Richard Vodden

How do you convince an organization to let automation manage Kubernetes workloads at scale? Yasmin from CloudBolt explains why the real challenge isn't the tooling — it's building enough trust to act on it. Data points, guardrails, preview modes, rollout gates. "You can only go as fast as the speed of trust." Watch the full interview: https://ku.bz/bvr2-nv4P Meet the CloudBolt Software team at Booth 438 at KubeCon Europe 2026 in Amsterdam 👉 https://ku.bz/5pwF68l6Q

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We've got some interesting problems ranging from building conversational systems that affects 2Mn+ SMBs, process 1.35Bn monthly transactions and providing streaming learning platforms for creators and educators to hundreds of thousands of learners

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Tom Elliott explains his vision for simplifying CI/CD and the use of Terraform with his product Ocuroot to John Crickett

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Event sourcing and BDD scenarios share the same mental model: both capture what has happened, not what hasn't. In event sourcing, we name events in past tense: "OrderPlaced," "PaymentReceived," "InvoiceAged." In Given-When-Then scenarios, the Given section describes past conditions—things that have already occurred. Here's what this means practically: there's no "payment not made" event because nothing happened. But "time passed"? That's an event we can capture if it has meaning in the domain. This shapes how I write Given statements. Instead of "Given I have not paid my invoice," I write "Given seven days have passed and there's no record of payment." Every Given becomes something that actually occurred—making scenarios more testable and mapping better to how (not just automated) systems really work. How do you handle time-based events in your scenarios? https://lnkd.in/gcMZHdph

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Spoke at the London Microservices Meetup yesterday - on the topic of keeping things up to date. There always seems to be something that needs to be updated or migrated, particularly if you're a platform team. Getting good at managing these sorts of projects is well worth it. They may not be exciting but they are essential, and if you can get through a migration without everyone hating you, that's a badge of honour! I very much enjoyed Eddie's talk at the same event on Building AI Agents, a great roundup of the options available with lots of practical examples. Thanks to Oliver Short, Mark Short and the SEEKR team for inviting me and hosting the event. If this sounds interesting to you, I quite often give talks at organisations, either as a one-off or as part of a larger consultancy engagement. There's a list of recent talks on my website at https://lnkd.in/eJ9tJrwE

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If you’re a Head of Engineering who is ready to transform a team, then I've got a role for you. I’m partnering with Julia Bearzatto at Equiem on a genuinely transformational hire. Equiem is entering its next phase of growth and needs a strong engineering leader to help bring its vision to life. This isn’t a keep-the-lights-on role. It’s a reshape-the-engine-room role. The mandate 👉 You’re a T-shaped leader with strong product thinking and serious delivery discipline. 👉 Drive cultural change, not avoid it. 👉 Have opinions on architecture, data strategy, and operating models. 👉 Care deeply about people's performance and role clarity. 👉 Connect technical decisions to commercial outcomes. 👉 Get involved in design and architecture without needing to code daily. This is innovation-led, product-led engineering maturity work. Not just scale for scale’s sake. What you’ll actually do in the first 6–12 months 👉 Reshape the team (right people, right roles) 👉 Shift mindset from legacy to curious & outcome-driven 👉 Implement a modern operating model 👉 Create visibility and predictability in delivery 👉 Unlock 7 years of event data using pragmatic tooling 👉 Elevate tech leads into real leaders 👉 Strengthen SOC2 / PCI discipline without slowing innovation Success looks like: 👉 One unified engineering team pulling in the same direction 👉 Mature planning and reliable timelines 👉 Engineers contributing to product strategy 👉 Data driving real business insight Why you’ll love it: 👉 Autonomy to restructure and implement your model 👉 A CPTO who wants you to have an opinion, not ask for permission 👉 A stable team (low attrition that’s both an opportunity and a challenge) 👉 A genuine chance to leave a mark on the company’s trajectory If you thrive on lifting standards, reshaping culture, and building a product-engineering powerhouse, let's talk. I've got plenty of information to share so please hop into my inbox if you'd like to find out more.

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Your CI/CD pipeline takes 45 minutes. Developers merge to main and go to lunch. You call this continuous delivery. We call it continuous waiting. The symptoms: - 30-60 minute pipeline runs for basic changes - Flaky tests that fail 20% of the time for no reason - No clear rollback strategy - "just revert the commit and wait another hour" - Developers merge to feature branches to "test in CI" because local dev is broken - Teams bypass CI/CD entirely for hotfixes because it's faster to YOLO to production Here's the truth: if your deployment pipeline takes longer than a coffee break, developers will route around it. And they should. A slow pipeline isn't just annoying. It's a productivity tax that compounds: - Context switching kills flow state - Batch changes get bigger and riskier - Feedback loops stretch from minutes to hours - Fear of breaking things slows innovation What actually fixes it: - Parallel test execution - don't run 500 tests sequentially - Fail fast on static analysis before expensive integration tests - Incremental builds - rebuild what changed, not everything - Reliable tests or no tests - flaky tests are worse than no tests - Deploy with feature flags, not by waiting for perfect code At WANTED.solutions, we've cut customers pipeline times from 60 minutes to under 10 minutes while increasing reliability. The secret isn't exotic tools. It's brutal prioritization of what and when actually matters. How long does your deployment take? Be honest. #wantedsolutions #creativepioneers #ci #cd #deployments #pipelines

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Platform Engineering Needs a Shared Language As I continue to chat with clients globally, I have seen that one of the hardest parts of platform engineering isn’t the tech, it’s the translation and lack of a shared language. I’ve lost count of how many times we’ve started a client kickoff and heard five different definitions of what “the platform” actually means. CI/CD pipelines, IDPs, Kubernetes, portals, everyone's talking about something slightly different. Those small misalignments slow everything down. Without a shared language and a clear strategy, teams struggle to move. That’s why we always spend time upfront building alignment before a single component gets designed. The Platform Engineering community has been a great reference point for us, giving us shared frameworks, vocabulary and examples that get everyone on the same page. Once that happens, org design, tooling, metrics and governance just flows much more naturally. I am looking for more insights into platforms and would love to hear how your team and organization describes “your platform”?

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If you fancy a change of pace from the latest blog on AI incantations, we've written about - what I think is - a nice pattern for our Rust AWS Lambdas. https://lnkd.in/ejwc4RqC

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The best engineering leaders protect their teams. But no one talks about the cost. At CTO Craft Con London, our Head of Engineering Rebecca A. is speaking about that hidden work in her talk: “The Human Load Balancer: Protecting Your Team Without Burning Out.” A session about recognising overload, moving past the myth of the hero leader, and building leadership practices that actually last. It is a timely conversation, and one Rebecca A. brings real leadership experience to. If you’re at CTO Craft Con next week, make sure you catch her session 👇 https://lnkd.in/epHfuQyz #EngineeringLeadership #CTOCraftCon #Leadership

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Landing your first Platform Engineer role is both exciting and daunting, but you’re not alone. Platform engineering has become a cornerstone of modern software delivery. Our first 90 days should focus on listening, learning, and mapping: understanding developer pain points, auditing existing tooling and infrastructure, and identifying where automation can have the biggest impact. Check out a step-by-step roadmap for thriving in your first 90 days as a platform engineer: https://lnkd.in/ed_fzaYA #PlatformEngineering #DevOps

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Your CI/CD bill is not exploding because of “expensive runners,” it is bleeding out through flaky tests, over-parallelized jobs, and slow feedback loops that quietly tax every deploy This piece shows you how to redesign pipelines so you cut compute waste, shrink queues, and speed up developer flow without adding yet another approval gate or YAML religion Full breakdown in the comments. #DevOps #CICD #PlatformEngineering

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“We are not load testing to celebrate every success. We're not testing to celebrate every green light we get from a test. No, we load test to uncover failures.” Just Eat Takeaway.com's Senior SRE Christopher Orchard shared how a Friday-night incident reshaped their approach to reliability and sparked a cultural shift: blameless learning, stronger architecture, and adoption of Grafana Cloud k6. 🎥 Watch the talk from #ObservabilityCON: https://lnkd.in/eBQ9WjmF

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Microservices-based development can become a nightmare of tangled environment dependencies. At QCon London, WireMock CTO Tom Akehurst talked this challenge - and how it can be solved by scaling API independence. Watch the recording here: https://lnkd.in/ebE7s4mq

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Clearing System Design interviews at the Staff+ level remains a mystery. Even if you go for best-in-class courses, like HelloInterview by my colleague Stefan, you're often left on your own to show your experience. Sys Design is hard - you need to master foundations, manage time and comms, make solution future-proof, etc. Common prep materials make it worse with overly complex examples like social platform ranking systems or Dropbox-style sync protocols. The truth is: on Staff+ interviews they ask relatively simple questions to test depth, not speed. You won't waste time drawing 20 components - they want to see how deeply you think instead. I don't know the full formula to clear Sys Design rounds at this level, but can share what was working for me personally: 1/ Learn the fundamentals: things like GFS/Dynamo/RocksDB papers, behavior of distributed systems under high load, data locality, over-provisioning, clocks, replication lag, consistency models, use scientific notation, etc. Example from Anthropic Sr Staff interview: - Me: "I don't remember the exact metric name, but we trigger provisioning when we detect this resource utilization pattern." - Interviewer: "Oh, we call it metric X, and pattern Y, and the way you're describing it is how it works in our system." Pro tip: share some anecdotes, e.g., "we don't need persisted state from the get-go, but it was a nightmare to revoke stateless sessions on my previous project". 2/ Become good at sizing the problem. Know the population of key countries/markets, understand seasonal usage patterns across days/weeks, distributed systems fundamentals - like maximum dataset size for RDBMS, DB index overhead, key latency numbers, etc. Example from Google L7 interview: - Me: "Let me quickly quantify the system. For this problem, I'm estimating the population size to be in the mid-hundreds of millions, let's say it's 500M, but I will round it up to 1B." - Interviewer: "Actually, in my reference notes I have 500M, so let's keep it like this, so it's easier for me to compare the final numbers." - In the end, the final numbers checked. Pro tip: casually drop some fundamental reference, e.g. "By Little's Law, RAM won't bottleneck this cluster given our latency and throughput targets". 3/ Start and finish simple. Most real systems avoid expensive services like Kafka, complex client/server protocols, or real-time UI updates. Example from my current role's interview: - Me: "I'd just hash the input and denormalize the schema to avoid excessive DB upserts. Not the fanciest approach, but it works". - Interviewer: "Oh, this is exactly how our system actually works". Pro tip: research the company's tech stack, and don't be shy if you're not familiar with it: "I haven't used GCP, but we solved similar problems with AWS service X".

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