For your team
Migrate to Skyone
Featured products
Ecosystem and collaboration
DevOps & SRE: Understanding the models that are transforming IT operations
The promise is attractive: more agile teams, faster deliveries, and highly reliable systems. But as the complexity of IT operations increases, so does the confusion about the paths to get there. DevOps or SRE? Culture or engineering? Agility or reliability?
This question isn't just technical: it's strategic. According to a Gartner study , by 2027, 80% of organizations will have incorporated DevOps platforms into their development tools, compared to 25% in 2023. This
leap shows the urgency, but also reveals a gap: if DevOps is so prevalent, why do many teams still face failures, rework, and operational bottlenecks? This is where SRE comes in, and the need to truly understand what differentiates these two models.
In this article, we go beyond the definition. We will explore how DevOps and SRE emerged, where they meet, where they diverge, and why this choice (or combination) can be decisive in transforming IT into a competitive advantage .
Let's go?
Before becoming a practice, DevOps is a concept that represents a paradigm shift in how technology areas work. The acronym comes from the combination of " Development " (Dev) and " Operations " (Ops), two disciplines historically separated within IT.
Traditionally, the team that developed the software was not the same team that deployed it or maintained its stability. This separation generated conflicts, bottlenecks, and significant inefficiency. The DevOps model was born precisely to eliminate these barriers, creating a continuous flow between development, testing, delivery, and operation.
More than a methodology or set of tools, DevOps is an organizational culture focused on agility with responsibility . Its focus is on accelerating the delivery of value to the customer, without sacrificing the reliability and stability of systems.
But how does this translate into practice? Let's look at the fundamentals!
Principles and objectives
DevOps is underpinned by several essential principles, all sharing a common goal: increasing delivery speed with security and predictability . The practice encourages shorter development cycles, with deployments and automated testing, allowing companies to respond quickly to market changes and demands.
Key pillars include continuous integration ( CI ) and continuous delivery ( CD ), which automate and integrate all stages of software . Another central principle is active collaboration between departments , reducing friction and promoting a shared vision of responsibility for the product.
DevOps also challenges a traditional IT idea : the separation between "who builds" and "who maintains." By aligning teams with common goals, it creates a virtuous cycle where agility, quality, and reliability go hand in hand.
Common practices and tools
In practice, DevOps materializes in routines and tools that support automation, integration, and continuous monitoring pipeline testing , infrastructure-as-code (IaC) provisioning, proactive monitoring, and deployments , often daily or even continuous.
Tools like Jenkins pipeline orchestration ), Docker (for application containerization), Kubernetes (for managing clusters at scale), GitLab CI/CD , and Terraform (for infrastructure as code) are frequently adopted to support this ecosystem .
But one point deserves emphasis: DevOps is not about tools, but about real integration between teams, processes, and deliverables. A robust stack is useless if the team culture remains fragmented. It is the combination of mindset, processes, and technology that enables true DevOps.
Benefits and challenges in the operation
Adopting DevOps brings real and tangible gains : shorter delivery cycles, higher quality products, fewer production errors, and teams more aligned around common goals. The infamous " midnight deployments apps or e-commerce ), with less stress and more predictability .
On the other hand, the transition to DevOps is not trivial. It requires profound cultural changes, a review of legacy processes , and often, a redefinition of roles within IT. There is also the risk of adopting tools before aligning strategies—which can lead to the automation of inefficiencies.
Therefore, DevOps is a powerful starting point, but not necessarily the end point . In environments where reliability becomes as critical as speed, the need arises to complement this model. That's where Site Reliability Engineering , or simply SRE, comes in. And that's what we'll discuss next.
If the DevOps model proposes agility with integration, SRE emerges as the necessary answer to deal with reliability at scale . Created within Google in the early 2000s, SRE ( Site Reliability Engineering ) is, in practice, the application of software to the universe of infrastructure and operations.
But what does this mean in real life? That the reliability of systems cannot depend on manual processes or emergency actions . Thus, SRE transforms the operation into a structured, automated, and data-driven process, where failures are predicted, managed, and learned from, not just corrected.
While DevOps seeks fluidity between areas, SRE focuses on ensuring that systems remain available, performant, and resilient , even in the face of constant changes. These are models that interact, but operate with distinct logics and objectives.
Check out more details below.
Principles and objectives
The starting point of SRE is straightforward and realistic: failures will happen. The difference lies in how we prepare for them. The model's proposal is to transform these inevitabilities into learning and growth opportunities, with less urgency, more structure, and, most importantly, less impact on the business.
To achieve this, SRE is anchored in three fundamental pillars :
- SLOs ( Service Level Objectives ) : internal reliability targets, such as 99.9% monthly availability, that define the acceptable level of service;
- SLIs ( Service Level Indicators ) : technical metrics that measure whether these objectives are being met, such as latency, throughput , or error rate;
- SLAs ( Service Level Agreements ) : formal agreements with clients or users that translate SLOs into contractual expectations of delivery.
But perhaps the most provocative concept of SRE is that of the error budget . Instead of pursuing perfection (which, in complex systems, is illusory), the model proposes an acceptable limit on failures . This "error budget" allows for calculated risks, confident release of new versions, and maintaining a healthy balance between innovation and stability .
And the thinking doesn't stop there. To ensure that the operation is truly prepared for the unexpected, SRE also incorporates a bold practice: chaos engineering . This approach involves intentionally inducing failures in a controlled manner to observe how the system behaves . This is because, by simulating extreme scenarios, it is possible to strengthen resilience and prevent real failures from becoming crises.
In the end, we can say that SRE does not seek to eliminate risk, but to make it manageable , with data, automation, and the mindset of continuously learning from the unpredictable.
Common practices and tools
In their daily work, an SRE engineer acts as a hybrid between a developer and an operator . Therefore, their mission is to automate as much as possible, reduce manual intervention, and maintain predictable operations, even in highly complex scenarios.
Common practices include:
- Automation of repetitive tasks, such as deployments , rollbacks , and escalation;
- Implementation of resilience tests, simulating controlled failures to strengthen the robustness of the system;
- Deep observability, with real-time metrics, intelligent alerts, and end-to-end traceability;
Post -incident analysis , treating failures as valuable sources of learning.
In day-to-day operations, tools like Prometheus (metrics collection), Grafana (visual dashboards), Kubernetes ( container ), Terraform (IaC), and Sentry (application monitoring) are part of the essential toolkit of a modern SRE team.
However, more important than the stack is the engineering mindset applied to reliability . The true differentiator of SRE lies in how it anticipates risks, automates responses, and builds a resilient operation, always based on data and continuous learning.
If you want to delve deeper into this topic from a Brazilian perspective , it's worth checking out the book "SRE Journey in Brazil ," written by Alessandro Silva, Ana Genari, and Antonio Muniz, professionals who experience the model daily in large operations in the country. Without a doubt, it will be a rich read, connecting theory and practice with the reality of our market.
Benefits and challenges in the operation
Adopting the SRE model transforms a company's relationship with its own operations. Systems become more reliable , incidents less frequent , and recovery processes faster and more organized . As a result, team and customer confidence increase, and the ability to scale smoothly becomes a reality.
However, the challenges are proportional to the gains . Implementing SRE requires technical maturity, governance over metrics, and a culture of continuous learning. It also requires professionals with a multidisciplinary profile, who master both code and infrastructure; both strategy and operations.
Therefore, SRE does not replace DevOps, but rather complements it . While one focuses on the fluidity of delivery, the other ensures the solidity of support. And it is in this complementarity that many companies find the ideal balance between agility and reliability.
But ultimately, how do these two models differ in practice? That's what we'll see next.
As we have seen, the DevOps and SRE models share common goals (such as delivering software with greater agility and reliability), but they follow different paths to achieve them . Therefore, although they often appear as synonyms in market conversations, they start from distinct premises and operate with complementary focuses.
While DevOps was born as a cultural movement that brings development and operations closer together, SRE emerged as a technical and structured model, focused on reliability, metrics, and incident automation. Understanding these differences is essential to applying each approach strategically , according to the organization's context.
Below, we have organized a practical comparison between the two models, highlighting what changes, in theory and in practice.
| Aspect | DevOps | SRE |
|---|---|---|
| Origin | Culture created by market practices | Model created by Google |
| Objective | Accelerate deliveries with quality | To increase the reliability, performance, and observability of systems |
| Main focus | Agility and integration between development and operations | Reliability and resilience of systems |
| Responsibilities and profile of the teams | Developers and Operations teams collaborate continuously; responsibility is shared | Engineers with a hybrid profile assume and measure reliability |
| Culture of error | Correct mistakes quickly and learn from them | Tolerate failures within defined limits and prevent recurrences |
| Scope of work | The entire development and delivery cycle | Support, monitoring and incident response |
| Integration with the business | Align deliveries with product goals | It guarantees stability for growth and innovation |
| Key metrics | Delivery time – Production failures | – SLIs – SLOs – SLAs – Error budgets |
| Common tools | – Jenkins – GitLab – Docker – Terraform | – Prometheus – Grafana – Kubernetes – Sentry |
This chart shows that DevOps and SRE are not opposites, but models that meet at different points in the modern IT journey. Together, they offer a balanced path to innovate safely and scale without losing control.
Convergence is the word that defines the current state of technology. What were once distinct approaches are now intertwined with artificial intelligence (AI), automation, real-time data, and operations that need to be resilient, predictive, and evolutionary.
The numbers help to illustrate this scenario. According to a study published by Markets and Markets , the global DevOps market is expected to grow from US$10.4 billion in 2023 to US$25.5 billion by 2028 , with a compound annual growth rate (CAGR) of 19.7%. Furthermore, according to the SRE Report 2025, published by Catchpoint , 53% of SRE teams consider performance issues as critical as complete failures, and 30% are prioritizing the use of AI to increase efficiency and operational predictability .
These data reveal a clear trend : DevOps and SRE are being powered by AI , which adds predictive intelligence to operations and accelerates responsiveness. This convergence is not theoretical: it is happening now, behind the scenes at companies that are redefining how to operate IT with intelligence, security, and speed .
What does this change in practice?
- Observability evolves with models that predict failures before they happen;
- Pipelines become smarter by identifying error patterns and automatically suggesting fixes ;
- teams use AI to simulate scenarios and automate responses , reducing reaction time and keeping operations stable.
We can say that the big question right now is how to design operations that learn, adapt, and continue to evolve. This is the convergence that is already shaping the future of IT, as well as the foundation for intelligent, resilient, and scalable operational architectures .
In practice, talking about DevOps and SRE means discussing what sustains the business when everything needs to function continuously. And for that, it's not enough to have good tools or follow market trends. It's necessary to deeply understand the operational challenges, the reality of legacy systems, the pace of innovation, and, above all, what's at stake when something fails.
At Skyone , we support companies that experience this scenario every day. Organizations that need to grow without stalling, innovate without compromising stability, and operate with clarity , even in complex environments.
Our work goes far beyond technical consulting . We work at the intersection of strategy, culture, and technology. We help implement DevOps pipelines We apply the SRE model pragmatically, building real layers of reliability in critical systems such as ERPs, industry-specific applications, and complex cloud integrations.
We know that each company has its starting point . Some are taking their first steps in automation; others already run distributed operations with high data volumes and uptime requirements. That's why our support is always contextualized : no ready-made formulas; everything is based on the reality and ambitions of your business.
If you're at this crossroads, rethinking processes, seeking more control, or trying to scale safely, we're ready to talk! Speak with a Skyone specialist . And we'll understand your situation, explore paths, and together design an operation that works today and continues to work tomorrow.
DevOps or SRE? This question, which seems technical, actually hides a strategic decision : how to structure an IT operation capable of keeping pace with the speed of the business without compromising reliability.
Throughout this article, we explore how these two models emerged, how they differ, and, most importantly, how they can complement each other. The most important thing is not to choose a side, but to understand what your operation needs now, and what it will need in the future .
If you've made it this far, you're already doing what many still postpone: seeking clarity before seeking solutions . And this clarity is the first step in transforming your IT operation into a competitive advantage.
However, the journey doesn't end here! On our Skyone blog Explore other available content and evolve with those who understand real-world operations.
"DevOps" and "SRE" are terms that are increasingly heard, but not always well explained. And when it comes to structuring an efficient and reliable IT operation, understanding what's behind these models can make all the difference.
Below, we've gathered direct and essential answers for those who want to start understanding, comparing, or applying these concepts in their daily work.
What are DevOps and SRE?
software delivery more agile, integrated, and continuous. It promotes collaboration between teams and process automation to shorten the time between writing code and putting it into production.
SRE ( Site Reliability Engineering software engineering to system operation, focusing on reliability, performance, and resilience. Its goal is to ensure that systems function stably, even in highly complex scenarios.
How do I know which model to adopt?
With the increasing integration of artificial intelligence (AI), data, and operations, the choice between DevOps and SRE is no longer an isolated decision. Today, the most relevant aspect is understanding how these models complement each other to create intelligent, resilient, and scalable operations.
If the goal is to accelerate deliveries and improve collaboration between areas, DevOps is the ideal foundation. If the priority is to ensure stability in critical environments, SRE comes in with a focus on automation, reliability, and incident response.
And with AI driving both models, the combination of the two becomes even more powerful: DevOps structures the continuous delivery flow, while SRE applies operational intelligence to maintain stability, even under pressure.
Start transforming your company
Test the platform or schedule a conversation with our experts to understand how Skyone can accelerate your digital strategy.