From Enablement to Reliability: How Platform Engineering Aligns with SRE Goals – A conversation with Sean P Alvarez and Ajay Chankramath

On distinguishing SRE from Platform Engineering, building developer-first platforms, and the practical lessons behind treating platforms as products.

Platform Engineering is often confused with Site Reliability Engineering (SRE) or seen as the latest rebranding of DevOps. In reality, it represents a distinct shift: treating internal platforms as products, designed for adoption and developer experience. In this conversation, we speak with Sean P. Alvarez and Ajay Chankramath—co-authors of the forthcoming Platform Engineer’s Handbook (Packt, 2026)—about where SRE and Platform Engineering converge, where they differ, and why collaboration between them is essential in today’s organizations.

Sean P Alvarez is the Chief Technology Officer of the Life Sciences business at Brillio, where he leads engineering teams and advises clients on cloud strategy and platform modernization. With over 15 years of experience in regulated industries and consulting, he specializes in applying Platform Engineering principles to drive enterprise-scale transformation.

Ajay Chankramath is the Cofounder and CEO of Platformetrics. With more than 35 years of global experience, he has led platform engineering at Thoughtworks, Oracle, Broadridge, and Xilinx, and is recognized as a Platform Engineering Ambassador and Team Topologies Advocate.

Together, they are writing The Platform Engineer’s Handbook on building secure, developer-focused platforms that streamline modern software delivery. The book takes a hands-on, “build first, clarify as you go” approach—guiding readers from source control governance and Kubernetes runtimes to observability, self-service onboarding, and AI-augmented tooling. Built for practitioners, it equips engineers to design platforms that scale without disrupting delivery.

You can watch the full conversation below—or read on for the complete transcript.

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1: Sean, Can you take us back to the moment when you first realized you were doing what we now call Platform Engineering? I imagine the term might not have existed yet, but the work was already there.

Sean Alvarez: It’s a great question, and thank you. I’ve always worked in somewhat regulated industries—life sciences and the financial industry. In those industries, the release process tends to be cumbersome. There are a lot of compliance issues, a lot of sign-offs that need to happen, and a lot of double and triple checking to make sure things won’t go wrong or that auditing won’t get messed up.

When I first started working with companies that would burn deliverables onto CDs and move things back and forth, I tried to introduce automation, but there wasn’t much trust in it at first. That led to centralized teams who stayed up all hours of the night doing deployments over and over again. There really wasn’t trust to move to something like what we’d now call DevOps.

At the same time, there was a desire to speed up development as the industry matured and as more start-ups entered the space and moved more nimbly. We wanted to make the deployment process—and the SDLC overall—less of a dreaded gate. Instead of developers thinking, “Oh no, I need to submit this to the DevOps team or the Operations team,” we wanted to turn it into an enabler.

To do that, we had to work across silos—security teams, networking teams, compliance, even upper management and governance—to put automation in place. That’s really where Platform Engineering took off for me: ensuring deployments were safe, compliant, and reliable, while allowing developers to move faster and giving the organization confidence that releases would go smoothly.

2: Every company has its own unique engineering culture. In your journey across different organizations, how have those environments shaped your understanding of what Platform Engineering really is?

Sean Alvarez: As I moved into more of a consulting role, I worked across industries and saw more organizations that operated closer to start-ups—moving fast even at the risk of breaking things. As the industry matured, I realized Platform Engineering wasn’t just about enabling speed. Developers also had to want to use it.

When you have individual full-stack teams in control of their deployments, Platform Engineering can look like extra work—just another backlog item or another check. If the platform feels forced, adoption won’t happen. Instead, it has to be something they want to use.

It’s not a “build it and they will come” situation—it has to be product-oriented. Just like external products compete for market share, internal platforms have to attract developer adoption. If we think of engineers as internal customers, that adoption becomes the real measure of success. It’s where the interests of leadership and developers align, and that’s when Platform Engineering really becomes powerful.

3: Ajay, in your journey across organizations, how did different environments shape your understanding of Platform Engineering?

Ajay Chankramath: My journey has been slightly different, but not too dissimilar to what Sean described.

Many years ago, I had a role supporting developers, though I was a developer myself. My first job involved building complex algorithmic software. But I noticed that developers—including my own team—always encountered friction. They couldn’t get things done the way they wanted.

Back then, roles were structured differently. There was a clear divide between developers writing code and then “throwing it over the wall” to another group—experienced engineers who built the product software. I started looking at this challenge through fundamental principles of software design, like loose coupling and high cohesion, which have been around for decades.

The first thing I did was identify common developer pain points and create reusable components to improve productivity. That led to a patent we called ROMS—Reusable Object Modules. This was 25 years ago, before DevOps, SRE, or Platform Engineering existed. Looking back, ROMS was essentially a fundamental building block of a platform: reusable capability packaged as a library.

We presented it at conferences, and that became my first foray into what I’d now recognize as platform thinking. The spark came from applying core software principles, which is probably the theme of today’s conversation—how principles extend into SRE and Platform Engineering.

Eventually, leadership asked me to build a team around this work. That transition took me from software development into support-related activities, which we then called Software Productivity Automation. We didn’t have today’s terminology, but the idea was similar.

Over time, working mainly in large companies, I saw the federated model in action: a centralized set of services with individual teams building on top. It’s a strong model because it gives smaller teams autonomy. But the downside is that centralized teams face huge backlogs. That almost never works out, and so the real question becomes: are individual teams able to be self-sufficient?

With the advent of public cloud, that’s changed significantly. Over the last 10–15 years, cloud services have made it much easier for smaller organizations to adopt these practices and integrate them into their ecosystems.

4: What are some of the biggest misconceptions you see today when teams practice SRE and Platform Engineering?

Ajay Chankramath: One of the biggest misconceptions is that constructs like SRE, Platform Engineering, DevOps, or DevEx are simply newer terms replacing older ones. That’s absolutely not the case. Each has its own role in the larger scheme.

We emphasize this in our book: DevOps is not a team and should not be a job title. It’s a cultural paradigm—about improving collaboration and communication across the SDLC.

SRE is about applying software engineering principles to operations to create highly reliable production systems. DevEx—developer experience—has always been there. It’s about how developers interact with tools, frameworks, and processes throughout the SDLC.

If you define these clearly, the overlap becomes easier to see. Platform Engineering sits at the center, enabling all three—giving developers self-service capabilities, enabling SREs, and supporting the DevOps culture.

That’s why it’s wrong to think Platform Engineering replaces SRE. SRE has existed since 2004 and continues to serve a distinct purpose. Platform Engineering is complementary—it enables SRE and DevOps to succeed together.

Sean Alvarez: I’ve also seen misconceptions where SRE is viewed only as production support. People then ask: does Platform Engineering automate that away? The answer is no.

SRE plays a vital role in ensuring production reliability. Platform Engineering spans the entire SDLC—from onboarding new team members to building, deploying, and running software in production. SRE should inform what Platform Engineering builds to make their jobs more efficient, but they aren’t the only users of the platform.

Platform success depends on collaboration—SREs, developers, and business owners all need to work together.

5: There’s a lot of overlap between SRE, DevOps, DevEx, and Platform Engineering. Would you like to talk a bit about what each brings to the table, how you personally draw boundaries between them, and where they are similar or different?

Ajay Chankramath: Absolutely, that’s a great question. Let me step back and offer one-line definitions for clarity.

DevOps is the cultural movement aimed at breaking down silos. It improves collaboration across the SDLC—from planning and coding to testing, deployment, and operations.

SRE began at Google as the application of software engineering principles to operations. Historically, operators knew systems well but weren’t software developers. Google shifted that model, expecting SREs to understand both software design and systems. Today, not every organization does it the same way, but the principle remains: SRE is more than system administration—it’s a role that requires deeper software knowledge.

DevEx is the outcome of enabling developers to be more productive. It’s well-studied now, with research from books like Accelerate and companies such as GetDX. Measurement is critical: you can’t improve productivity without first understanding where you stand.

Platform Engineering, then, is about the tools, processes, and techniques that improve all these aspects. It’s not just building automation or software—it’s building capabilities as a product. That’s why it’s different. Platform engineers don’t “take code and push it to production.” That’s an anti-pattern. Instead, the role is about enabling developers to be self-sufficient, reducing friction, and making the SDLC as fast and efficient as possible.

Think of it like providing APIs or libraries. Developers need to ask: “What do I need to be productive?” Platform Engineering exists to deliver those capabilities.

Sean Alvarez: What makes our Platform Engineer’s Handbook unique is its practical approach. We’re less about theory and more about how to actually create these capabilities.

If you look at tooling, the distinctions become clearer. Platform Engineering often brings to mind Kubernetes clusters and deployment automation—but it’s much broader than that. It includes enabling new projects, automating pipelines, and creating self-service capabilities.

SRE, on the other hand, focuses on reliability—SLIs, SLOs, SLAs, and observability. Their responsibility is to ensure systems are running well in production.

Developer experience isn’t just about portals like Backstage. It’s about making platforms easy to use. Whether through APIs, CLI tools, or portals, DevEx ensures developers adopt what Platform Engineering provides.

Together, these roles form a layered model: Platform Engineering builds capabilities, DevEx makes them usable, and SRE ensures reliability. The overlap is real, but the responsibilities remain distinct.

6: Looking back on your years building and scaling platforms, what was one of the hardest lessons you learned at the enterprise level?

Sean Alvarez: When people hear “enterprise,” they often think “process”—multiple levels of management, sign-offs, and compliance. That usually leads to a push for standardization.

In many organizations, Platform Engineering is introduced as a way to rein in DevOps sprawl. Instead of every team building its own pipeline or observability, leadership wants a single, standardized platform for everyone.

But forcing a single solution across the enterprise is often a recipe for failure. It creates complexity, slows delivery, and leaves some teams feeling stifled. They start working around the platform to meet their needs, and friction grows.

A better approach is the 80/20 rule: serve the 80% of teams whose needs can be standardized, and let the remaining 20% adapt their processes where necessary. That reduces time-to-value, avoids endless edge-case debates, and ensures most teams actually benefit from the platform.

Ajay Chankramath: Sean made a great point about the 80/20 rule. You’ll never get 100% success, and you shouldn’t aim for it. The question is: how do you achieve that 80%?

In our book, we outline seven principles that guide successful platforms. A few highlights:

1. Measure what you improve. Quantify waste and friction so improvements are visible.

2. Treat platforms as products. This isn’t just automation—it’s technical product management. Capabilities must be managed like products with clear value propositions.

3. Balance build vs. buy. Engineers love to build, but with so many products available, organizations must consider total cost of ownership.

4. Design for composability. Platforms aren’t just Kubernetes. They consist of multiple components. Each must be composable, extensible, and replaceable.

5. Prioritize observability. Don’t limit it to applications—extend it across the SDLC.

6. Enable team autonomy. If teams wait on others for security or approvals, waste accumulates. Platforms must empower autonomy.

7. Articulate value. This is critical. Success depends on clearly communicating the value unlocked, not just building capabilities.

Without these principles—especially value articulation—platform engineering risks losing executive support and ultimately failing.

7: Do you think there is confusion or resistance when people start working on Platform Engineering or its principles? Are there gaps, and what has worked for you in bridging those gaps?

Sean Alvarez: One reason organizations adopt Platform Engineering is to standardize and make developers’ jobs easier. But in doing so, we often take control away from developers.

For example, if we say, “Every developer must use this deployment pipeline,” it might simplify things for the organization, but inevitably some teams will run into cases it doesn’t support. Maybe the pipeline was designed for a single service, but a team needs to deploy three. Now they’re frustrated, waiting on Platform Engineering to adapt the pipeline—or worse, being told to make their work fit into it.

That dynamic quickly creates confusion and resentment. Developers no longer want to use the platform, and adoption stalls.

The way to bridge this gap is to treat the platform as an internal product. The most effective way is to have a technical product owner—someone who understands product management practices but also has the technical depth to talk with developers.

This role continuously interviews developers, identifies gaps in their day-to-day work, and ensures the platform gives them flexibility—guardrails where needed, but also options to override defaults when necessary. By organizing and prioritizing a backlog around developer needs, a technical product owner ensures the platform provides real value, which drives adoption and organizational success.

Ajay Chankramath: Sean covered most of it, but I’ll add this: the technical product owner role is not about saying “yes” to everything developers ask for. Every developer comes with their own perspective, and building every request would be unsustainable.

The job is to balance ROI across the organization. Building platform capabilities costs time and money. The question is: what value will this unlock across the enterprise, not just for an individual team?

That’s where challenging requirements becomes important. By pushing back and prioritizing based on organizational value, the technical product owner ensures investments make sense.

This ties back to the seventh principle we mentioned earlier—articulating value. Without it, platforms risk losing executive sponsorship. We’ve seen it happen: executives reassign platform engineers back into product teams because they don’t see visible value.

A strong technical product owner prevents that by showing how the platform delivers ROI across the organization. That value articulation is often the difference between success and failure.

8: Your book, Platform Engineer’s Handbook, takes a “build first, clarify as you go” approach. Instead of starting with strategy decks and frameworks, you dive straight into building. Why do you think this approach works better, especially for technologists new to Platform Engineering? And what makes it more effective than leading with theory?

Sean Alvarez: Great question. If you think about who gets into Platform Engineering, it’s often people from two backgrounds. Some are software developers who understand APIs and architecture but aren’t used to handling infrastructure. Others come from operations or SRE roles, familiar with Terraform, ServiceNow, or Dynatrace, but less with software development practices like GitHub projects or release pipelines.

Platform Engineering covers the entire SDLC, which is a big scope. You can’t really “practice” it in a small sandbox—it requires working with real teams, real projects, and real deployments.

That’s why starting with building makes sense. It’s similar to “dogfooding”—using what you create. If you build even a small demo platform and deploy an application on it, you immediately see the friction developers face. That teaches you what features are needed. You then build those features, measure their impact, and learn from the experience.

The theory and strategy become clearer once you’ve lived through the practice. You’re not just reading slides—you’ve felt the difference. That makes the lessons stick and prepares you to scale up to enterprise scenarios.

Ajay Chankramath: I agree. Developers understand software best. If you show them real builds and workflows, you bring them along much faster than if you start with strategy.

When this idea was first proposed, Sean and I knew it would be a challenge because we were used to explaining the “why” first. But flipping the model is powerful. It engages developers with what they already enjoy—building—and then shows them why it matters.

That’s why we believe this approach will make the book stand out. It’s not theory-heavy; it’s practical, hands-on, and aligned with how developers actually learn.

9: Ajay, you’ve repeatedly emphasized the seven principles and the importance of measuring value. Do you think taking a “build first, clarify as you go” approach will help highlight that key aspect of value measurement?

Ajay Chankramath: That was the first question that came to my mind when we considered writing this book. We’ve always said you need to measure something before you can improve it. How would that work with a “build first” model?

The more I thought about it, the more I realized this approach makes value measurement easier. When you’re actually building, the value is visible right there—not in a spreadsheet or a theoretical model. Developers can see what they’ve created, how much effort it took, and what productivity gains it delivers.

Instead of abstract discussions, you have concrete examples: “I built this, and here’s the measurable improvement.” That makes the articulation of value much stronger.

This is also one of the unique aspects of the book. I haven’t seen another resource take this approach—making value measurement practical and hands-on. It’s a challenge, but we’re confident it will provide a powerful way to connect principles with real-world practice.

10: Looking ahead, as more organizations mature their platform teams, how do you see the SRE role evolving? Do you expect a dramatic shift in the next few years?

Ajay Chankramath: Absolutely—and it’s a great question. Let me break it down across a few dimensions:

1. Specialization: SREs focus on complex reliability challenges, while platform engineers focus on building capabilities that enable both developers and SREs. The partnership between these roles will strengthen. Instead of friction over “who owns what,” SREs and platform engineers will complement each other.

2. Abstraction. SREs will increasingly work at higher levels—service meshes and clusters—rather than building individual features. Their focus will stay on ensuring reliability under pressure, not on building platform products. That’s where collaboration with platform engineers becomes critical.

3. Domain-driven platform engineering: This means applying platform principles directly into products, not just infrastructure. For SREs, it requires more domain knowledge—something Google emphasized in its original SRE model but that has been diluted over time. I believe we’ll see a return to that principle.

4. AI: SREs are already using AI for anomaly detection, root cause analysis, and automated remediation. Platform engineers will need to provide capabilities that make this easier. AI won’t replace these roles, but it will reshape them, moving focus from rote tasks to domain-driven decision-making.

5. Risk and compliance: Especially in industries like finance and healthcare, SREs will need to take on more responsibility here, supported by platform capabilities. Compliance is not going away—it’s only becoming more central.

We’ll also see some fluidity between roles. Some SREs will transition into Platform Engineering if their interests and skills align more with building capabilities, and vice versa. This cross-pollination will strengthen both practices.

11: Sean, you mentioned that much of Platform Engineering is about automating deployments and similar processes. Do you think AI can really make a big difference here, or is it still hype and early experimentation?

Sean Alvarez: Ajay mentioned the growing importance of domain knowledge, and I think that’s the key. Every time there’s a wave of abstraction, people ask if their jobs will disappear.

When cloud and serverless databases arrived, DBAs wondered if they were obsolete. Now with AI, people are asking the same thing: will software developers vanish because AI can write code? Do we even need Platform Engineering if AI can generate infrastructure as code, analyze logs, and raise alerts automatically?

The reality is that AI can take over rote, repetitive tasks—like writing observability queries or scanning logs for anomalies. That frees SREs and platform engineers to focus on higher-value work: understanding what uptime means in a given domain, or which processes truly require five nines of reliability.

For example, in fintech, stock-trading throughput during the day has a very different priority than a nightly batch process. One demands higher uptime even if it costs millions more; the other can tolerate delays. SREs and platform engineers, with their domain understanding, are the ones who can make those calls and guide how AI should be applied.

So I see AI as an inflection point. It won’t replace these roles—it will elevate them. The day-to-day debugging and manual tasks will shrink, while the focus shifts to domain analysis and delivering business value.

12: For someone currently in an SRE or DevOps role who is now expected to build or contribute to an internal platform, what’s the one mindset shift or practical skill you’d suggest they prioritize? And what’s the first practical step they should take to set themselves up for success?

Sean Alvarez: The mindset shift is this: whenever you build something—whether it’s a script or an automation—ask yourself, “Will someone need to contact me to use this?” If the answer is yes, it’s not done yet.

The goal is self-sufficiency. If a developer needs help every time they use your tool, you’re stuck in an operations role—answering tickets all day—instead of moving on to the next feature. True platform engineering means building things that others can use independently. That mindset is critical.

Ajay Chankramath: Sean gave a great example. To tie it together: the biggest shift is adopting a product mindset. Every script or automation should be treated like a product with long-term viability.

The second piece—and sometimes more important than technical skills—is communication. Build your soft skills. Relationships, collaboration, and communication determine whether a platform succeeds. Developers historically avoided this, but today it’s essential.

AI or not, tools will come and go. The constant is people. If you can communicate, align stakeholders, and articulate value, you’ll set yourself—and your platform—up for success.

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To explore the principles and practices discussed in this conversation in greater depth—including building developer-focused platforms from a blank slate, embedding observability and security, enabling self-service onboarding, and layering in AI-augmented services—keep an eye out for The Platform Engineer’s Handbook by Sean P Alvarez and Ajay Chankramath, coming August 2026.

The book provides a hands-on, progressive journey: from source control governance and Kubernetes runtimes to developer portals, reusable CI/CD workflows, infrastructure blueprints, and FinOps observability. Each chapter combines concepts with lab-based exercises and production-ready patterns, equipping engineers to build scalable, secure platforms that streamline software delivery.