesting features of Drupal and its design philosophy is related to the API. Drupal’s architecture can be decoupled to operate in a “headless” mode. By doing this it is possible, for example, to have a backend that exposes APIs (in this case Drupal) and a separate front-end that uses them through a framework such as Angular, React or Vuejs (in general there is no limit in using a frontend framework of preference).

Why choose Drupal as your headless CMS? Here are some good reasons:

• Drupal started the API-first initiative several years ago , with the community’s great participation to make Drupal a fully headless-compatible platform.
• Starting from Drupal 8.2 the RESTful module is available in the core, allowing easy interaction with all the standard entities available in Drupal (nodes, users, taxonomies, comments). Accompanied by the REST UI module, you can have very detailed control of what can be accessed through the REST API and how.
• Since Drupal 8.8 JSON:API has been integrated into core. Strictly follows the JSON:API specification and significantly improves the REST experience with Drupal. All it takes is a developer to be familiar with the standard to be able to start working with the API very quickly, without having to spend hours training Drupal.
• The GraphQL contrib module allows you to expose graphql schemas from Drupal.
• Wide availability of documentation, examples, tutorials and support .

ADVANTAGE 9: MOBILE-FIRST

Being mobile-first is a basic requirement for any website today. Over the years the Drupal community has invested heavily in making Drupal a first class mobile platform through a dedicated initiative.

These are some of the features worth mentioning:

• Responsive design for Admins : it is possible to create, add or edit content even from mobile or tablet thanks to the WYSIWYG editor that adapts to the screen size
• Responsive themes : from Drupal 8 onwards, all core themes are natively responsive
• Responsive images : thanks to the Breakpoints and Responsive Images modules, the images on the site can be configured to serve different images and automatically scaled according to the device that requests them.

Modulo Breakpoints - Credits: Drupal.org

• Responsive tables : by assigning different priorities to the columns of a table, it is possible to show only the indispensable ones from mobile, guaranteeing greater readability. From the desktop, of course, all the columns are shown.

ADVANTAGE 10: DRUPAL IS CLOUD NATIVE READY

Over the years, a great deal of work has been done to make Drupal a modern platform ready for Cloud Native development approaches and adhering to the principles of the 12-Factor methodology .

This approach allows you to overcome the limits of monolithic architecture and make Drupal a first class citizen in the Cloud Native ecosystem through the use of modern technologies such as Docker containers and Kubernetes for orchestration . It also allows you to set up Continuous Integration and Continuous Delivery pipelines and automate many of the manual processes such as QA and automated testing.

ADVANTAGE 11: IT IS THE RIGHT CHOICE FOR THOSE INVOLVED IN MARKETING AND DIGITAL COMMUNICATION

Those involved in marketing recognize the value in having an easy-to-use and efficient system in implementing the many processes activated on a day-by-day basis. The most heartfelt need is to create content once and use it over and over again in different ways and on different touchpoints to prolong its life and create contextual user experiences.

So what are the reasons why enterprise marketers choose Drupal ?

1. It’s incredibly scalable . Some of the largest, most visible and busiest sites in the world are built on Drupal (NBA, Johnson & Johnson and The Weather Channel to name a few), as well as enterprise sites with over 1 million pages and over 20,000 requests per second.

2. It allows you to put content marketing at the center. An important part of any marketing strategy today involves creating content. Drupal allows editors to produce articles and posts, embed videos and create landing pages with remarkable ease of use, thanks to in-page editing.

3. It allows for easy integration with marketing automation , email marketing and CRM tools. The major martech platforms (HubSpot, Mailchimp, Salesforce among many) can be easily integrated by means of custom modules.

4. Facilitates the identification of clear editorial workflows designed on the processes of the specific organization.

5. It allows you to create dynamic digital experiences , integrating content, community and e-commerce where necessary.

6. It allows the onboarding of new resources without additional costs because it does not require usage licenses.

7. It is an ideal bridge between marketing and IT: its low-code nature on the front editor ensures marketers can work independently in a digital space. On the other hand, internal IT teams have the freedom to get their hands under the hood and have maximum control over development and security aspects.

8. Benefit from an entire community of passionate developers . What does it mean for a marketer? Have a space that is always up to date with market trends.

9. It is ideal for optimizing the search engine chosen for your website.

10. Security is a top priority for the development community (and has been over 90% guaranteed on over 1 million websites to date).

11. One last fundamental aspect for marketing is that Drupal is omnichannel . To realize an omnichannel strategy it is necessary to centralize the distribution of content on multiple interfaces. Drupal’s API-first architecture and the ability to operate in " headless " mode is the solution to this need, allowing you to create flexible and scalable digital experiences. In this way, we can use the Drupal platform to manage the user experience across multiple channels, such as mobile apps, chatbots, etc.

Conclusion

It is clear that Drupal is no longer the original CMS. With its extreme flexibility, versatility, predisposition to a plethora of integrations, reliability and all the advantages of Open Source, Drupal can be transformed into a real Digital Experience Platform , Low Code / No Code for teams of marketing, capable of satisfying any enterprise requirement, worth of being included in the best MarTech stack of any enterprise.

Used and appreciated by more and more companies all over the world (to name others in addition to those distributed in the previous chapters: Pinterest, Twitter, eBay, Verizon and P&G), it has also been chosen by Italian companies, such as ilgiornale.it, FiscoOggi and Zambon .

The DevOps paradigm proves to be a winning strategy for the success of the digitized company .

Modern organizations require unprecedented levels of flexibility, speed and continuity of service. In order to ensure that business activities run smoothly and that competitive objectives can be achieved, business support applications must therefore meet the requirements of high quality and rapid delivery .

Developing, implementing, distributing and maintaining applications according to DevOps methodology enables you to accelerate the timing of release into production , contributing to the success of strategic initiatives.

What is DevOps?

But what exactly is the DevOps framework and what are the founding principles?

The term designates an approach that facilitates collaboration between cross-functional Developers (Dev) teams and IT Operations (Ops) staff. The key goal is to standardize, speed up, automate and optimize the activities related to the application release phase, improving the quality of the code and the security of the software. In addition to promoting a strong cultural change in terms of collaboration and operations, the model uses process automation tools, as well as precepts borrowed from the Lean Management logic.

Although the prescribed approach is not unique, some shared rules and best practices can be identified including:

• organization into small multidisciplinary groups that collaborate on projects;
• automation and repeatability of test and deployment processes;
• constant verification of the quality of the code;
• the collection of feedback from users to ensure a better alignment between application and desired state.

The 4 pillars of the DevOps pipeline

Hence the four pillars that characterize the DevOps approach:

• Continuous integration e testing

• Continuous delivery e deployment

• Continuous operations

• Continuous assessment

These phases involve both developers and Operations personnel, in order to cover the entire software life cycle : build construction, release into production, maintenance during operation, monitoring of operation, evaluation of defects and enhancements.

Continuous integration e testing

Continuous integration (CI) is a method that allows developers to frequently – even several times a day– integrate the changes made to the source code within a single repository. The changes are subjected to automatic tests carried out in a continuous cycle to immediately identify any eventual operating errors. Before working on any new changes, developers make use of a copy of the current code, stored and validated within the shared repository.

Continuous delivery e deployment

Continuous Delivery (CD) is aimed at accelerating the release of software. It makes it possible to create executable and production-ready builds starting from the common codebase, validated through CI processes. Continuous deployment is the extreme and final step of the CD process, enabling the deployment of every single code change that has passed the tests to the production environment.

FIND OUT MORE: CI/CD best practices

Continuous operations

The concept of Continuous operations refers to the availability of applications for the end user and to service continuity. Any changes made to the software (such as a functional or security patch) or to infrastructure (such as server maintenance) must be transparent to the user, so it does not in any way result in an interruption of service or operations.

Continuous assessment

Continuous assessment refers to the monitoring phase of applications in production (availability, performance, defects, etc.), carried out at a very high frequency. Thanks to the feedback collected from users, developers receive valuable information on eventual corrections or improvements to be made. Subsequently, the interventions are carried out according to priority criteria, based on urgency and on the required investments.

DevOps techniques, platforms and tools

Conducting projects in DevOps mode requires not only a change of pace at the cultural level, but also the support of a series of techniques, platforms and tools that can facilitate the efficient implementation of the methodology.

Cloud-native development architectures, for example, can simplify the adoption of DevOps practices. A design approach based on the use of microservices and containers is particularly well-suited for the organization of work based on the collaboration of cross-functional teams and geared towards accelerating release times.

In fact, applications are conceived as a structured set of independent functional units ( microservices ), which can be modified by small groups of specialized developers, without altering the overall behavior of the software. The ability to intervene on the single application functionality and in a transparent way for users, allows developers to operate simultaneously and in a continuous cycle. Each change to the code is immediately received, tested, released and evaluated by users, who can provide developers with valuable feedback.

Containerization techniques, on the other hand, insert the microservices or applications inside complete runtime systems (the so-called “container" ), which guarantee the operation of the software regardless of the underlying hardware infrastructure. Orchestration solutions such as Kubernetes enable the dynamic administration of container management, deployment and portability across different environments, following the automation processes prescribed by the DevOps model.

Reviewing the technologies supporting DevOps practices, we then find a series of tools created to perform specific tasks related to the different phases of the software design and management pipeline . From planning and collaboration tools such as Kanban Tool and Jira , to configuration management solutions such as Terraform and Packer , without forgetting the monitoring phase supported by tools such as Grafana, Prometheus and Datadog . Finally, tools such as GitLab and GitHub offer concrete and constant help during all phases of the application life cycle.

DevOps strategy: steps and tips for its creation

Having clarified the principles and technologies supporting the DevOps model, how can the framework be correctly implemented within a structured and effective strategy?

Developing a clear and shared roadmap is a key step for optimizing the design, release and monitoring processes according to the DevOps logic. First of all, because it provides developers and Operations staff with a granular view of the processes, ensuring alignment and synergy on the activities in progress. The availability of a detailed work plan makes it possible to more quickly and efficiently identify the priorities and the interdependence relationships between the different processes and work groups. The sequence of interventions can therefore also be rationalized in the medium to long term, facilitating an optimal coordination of activities carried out by developers and Operations personnel.

The recommendations for defining an effective roadmap basically follow the best practices for planning and implementing any complex project.

DevOps benefits and challenges

• Before embarking on a journey towards DevOps, however, companies must thoroughly analyze the benefits and challenges deriving from such a radical choice. Looking at the advantages of adopting the model, we can mention: Time to market acceleration - The collaboration between teams and automation tools dramatically simplify and help speed up application integration, release, deployment and monitoring; Superior Code Quality - Test automation helps detect errors early, preventing them from making their way into production. Even subsequently, the communication between Dev, Ops and users allows a quick identification and resolution of bugs; Alignment with the desired state - The monitoring and collection of feedback makes it possible to create applications that meet the real needs of users; Improved flexibility and support - Typically, applications developed in DevOps mode take advantage of modern Cloud Native techniques, so they are typically easier to scale and maintain; Increased team efficiency - By sharing goals and having visibility into processes, the Dev and Ops teams are able to ensure greater levels of commitment and coordination of the work. Reduction of costs - Team efficiency, release acceleration and minimization of risks ultimately leads to a cost reduction for software management activities. While there are many advantages to the DevOps methodology, a number of challenges must also be taken into consideration when deciding to tackle the change of pace towards the new paradigm. Some of the aspects that deserve greater attention include: Change management - Transforming procedures and work habits requires not only the acquisition of new skills and technologies, but above embracing a cultural change. Company employees are not always prepared; Lack of skills and resources - The transition to DevOps necessitates a corpus of methodological knowledge (on the practices and principles related to the model) and technological expertise (for example on Cloud Native techniques and management/automation tools), which may be difficult to find inside the company and therefore must be built or acquired externally; Choice of tools - The market offers a very wide range of technologies to support the DevOps methodology. Given the diversity and range of the solutions, it can often be difficult to navigate the offer and make the right choice; Relatively high investments - Despite the returns and benefits, the barrier of entry for the DevOps model can be quite scary. Companies, in fact, must act on several fronts (organizational, cultural, technological, operational) and therefore must be willing – at least during the initial phase – to commit themselves economically and in terms of resources.

Does it make sense for your Company to adopt DevOps?

Finally, weighing the different pros and cons, it is necessary to understand if the DevOps model is convenient for your organization, analyzing all the characteristics of the specific case.

For the majority of companies, positive factors clearly outweigh potential challenges, but you must keep in mind that improvisation and a “do-it-yourself” approach are not ideal in such complex projects. As highlighted, the DevOps transformation requires careful consideration and expertise in multiple domains: change management, knowledge of Cloud Native architectures and software management, familiarity with best practices, to name just a few.

To implement a successful DevOps strategy, it is therefore critical to have the support of an experienced and proven partner, who can transfer the necessary technological and methodological know-how to the company. Ultimately, the maximum benefits from DevOps – overcoming the various obstacles – will only be reaped by those with competent guidance on their side.

“Agile Methodologies” promise flexibility, speed of execution and the ability to deal with the multitude of scenarios in which development teams are called upon to operate in the digital transformation process.

A bit generic and perhaps even utopian. In fact, many organisations are ready to testify to the failure of these tools. But like any tool, agility must be applied to the right problem for it to be the solution.

Let’s address the elephant in the room: when people talk about Agile, they often do so improperly, referring to specific frameworks (Scrum being the most famous) or worse, to parts of them. The word “Agile” (with a capital A) actually refers to a mindset, an approach to organising projects, born in the field of software engineering.

The confusion is understandable and largely attributable to the very promoters of these organisational models who, in some cases and especially during the early periods of widespread adoption, spoke about them enthusiastically, as if they were magic wands capable of solving every delivery problem in one fell swoop, simply by adopting certain practices.

Today, agility is no longer optional. The software world moves at breathtaking speed and digitalisation is one of the main competitive differentiators for every product and service.

But is it really always needed? And how can Agile (with a capital A) help our organisation be agile (with a lowercase a), which is what we’re really interested in?

What is meant by Agile methodology?

An Agile methodology, broadly speaking, is a set of codified practices and rules whose purpose is to facilitate the migration of production processes from a waterfall logic to a more iterative and incremental approach.

In the waterfall approach, all design work is done in an initial phase. The focus of implementation is strict adherence to what was designed, and the result is verified at the end through acceptance tests that in turn aim to verify compliance with the specifications.

The authors of the Agile Manifesto, veterans of numerous unsuccessful projects, noticed that the main cause of problems was the complete lack of evolution in this equation.

If, in a long-term project, you don’t remove the constraint of strict adherence to the initial specifications, all the risk accumulates at the end. Unforeseen events, areas not covered by the analysis, incomplete or inadvertently incorrect requirements, changes in the market or corporate strategy, user feedback… everything is ignored until the project goes into production, which is when time and budget have run out (and almost always been exceeded).

In Agile software development, the main goal is to adopt practices and processes that help product teams focus on what truly delivers value, constantly improving their processes and the quality of the outcome.

The Agile Manifesto

So when we talk about Agile methodology, we are actually referring to an approach. A way of working that favours collaboration, adaptation and alignment of the product with shifting business goals, over adherence to pre-established and no-longer-negotiable plans.

Much like the Cloud Native model, the Agile movement began with the drafting of a manifesto that summarises the guiding principles for adopting and customising the framework in twelve key points. Here is an excerpt:

• Our highest priority is to satisfy the customer through early and continuous delivery of valuable software […]

• Welcome changing requirements, even late in development […]

• Business people and developers must work together […]

• Build projects around motivated individuals […]

• Working software is the primary measure of progress […]

• Continuous attention to technical excellence and good design enhances agility […]

Before delving further, let’s take a step back to understand what gave rise to this manifesto of values.

What are the goals of Agile methodology?

The Agile Manifesto, contrary to what one might think, is not a seminal product. It is a synthesis of the principles that drove, from the early 1990s, some developers to elaborate methodologies that would allow them to prevent the majority of software projects from failing within their organisations.

Agile is therefore not the answer to doing more with less, even though it is true that an Agile team, over the medium to long term, increases its efficiency thanks to good practices, efficient communication and trust at every level.

Agile is the answer to reducing the risk of a project, which sees in an empirical approach, based on continuous learning and process improvement, the solution to a potentially disastrous launch.

Generally, Agile organisations adopt the following practices to achieve this result:

• Frequent releases: Software is put into production very frequently, without waiting for perfection. Frequent releases of new features make it possible to track their actual adoption by customers and gather useful feedback to avoid building “cathedrals in the desert”.
• No technical debt: The organisation (not just the development team!) does not consider it acceptable to accumulate technical debt, as it would progressively make it impossible to maintain a rapidly changing codebase, preventing frequent releases. The team has the mandate to constantly improve the state of the code and their practices, without the race for new features taking over.
• Communication: Communication between the team and stakeholders on business topics is possible and indeed encouraged: an Agile team doesn’t just implement features (whose end-to-end behaviour is at best specified by requirements and use cases), but is also called upon to imagine solutions, especially in case of unexpected issues. Developers are therefore not mere executors, but must be results-oriented, able to make proposals and generate solutions.

This is an approach that may appear more expensive than the classic waterfall, but this impression is often false. How many projects seem perfectly on track until, close to the end, problems, delays and rework emerge?

An Agile approach seeks to bring testing and even adoption by real users forward as much as possible, so as to identify and address potential issues from the outset and get everything on the right track while it is still simple, quick and relevant to do so.

But is it always necessary?

What is the typical characteristic of Agile projects?

In terms of risk management, there are no projects that don’t benefit from an empirical approach. Frequently and promptly putting the product before its stakeholders, including end users wherever possible, can only bring out early and clearly the vital information needed to shape the software around real needs, investing in what truly delivers value.

Learning (not only technical, but also business) and adaptation are indeed the two aspects most rewarded by such an approach.

There are cases where a progressive approach, starting from scratch, is not applicable. Imagine wanting to create a new product to replace one already in production. It is unlikely that users would be satisfied with a subset of features, waiting for all the ones they are already accustomed to to be completed over time.

These cases seem like ideal candidates for a waterfall approach: we need to bring a well-established body of features into production. We know everything we need to do and how we need to do it, right?

Maybe.

First of all, in that case, why build a new product? Certainly there are purely technical reasons: key dependencies reaching end of life, legacy systems that are no longer maintainable, expiring licence contracts that force a technology change… but the opportunity remains a good one to look at the system with a critical eye and remain agile and discerning in the approach, to seize opportunities to increase the value of the outcome.

For example, the team can expose features to end users as they are completed, in a test environment. The organisation can then gather feedback, make adaptive decisions and adjust the roadmap to ensure time and budget are respected, anticipating any compromises, but also deciding to drop old features that were never used (or openly hated) in order to invest in improving the most critical ones or introducing new features.

In these scenarios, the architectural choices made in the past also influence the way and extent to which the Agile approach can help the product evolve. A microservices architecture, in fact, works optimally with an empirical and evolutionary way of conceiving change.

But above all, the focus on good practices and the quality of production processes ensures the creation of a maintainable and controlled product, both before and after going into production.

After all, which project doesn’t benefit from investing time and budget on the things that deliver the most value?

READ ALSO:

• How to introduce DevOps culture in your company
• Microservices: what they are and why use them

What are the Agile frameworks?

Alright, we’ve talked about mindset and principles, but in practice how do you reorganise to work in an Agile way?

As already mentioned, there are various methodological interpretations of the Agile mindset; in fact, the manifesto was born from the comparison of different organisational realities, distilling their common principles in retrospect.

Agile Frameworks are skeletons of already-consolidated practices that can facilitate the adoption and maturation of an Agile mindset within an organisation.

Why are they called frameworks? Because they provide guidance and “prescriptions” without imposing the operational details. For example, Scrum requires the use of an ordered, emergent and detailed product backlog; but it doesn’t say whether this backlog should be represented on a board or consist of a pile of sticky notes in a shoebox. Each team can implement its backlog in whatever way is most convenient and suitable.

Different frameworks are more or less suitable depending on the scenario and, although it is possible to get an idea of which is the most appropriate to start with, experimentation remains a very important component. Changing an organisational approach inevitably has effects on the context, and it is common for a framework that was suitable at a given point in time to end up transforming the organisation to the point where it becomes constraining, giving rise to further evolution.

The important thing is not to confuse frameworks (or methodologies) with agility: following the dictates of any Agile Framework to the letter, without developing an Agile value system, can lead to results very different from those hoped for and even worsen a team’s performance.

By way of example, let’s very briefly look at three examples of Agile frameworks, specifically: Scrum, Kanban and eXtreme Programming.

Scrum

Scrum is the most famous among Agile Frameworks, to the point that many now incorrectly use “Agile” and “Scrum” as synonyms.

The Scrum Guide defines it as follows: “Scrum is a process framework that has been used to manage complex product development since the early 1990s. Scrum is not a process or a technique for building products; rather it is a framework within which you can employ various processes and techniques. Scrum makes clear the relative efficacy of your product management and development practices so that you can improve”.

It is a framework oriented towards producing working software from the very first iteration and requires the entire organisation (not just the development team) to embrace its values in order to reap its benefits.

Besides being the most famous, Scrum is also the most misunderstood and poorly implemented, which has earned it the undeserved hatred of many disappointed developers. In the words of its creators, Scrum is easy to understand, but difficult to master.

It is a framework particularly suited for creating new products, where user feedback can make a real difference.

Kanban

This is a methodology inspired by the principles of Agile software development, the theory of constraints and the principles of the Toyota Production System. Developed by David J. Anderson in 2007 after a long gestation at Microsoft, it was formalised in the book “Kanban” published in 2010. Its operation is based on six principles and six practices:

1. visualise the workflow;
2. limit work in progress;
3. measure and manage the workflow;
4. make process rules explicit;
5. establish feedback loops;
6. establish cycles of process evolution and improvement.

Like Scrum, Kanban is also often misunderstood and reduced to one of its physical components: the board. The famous whiteboard populated with colourful sticky notes, diligently arranged in columns to represent the flow, is a very common aid for implementing the first practice (visualising the workflow). However, Kanban goes well beyond that, providing tools for identifying bottlenecks, measuring the effectiveness of process improvements and making accurate delivery forecasts.

Kanban’s focus is on creating the smoothest and most continuous delivery flow possible. It has the property of “starting from what the team is already doing and evolving based on evidence,” which makes it a very lightweight framework to adopt. However, to put it into practice for the first time, the help of a facilitator is often a key element to avoid getting lost in the many options and getting the right start.

Kanban is a scalable framework that can be adopted by a single team within a larger organisation, but is particularly suited for optimising systems composed of multiple interdependent workflows. It is an excellent entry point for organisations that want to develop an Agile mindset one step at a time, modifying their habits gradually and without sudden upheavals. For this reason, however, it requires a great deal of discipline.

Extreme Programming (XP)

Extreme Programming is a software development methodology that emphasises writing quality code and rapid response to changing requirements. It is a very rigorous framework that prescribes twelve practices that a development team must adopt in order to achieve the expected results.

XP has the great merit of having distilled and promoted many of the good development practices that have become common elements for every Agile team, regardless of the method they use. For example, it promoted:

• continuous integration;
• peer programming;
• iterative development and planning;
• the use of User Stories;
• the systematisation of testing and refactoring;
• the prohibition on developers writing code that is not strictly necessary;
• the emphasis on code clarity and simplicity; the preference for non-hierarchical management structures;
• finally, the importance given to direct and frequent communication between developers and the client, and among the developers themselves.

Extreme Programming, often criticised for being a model too centred on software engineering and for delivering more value to developers than to the business, is a development model that, in exchange for strict discipline and a process very focused on development practices, delivers very high technical quality.

READ ALSO: User Story Mapping: how to design a web product together with your team

Agile Methodology: a practical example

To get a more precise idea of Agile Methodology, a practical example can help us grasp its distinctive features. Let’s try comparing the way two different methodologies operate at various stages of the project lifecycle. For this example, we’ll compare a waterfall approach, generally contrasted with Agile, using the Scrum framework as an example.

We want to make clear that these are generalisations, deliberately polarised towards extreme cases. Reality is always more nuanced and depends very much on the degree of maturity in applying both approaches.

On the left side of the table we find the phases shared by the two approaches, while in the columns we find the respective way each phase is managed in the two different frameworks.

That’s great, but does it really work?

A concrete example of agility in action is represented by the Telethon success story that appears among our case studies.

The Telethon Foundation engaged SparkFabrik to improve the percentage of donations channelled through the website, which at the time of engagement stood at around 3% of total donations during the winter marathon.

Thanks to the Agile approach adopted by the entire organisation, the development of the donation website was completed a week ahead of schedule and without the need for an acceptance testing phase, since the client was able to validate the product increments at the end of each sprint.

Being able to review the application’s components every week with users and client-side managers made it possible to promptly revisit assumptions, adjust course and make decisions that were easy to implement, accelerating in the right direction. The increase in donations received through the new website was 37%!

Can you spot the elements discussed so far within this story?

The rapid release of the product; constant communication between the team and the client; timely and cyclical feedback and, of course, the quality and client satisfaction given the results achieved: all the elements promoted by the Agile Manifesto.

DISCOVER OTHER FRAMEWORKS:

• DevOps
• DevSecOps
• FinOps

Watch out for the pitfalls: how to avoid getting hurt

As we wrote, agility is first and foremost a mindset and requires a change of direction. Thinking you can adopt Scrum and then asking your PM to make sure things are delivered “exactly as planned at the end of each sprint” is no different from requiring that “the work is completed as per specifications, in time for the milestone review”.

This is simply a “relabelling” exercise and will bring nothing but frustration and poor results, as it does nothing more than accelerate the execution of the “plan”, often at the expense of product quality (the exact opposite of the goal!).

There is a term we use at SparkFabrik to describe this approach: Agile à la carte. It is a provocative way of naming the tendency, observed in several of our experiences, to adopt only the easy and immediately understandable aspects of methodologies and frameworks. These are usually the least substantial and most superficial elements — the so-called low-hanging fruit — the parts that are easy to stick onto existing processes, under the illusion that doing so changes their substance.

There is nothing particularly deplorable about this. Introducing new management principles is neither an easy nor cost-free process, and adopting a framework is not always the best way to “agilise” your business.

The adoption of Lean practices, already well-established in many areas including management, or the emergence of relatively recent and less talked-about approaches like Disciplined Agile (which defines itself as a toolkit and differentiates itself from frameworks by not wanting to be prescriptive) or SAFe (a set of practices and models for adopting Agile at enterprise scale that incorporates the concept of value stream at its core, borrowed from the Lean world), are all signs that the ways of practising agility are as numerous as the enterprises that want to adopt it.

Perhaps it is time to stop talking about Scrum or Kanban methodology, about tools, frameworks and pre-packaged solutions, and return to analysing the fundamental principles. There are, for example, interesting hybridisations between more traditional approaches to project management and Agile practices, complete with certification programmes for “Agilist” PMIs, which can provide an optimal solution for introducing a change in thinking, taking one step at a time in the right direction.

The journey from a “traditional” organisation to a fully Agile one is itself an empirical process, one that cannot be systematised (and beware of anyone who promises otherwise). And in any case, there is no moment when an organisation becomes agile. Agility, like all qualities, is not precisely measurable and sometimes it is only by observing other realities that we can tell whether and how we can improve.

It is wise to expect experimentation and the occasional failure, try different approaches and, above all, seek dialogue. In this respect, participation in communities and events (be they industry conferences such as Agile Business Day or so-called unconferences like Play14) plays a fundamental role in creating opportunities for exchange, growth and in identifying patterns of success and failure common to other organisations.

In essence, the paths and methodologies are numerous and constantly evolving; their names are often registered trademarks and serve in some way to make agility a business in its own right.

Is Agile methodology still relevant today?

More than two decades after the birth of the Agile Manifesto in 2001, the question of whether Agile is still relevant in software development is more than legitimate. The answer remains a resounding yes. The software world is in constant evolution, with new technologies and emerging requirements that demand flexibility and adaptability — intrinsic characteristics of the Agile approach. For this very reason, changes such as the introduction of new programming languages, cloud computing and other technological innovations do not risk making the Agile approach outdated; on the contrary, they provide the opportunity to apply the methodology’s principles, demonstrating their extreme necessity. That is why Agile continues to be a valuable methodology. Its fundamental principles — such as collaboration between teams and clients, iterative and incremental delivery, and the ability to react to change — will not only continue to be useful and relevant, but will be even more so in disruptive contexts and ever-new scenarios.

New trends

Agile is therefore, in every respect, a future-proof mindset. Will it remain unchanged in the years to come? It would be naïve to think so, and the already-mentioned hybridisations between different frameworks testify to the contrary. If anything, it will be the principles (those, yes) that will remain largely unchanged for a long time, while the frameworks will evolve significantly. We can cite, for example, the trend of the Obeya Management System, an approach that transcends and encompasses any Lean Agile methodology. Also derived from the Toyota Production System, Obeya is a Visual Management system that aligns strategy and execution through a collaborative architecture, without the need to certify scores of Scrum Masters or Agile Coaches. This system promotes collaboration, transparency, communication and accountability, offering a powerful team-centric management tool.

Another trend is linked to the growing spread of Agile principles, which have now broken beyond the boundaries of software development to flow into a wide variety of professional roles. Today, Agile skills are required in a great many business areas, constituting a fundamental requirement even for roles such as project managers, sales staff, business analysts and human resources specialists, to name but a few. This underscores the importance of a widespread Agile mindset throughout the organisation, at every level.

How can Agile methodology be useful to you?

In conclusion, we can say that Agile methodologies can be a fundamental ingredient in guiding companies towards a full digital transformation. A new way of working, ideal for putting into practice an efficient management of projects with a strong Digital and Cloud focus.

Agility is a quality that, once acquired, is reflected throughout the entire lifecycle of a project, bringing benefits in terms of product quality, customer satisfaction, monitoring and control capabilities, increased predictability of outcomes and risk reduction, greater flexibility and the promotion of continuous improvements and incremental evolutions.

Last but not least, successfully implementing an Agile methodology has a positive impact on team morale and significantly improves internal dynamics — fundamental aspects for maintaining a stimulating, creative and results-oriented work environment.

What matters most is developing the right posture towards the way the organisation approaches projects. Rather than trying to anticipate every possibility and hoping things go as planned from start to finish, accept that the world is complex and unpredictable, work iteratively with transparency and eyes wide open, and adapt your plans to maximise value, deploying resources to achieve the best possible outcome.

Digital disruption is revolutionizing every business, regardless of size or industry: new organizational and competitive scenarios are emerging on the horizon, with business models that are radically different from the past. more

No organization is immune to change, which involves two main aspects. On one hand, the ability to apply digital technologies to any process with a view to optimization and efficiency; on the other, a cultural openness to innovation and a willingness to experiment, with the aim of rapidly developing new market approaches by riding the wave of digitalization.

The strategic value of digital transformation (and how to measure it)

In 2020, Deloitte described Digital Transformation as the combined result of technology implementations and methodological competencies: for example, analytics software is only effective when built on solid data management processes; smart working solutions work downstream of IT ecosystems built by balancing security and flexibility. Thanks to the know-how and process organization methods underlying new technologies, disruption enables the desired benefits (from product innovation to customer satisfaction), driving a decisive increase in financial performance.

The survey reports that in 2020, 45% of companies with net revenue growth above the industry average demonstrated a high level of digital maturity, 31% medium, and 15% low.

Today, several years later, Deloitte itself questions the exclusive use of financial KPIs to evaluate the impact of technology investments. This approach risks preventing digital leaders from fully capturing the value of technology investments, potentially leading to reduced budgets for technology spending.

So how can we correctly measure the true value of digital transformation?

Choosing the right KPIs to evaluate Digital Transformation

In 2023, as part of the research “Mapping Digital Transformation Value”, Deloitte’s Center for Integrated Research surveyed 1,600 business and technology leaders to understand which KPIs they used to measure the value of technology investments. The most commonly used KPIs turned out to be traditional financial metrics, process performance metrics, and traditional customer metrics. While these measures are essential, focusing solely on them can cause organizations to lose sight of the broader impacts of technology value. Why?

Many digital technologies influence the entire organization as a whole, its people, and even the planet, for example by improving resource efficiency and reducing environmental impact. What’s more, an organization’s technology investments can also have reputational, social, or emotional impacts that may not surface in common KPIs.

Therefore, to fully assess the value of technology investments (and protect them), organizations should consider both the most common impact measures and other forms of benefit that technology delivers. This broader measurement can provide a complete picture of the value generated, help justify continued funding, and offer a solid and consistent basis for deciding when not to invest.

Easier said than done. In fact, 73% of respondents believe that the inability to define exact impacts or metrics is a barrier to digital transformation, followed by the inability to collect data and organizational silos.

However, there are some encouraging findings, such as the fact that, globally, 46% of organizations reported using purpose-driven KPIs to evaluate technology impact. These measures include sustainability, social return on investment, and workforce diversity, equity, and inclusion.

In other words, despite the difficulties in measuring certain types of metrics, organizations that adopt a holistic evaluation framework gain a clearer view of the impact of Digital Transformation within their organization, and are 20% more likely to see significant business value from their digital transformations.

The role of IT today

Beyond the need to accurately assess the value of digital transformation, the role of Information Technology (IT) has been undergoing an epochal transformation for several years. IT, once dismissed as a cost center, is now becoming a profit driver. The Chief Information Officer (CIO) is therefore gaining an increasingly strategic position at the company’s decision-making tables, especially in companies that could benefit most from technological and digital evolution. A study highlights that the best-performing companies are more likely to have their digital transformation led by the CEO (33%), while CIOs and CTOs (36%) are the ones driving average-performing companies toward the digitalization process.

This evolution has been further accelerated in recent years, demonstrating how information systems and digital technologies are indispensable tools for resilience. The most technologically prepared companies were able to respond with greater speed and effectiveness to unforeseen challenges, rapidly enabling solutions such as smart working. Investing in digitalization continues to prove essential for ensuring operational continuity in an increasingly unpredictable context.

Evolution of Information Technology in Digital Transformation

Having framed the growing value of digital transformation and the evolution of metrics to measure it, and having identified the CIO as an increasingly strategic role and responsibility for companies, it is important to get down to the practical dimension. What does digital transformation consist of today? Which areas of a company does it involve? What are the pillars that can bring an efficient digital approach to life?

We can say that, on a practical level, IT transformation is reflected on multiple levels. First and foremost, the main criterion guiding technology choices is represented by business needs: the focus is no longer on the solution per se. Today, companies are looking for IT solutions that not only integrate multi-source data but also offer engagement, collaboration, and analytics capabilities. Traditional software, designed to run on on-premise infrastructure, is giving way to Cloud Native applications, developed on containers and for distributed environments.

Another paradigm shift is the transition from descriptive analytics to predictive and prescriptive analytics, made possible by the availability of real-time data from multiple sources, as well as artificial intelligence systems.

Finally, the Internet of Everything broadens the concept of networking, with the proliferation of connected devices and available information.

Bringing the concept of digital transformation to an even more concrete level, three characterizing and enabling factors can be identified. They are Cloud Transformation, Cloud Native applications, DevOps & Agile: the three pillars of Digital Transformation.

Below, we will analyze each of these three areas in detail.

First pillar of Digital Transformation: Cloud Transformation

According to Gartner, today, cloud tends to be viewed as a technology platform, but this perspective will change significantly by 2027. Cloud computing will not only be a technological approach for application distribution but will also serve as the primary engine of business innovation.

Cloud is indeed establishing itself as the most advantageous architectural model today, thanks to a range of benefits.

Getting into the technical details, there are three types of Cloud architectures:

• Private: assets are consumed as a service within the company’s data center, which can reside in owned facilities or be leased from Cloud providers;
• Public: resources are delivered from the provider’s infrastructure, accessible via the Internet and shared among multiple users;
• Hybrid: the type destined to prevail, which involves a mix of public and private Clouds.

FURTHER READING: What is Hybrid Cloud? When to choose it, examples, advantages Pros and cons of multi-cloud: is it right for your company?

The advantages

Despite the differences, common benefits on the IT and business front can be identified that a company can gain by opting for a Cloud Transformation path.

First and foremost, among the most appreciated characteristics, we must mention the guarantee of operational continuity and, more generally, of resilience. A distributed environment across multiple data centers, geographically distant and accessible via the network, ensures users the availability of services always and everywhere, even in the face of disasters.

Cloud providers, thanks to economies of scale, can equip themselves with high-performance and cutting-edge technologies, including in terms of security. No company - whose core business is not IT systems - would be capable of equal investments to protect its own infrastructure.

At the same time, the ability to rapidly purchase technology assets as a service, within pay-as-you-go contracts, allows building IT environments in a flexible, scalable, and more cost-effective way, especially when managed according to the FinOps approach.

In short, the Cloud is the tool that enables aligning information systems with business needs, balancing robustness and agility.

ALSO READ: FinOps: why switch to Cloud financial management Digital Transformation and resilience: what the Coronavirus taught us

One more reason…

The Cloud also becomes the means of support for companies’ internationalization policies, as it allows for the rapid setup of infrastructure and technology resources close to the target market.

For example, SparkFabrik’s China Unit service enables Italian companies to strengthen their presence in China through the partnership with Alibaba Cloud and a range of consulting activities. The goal is to provide companies with a secure and compliant infrastructure that enables them to offer high-quality, fast, and efficient services to local customers.

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The importance of Cloud Management in Digital Transformation

The advent of Cloud Computing triggers a profound business transformation. Organizations increasingly feel the need to master the art of managing and controlling cloud environments. Good cloud management is essential to support the rapid evolution of processes and products, facilitating increasing outsourcing to the cloud and fostering digital transformation.

We therefore speak of Cloud Management to refer to the set of practices, technologies, and tools used to manage and control the environment of a Cloud infrastructure. This often occurs in multi-cloud contexts, given that the trend is to use services from multiple providers such as AWS, Microsoft Azure, and Google Cloud Platform simultaneously.

It therefore becomes crucial to integrate and coordinate these different Cloud infrastructures as a single entity, centralizing activities such as resource provisioning, performance monitoring, security management, capacity planning, and cost management.

FURTHER READING: Cloud Management: fully harnessing the potential of the cloud Multi-cloud orchestration: tips for doing it the right way

All of this may seem complex for a company aiming for digital transformation but still uncertain about which path to take. However, the benefits of the cloud and its proper management are accessible thanks to dedicated services and technology partners like SparkFabrik. For example, Cloud Migration services enable strategic planning and execution of Cloud migrations, maximizing the potential offered by providers such as Amazon AWS, Google Cloud Platform, Microsoft Azure, and Alibaba Cloud. Alternatively, Managed Cloud Services give companies all the power of the Cloud without the management complexity, allowing them to free up valuable resources to redirect toward value-added activities, while simultaneously reducing costs and issues arising from managing complex infrastructures.

Second pillar of Digital Transformation: Cloud Native applications

In new Cloud ecosystems, traditional applications, designed with a monolithic structure to run in client-server environments, may not function correctly or with adequate performance levels. This gives rise to the need for an alternative approach to software development, which is now in a consolidation phase: the Cloud Native paradigm. This paradigm enables organizations to fully leverage the advantages of flexibility and speed of time-to-market promised by the Cloud.

ALSO READ: Microservices and cloud-native applications: advantages over a monolithic application

Third pillar of Digital Transformation: DevOps & Agile

The ability of software to respond precisely to business demands is the key to the success of the digital enterprise. Cloud Computing, microservices, and containers converge toward this objective and encourage the adoption of Agile and DevOps development techniques, particularly suited both for developing Cloud Native web applications and for modernizing legacy applications with a Cloud Native approach.

Agile methodologies prescribe breaking down the project into iterative, sequential, short-duration cycles, each aimed at achieving a small improvement to the product until the final objective is reached. Every change made is released and verified directly by users, so as to collect feedback and intervene promptly in case of errors.

The DevOps methodology emphasizes collaboration between Developers and Operations throughout the entire application lifecycle (development, testing, and delivery), ensuring greater speed compared to traditional development processes. The use of microservices lends itself very well to DevOps practices: each microservice is an independent functionality and therefore allows small teams to collaborate toward achieving a common goal. This means that it is even easier to proceed with incremental and continuously tested releases.

ALSO READ: Agile and DevOps: what they are (NOT) and how they interact What is Agile methodology: examples and advantages

The role of Artificial Intelligence and Open Source in Digital Transformation

In recent years, Artificial Intelligence (AI) has gained great relevance, both in business contexts and beyond. Less discussed, but equally rich in potential, is Open Source, understood as software with open and modifiable source code. These two areas are emerging as fundamental elements for the success of modern companies. But what role can they play in the digital transformation of organizations?

Artificial Intelligence should not be considered merely an enabling technology, but a strategy capable of transforming operational models. For its part, Open Source provides fertile ground for flexibility and continuous innovation, reducing costs for companies and accelerating time-to-market.

In particular, the adoption of Open Source solutions democratizes innovation, enabling companies to rapidly integrate AI into their processes through continuously evolving tools and frameworks. These tools support the development of advanced applications, useful across every business area - from marketing to IT - improving operational efficiency and customer experience. Furthermore, they address critical challenges such as data management and ethical issues, creating a collaborative environment and allowing companies to share resources and knowledge to tackle complex problems more effectively.

Artificial Intelligence, made accessible by Open Source tools, cuts across organizations, automating repetitive tasks, optimizing workflows, and freeing up resources for strategic activities. It analyzes enormous volumes of data, offering insights that guide informed business decisions and help predict market trends. It improves customer interaction through personalized and timely support, anticipating their needs through predictive analytics.

AI’s ability to stimulate innovation enables companies to explore new business models and improve products and services, reducing risks and accelerating time-to-market. In conclusion, Artificial Intelligence, supported by Open Source solutions, is a powerful catalyst for Digital Transformation. Companies that can leverage these resources will be better positioned to face future challenges and capitalize on the opportunities offered by digitalization, strengthening their competitiveness and innovation.

Starting a Digital Transformation project in your company

The digital component is increasingly pervasive within organizations, permeating every function and business process. The ability to correctly innovate the underlying technology stack becomes a critical success factor and even a matter of survival.

Embarking on the digital journey means calibrating the right technology mix in relation to the company’s specific characteristics, planning innovation paths rationally and being careful not to disrupt delicate balances.

Digitalization therefore requires a business-centric approach: it is the needs of the company and its customers that determine the appropriate technology choices. This shift in perspective represents a key step toward innovation and requires specific competencies, which can be found in a qualified partner.

FURTHER READING: Application modernization: what it is and what are the advantages

By your side for technological innovation

SparkFabrik meets the current needs of businesses, complementing its technology offering with a methodological approach as well.

For example, we organize workshops dedicated to User Story Mapping, a technique that analyzes the interactions between the user and the web product through a shared process within a working group. Essentially, a typical user experience is imagined, mapped, and graphically represented, highlighting the user’s main needs and desires.

Among the consulting services aimed at Digital Transformation, SparkFabrik also offers the Cloud Native Assessment, which evaluates the status quo in terms of technology, processes, and culture, so as to define a personalized application modernization path. Individual cases are then examined, opting for the best solution and choosing from different approaches: from Lift and Shift (the simple transposition of traditional applications to the Cloud) to the complete modernization of applications with the introduction of containers and the adoption of new development paradigms such as microservices or Serverless.

In short, digital disruption requires digital culture (and awareness of its value), the right technologies, and above all, specific competencies, which often only a partner with proven experience can provide.