Platform Engineering Insights

𝗘𝘃𝗲𝗿𝘆𝗼𝗻𝗲 𝗪𝗮𝗻𝘁𝘀 𝗔𝗜. 𝗡𝗼𝗯𝗼𝗱𝘆 𝗪𝗮𝗻𝘁𝘀 𝘁𝗼 𝗙𝗶𝘅 𝘁𝗵𝗲 𝗗𝗮𝘁𝗮. The funding pitch that often secures approval includes: - AI strategy - GenAI use cases - Sophisticated dashboards However, critical elements are frequently overlooked: - Data definitions - Quality checks - Metadata management - Lineage tracking - Clear ownership The truth that data engineers understand is that AI doesn't fail at the algorithm level; it falters because the data it relies on is untrustworthy. You can't construct a skyscraper on quicksand. While foundational work may not be glamorous, it is essential. It doesn't get showcased to executives or earn innovation accolades, yet it is vital for the stability of everything built above it. Before pursuing the next AI use case, consider the following: - Do we have consistent definitions? - Can we trace the origins of our data? - Who is responsible for data quality? - Are our data pipelines tested and monitored? 𝖥𝗂𝗑 𝗍𝗁𝖾 𝖻𝖺𝗌𝖾𝗆𝖾𝗇𝗍 𝖻𝖾𝖿𝗈𝗋𝖾 𝖻𝗎𝗂𝗅𝖽𝗂𝗇𝗀 𝗍𝗁𝖾 𝗉𝖾𝗇𝗍𝗁𝗈𝗎𝗌𝖾. "𝗔𝗜 𝗶𝘀 𝗼𝗻𝗹𝘆 𝗮𝘀 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗮𝘀 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮 𝗶𝘁'𝘀 𝘁𝗿𝗮𝗶𝗻𝗲𝗱 𝗼𝗻. 𝗚𝗮𝗿𝗯𝗮𝗴𝗲 𝗶𝗻, 𝗴𝗮𝗿𝗯𝗮𝗴𝗲 𝗼𝘂𝘁—𝗻𝗼 𝗺𝗮𝘁𝘁𝗲𝗿 𝗵𝗼𝘄 𝗳𝗮𝗻𝗰𝘆 𝘁𝗵𝗲 𝗺𝗼𝗱𝗲𝗹." Illustration inspired by John Wernfeldt

DevOps vs. SRE vs. Cloud vs Platform Engineering. What is the difference? In my first company, I was hired as a DevOps engineer — but ended up working on internal automation tools too. It took me a while to really distinguish between these roles. They overlap a lot, but each has a different focus. - Cloud is about the platform - DevOps is about the process - SRE is about reliability - Platform Engineering is about productivity at scale let's dive in further: ⸻ Cloud Engineers own: • Cloud infrastructure design & deployment • Resource optimization & provisioning • Troubleshooting and support • Security implementation • Cost-performance optimization …and more, depending on your cloud stack and niche. DevOps Engineers drive: • CI/CD pipelines and Infrastructure as Code (IaC) • Deployment automation (blue/green, canary) • Bridging dev–ops workflows • Scripting & automation • Provisioning infra consistently across environments Site Reliability Engineers ensure: • Reliability, availability, and scalability of systems • Defining & tracking SLOs/SLIs • Chaos engineering & incident response • Performance tuning • Monitoring, alerting, and resilience testing Platform Engineers build: • Internal Developer Platforms (IDPs) • Tooling and automation for developer productivity • Golden paths for developers • Reliable, scalable infra platforms • Self-service systems for large engineering teams ⸻ Even though the lines are blurring, AI is amplifying the impact of each role. It’s interesting to see how they’re evolving in practice. Hope this breakdown helped clarify the landscape a bit. What’s your take on where these roles are headed? • • • If you found this useful.. 🔔 Follow me (Vishakha) for more Cloud & DevOps insights ♻️ Share so others can learn as well

Lesson #5: Build Platforms, Not Tools. Create a Platform Advantage One of the most strategic things that a tech company can do is build a platform advantage. This creates a durable moat for a business. It also creates a built-in incentive for the market to keep coming back to you. So let’s study the concept of a Platform Advantage. A platform can bring several benefits to a business. 1. Foundation On Which Others Build Value: A platform is a foundation on top of which other players in the ecosystem build value. An example of this is application developers building apps for the iOS or Mac or Windows platform. 2. Platform Takes a Minority of the Available Economic Advantage: Typically, a great platform is built in a way that the ecosystem enjoys a large part of the economic opportunity availed by the platform. Going back to IOS or Windows, the revenue captured by all the app developers building on iOS is far greater than what Apple makes on iOS devices or what Microsoft makes on Windows. 3. Decrease in Incremental Effort: A platform advantage is defined as something where value can be realized with far less incremental effort for every subsequent addition for the user/customer. A great example of this is our Meraki platform. It started as a switching platform, but then the management plane was able to also manage cameras in the environment and people just decided to add them because the simplicity of managing everything is that much easier. 4. Sum is Greater than the Parts: The value of a good platform is always greater than the sum of the piece parts. In the security business at Cisco, we used to operate much more as a holding company. Several different products. Several different ways to use and manage the products. Each run by a General Manager. This created a disjointed experience for customers and incongruent objectives between the teams and the customer. And it didn’t take advantage of the breadth of the offering. As we built out the Cisco Security Cloud, all of this started to come together. There is a common design language, a common policy engine, a common set of policy objects, cohesion and predictability in how each component of the platform behaves, etc. Adding a new product to your environment has very low marginal effort. All the piece parts are well integrated. 5. Ecosystem Advantage: A platform delivers an ecosystem advantage. If you think of the Google ecosystem vs the Apple ecosystem, people aren’t making purchase decisions based on every small feature that gets added. When the iPhone 15 is released, only decision I make is whether to upgrade from my iPhone 14 to the newer version. What I’m not doing is evaluating the camera on the Google Pixel. That’s because I also use the Apple Watch, and the iPad and the Mac and the AppleTV and the VisionPro and iTunes and Apple News and they all work in perfect harmony with each other. The platform advantage leverages the power of the ecosystem. Net net, build platforms.

A Platform Engineering VP shared some eye-opening numbers with me yesterday: VP: "I've been trying to quantify our environment costs. We have 200 developers, each making ~5 PRs a week." Me: "How long does it take to test each change?" VP: "Average wait time for a test environment is 45 minutes. Plus another hour to run tests. Sometimes up to 3 hours if there are conflicts." *does quick math* "That's about 2000 engineering hours every week just waiting for environments and test results." VP: "Exactly. At $150/hr fully loaded engineering cost, we're burning $300K every week. But duplicating environments for faster testing would cost even more in infrastructure." This is when I shared how modern service mesh architectures are changing this equation: Instead of duplicating infrastructure, you can create instant test environments by isolating at the request level using Istio/Linkerd. Each developer gets their own "slice" of the environment through smart request routing. The numbers got interesting: - Infrastructure costs: Down 90% (sharing resources vs duplicating) - Wait times: From 45 mins to 2 mins - Test completion: From hours to minutes - Time to debug issues: Cut in half The VP's response: "So we can give every developer instant environments AND reduce costs?" This is why I'm excited about modern cloud native architectures. The ROI isn't incremental - it's transformative. Real question: How are other platform teams measuring the cost of slow testing cycles? Would love to hear your metrics. #platformengineering #devops #microservices #productivity

In conversations with engineering leaders, I'm noticing an emerging theme: smart, capable managers who "grew up" in the 2010s and early 2020s are struggling to adjust to a new reality in tech leadership. For over a decade, the rule of the game was simple: hire, grow, and retain. Leadership meetings were dominated by conversations about headcount, hiring progress, and ambitious growth targets. There was grilled venison tapas at lunch, and we talked a lot about psychological safety and inclusion. These were important topics (and tapas), but they existed in an environment of abundance. Sure, we wanted things to be more efficient — but the solution was often to spend more money to make it so. We had no choice — headcount was growing by the day, and the focus was on scaling rapidly to meet demand and capture market share. Fast forward to today, and the landscape has shifted dramatically. I spoke with a VP of Engineering recently: smart, capable, and struggling with how to report upwards effectively while still maintaining empathy for the realities of software engineering and the people in their organization. They were visibly relieved to hear me say that others are grappling with these same challenges. Engineering leaders at all levels are living in a new world of intense scrutiny and accountability. The instincts and strategies they honed over years of rapid growth aren't serving them well in this new environment. Under pressure, toxic approaches that would have been quickly dismissed in the past are now getting airtime they never would have deserved before. We're seeing a fundamental shift in what it means to be an effective engineering leader: 1. Financial Acumen: Leaders now need a deep understanding of financial metrics and how engineering decisions impact the bottom line. 2. Operational efficiency: There's a renewed focus on doing more with less, optimizing processes, and identifying areas of waste. 3. Strategic prioritization: With limited resources, the ability to ruthlessly prioritize and communicate trade-offs has become crucial. 4. Change Management: Leaders must guide their teams through organizational changes and shifts in company strategy with transparency and empathy. 5. Metrics-driven decision-making: There's increased pressure to justify decisions with data and demonstrate tangible value. 6. Stakeholder management: Navigating complex relationships across the organization and managing expectations has become more critical than ever. The challenge lies in balancing these new demands with the core principles of effective engineering leadership: fostering innovation, maintaining team morale, and delivering high-quality products. How has your role changed in the past 12-18 months?

💫2026: How GenAI’s Role Changes in Insurance Simple efficiency gains are done. The basic productivity phase of GenAI is largely complete. What comes next is not smarter AI. It is exposed operations. ⸻ 🔍 What GenAI really surfaces in 2026 As GenAI moves beyond basic automation, it begins to reveal operational gaps insurers have lived with for years: 　⚠️ processes that work only because people fill in the blanks 　⚠️ decisions based on tacit understanding rather than explicit rules 　⚠️ operations that can be explained, but not consistently repeated This is not a technology issue. It is an operational reality check. ⸻ ⚙️ Why this matters now In 2026, GenAI removes the human buffer that used to absorb ambiguity. What was once: • “handled case by case” • “managed by experienced staff” • “good enough in practice” becomes visible, inconsistent, and hard to scale. ⸻ 🎯 Executive takeaway GenAI does not change insurance operations. It reveals which operations were never fully defined in the first place. GenAI is no longer an efficiency tool. It is an operational stress test. #GenAI #Insurance

As Chief Engineer of strategic ballistic missile submarine USS Kentucky, I felt I had to have every answer. I was in every action, every system, every repair. The stakes were too high for anything less. But here’s the truth: that approach was untenable. No single person can shoulder that weight forever. What saved me—and what made our team world-class—wasn’t my control. It was: ✅ Delegation — trusting officers and sailors to own their watch. ✅ Intent-based leadership — giving clear direction, not micromanagement. ✅ Trust-based communication — speaking up early, listening deeply. ✅ Transparent expectations — clarity about what “good” looked like. ✅ Deep but meaningful checking — not hovering, but verifying. Scaling your business is no different. Early founders often try to be in every decision, every hire, every customer interaction. But just like on a submarine, that weight will break you—and stall your team. The transition from “I control everything” to “we achieve everything together” is what transforms brilliant engineers and scientists into enduring leaders. 💡 Where are you in that journey—holding every answer, or scaling through trust? #Leadership #ScalingUp #Delegation #ExecutiveCoaching #EngineeringLeadership #CoreX #Trust #IntentBasedLeadership #focalpountcoaching

12 years in DevOps, and I’ll say it straight. DevOps is broken. Not in theory. In practice. It was supposed to bridge the gap between devs and ops. Instead, it created: ❌ Devs still waiting on ops. ❌ Ops still firefighting infra issues. ❌ Tool sprawl eating budgets. ❌ DevOps engineers babysitting pipelines instead of innovating. But... DevOps was never meant to be a job. 𝐈𝐭 𝐰𝐚𝐬 𝐚 𝐩𝐡𝐢𝐥𝐨𝐬𝐨𝐩𝐡𝐲. Companies misunderstood it, built "DevOps teams," and made the silos worse. Meanwhile, 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐝𝐞𝐥𝐢𝐯𝐞𝐫𝐲 𝐠𝐨𝐭 𝐰𝐚𝐲 𝐦𝐨𝐫𝐞 𝐜𝐨𝐦𝐩𝐥𝐞𝐱: → Multi-cloud, Kubernetes, and serverless took over. → Security and compliance became non-negotiable. → Developer velocity became a business priority. That’s where 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 comes. Instead of custom scripts, scattered pipelines, and ops bottlenecks… Platform teams build golden paths, 𝐬𝐞𝐥𝐟-𝐬𝐞𝐫𝐯𝐢𝐜𝐞 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬 𝐭𝐡𝐚𝐭 𝐥𝐞𝐭 𝐝𝐞𝐯𝐬 𝐬𝐡𝐢𝐩 𝐟𝐚𝐬𝐭𝐞𝐫 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐛𝐫𝐞𝐚𝐤𝐢𝐧𝐠 𝐭𝐡𝐢𝐧𝐠𝐬. ✅ Internal Developer Platforms (IDPs) remove infra complexity. ✅ Devs don’t waste time on YAML hell or Terraform nightmares. ✅ Standardization = faster, more reliable deployments. ✅ Security & compliance are baked in from day one. And the biggest shift? Platform teams treat developers as customers. 𝐃𝐞𝐯𝐬 𝐬𝐡𝐨𝐮𝐥𝐝𝐧'𝐭 𝐛𝐞 𝐟𝐢𝐠𝐮𝐫𝐢𝐧𝐠 𝐨𝐮𝐭 𝐢𝐧𝐟𝐫𝐚. 𝐓𝐡𝐞𝐲 𝐬𝐡𝐨𝐮𝐥𝐝 𝐛𝐞 𝐬𝐡𝐢𝐩𝐩𝐢𝐧𝐠 𝐜𝐨𝐝𝐞. DevOps isn’t evolving. It’s being replaced. High-performing teams are already moving to platform engineering. What’s your take? Is your company making this shift?

Platform over projects.     I’ve learned the hard way, I used to be on the product and platform side of business myself, that there’s no differentiated edge in wiring the same service ten different ways. It looks clever at the moment, but it slows everything that matters.     Time-to-value, reliability and the team’s attention.   What moves the needle is surprisingly simple: standardize the repeatable, and spend your creativity where it actually differentiates.      For me, that means a few clear, pre-approved ways to build common things (APIs, data flows, ML jobs) with the essentials already baked in - security, testing, observability. Fewer choices on the basics, more energy for the work that sets you apart.     It’s not about control for control’s sake. It’s about focus.    When the road is well-lit, people move faster and with more confidence. And the best ideas emerge where they matter most - product, experience, and outcomes.   If you’re still celebrating bespoke builds for routine problems, you’re not disrupting nor creating shareholder value.    Standardize the road. Let your best people sprint and create a unique competitive advantage.     Happy to compare notes on where to start and what to measure.      #PlatformEngineering #ProductEngineering #DeveloperExperience #Leadership #OrionInnovation  

The New Culture of Influence Power no longer moves top-down from institutions—it now flows outward from communities, creators, and digital networks. Gen Z places 5× more trust in peers and influencers than older generations. They look sideways, not upwards, for authority. • Identity has gone global: Gen Z and Millennials form global communities through platforms like TikTok, Discord, and Twitch. Geography matters less; shared values matter more. A climate activist in California connects more deeply with another in Seoul than their local politician. The internet has united young people across borders and reshaped identity into something global and collaborative. • Culture wars vs. creative renaissance: The narrative of polarization and culture wars misses the creativity rising from the chaos. Young generations use memes as political statements and remix traditional arts using AI. Nearly half of Gen Z already uses AI daily—not just for work but for music, art, and culture. Their nuanced stance—both excited and wary—will define how we balance innovation and integrity. • Platform power: loyalty earned, not demanded: Tech giants no longer monopolize culture. Young users instantly abandon platforms that violate trust or lose relevance, shifting influence quickly. Loyalty today is continuously earned, creating opportunities for new, more responsive players. Influence is increasingly open-source—a teen with a phone can launch a movement forcing a corporate or governmental response overnight. America’s next chapter belongs to a politically disillusioned yet socially empowered generation. They’re redefining trust, loyalty, and power. The center of gravity has shifted, and the new influential voices are grassroots, digital-first, and global in outlook. Smart founders, policymakers, artists, and strategists must engage these emerging networks and values directly. Bold ideas now spread bottom-up—and that’s exactly where the future of culture and innovation lies.