Come listen to experts in building infrastructure and enabling development and deployment processes discuss the ideas and technologies involved in DevOps.
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What If Tools Are Not Expensive To Build
Share Episode Developers spend more than 50% of their time reading code, making it the single largest expense in software engineering. Despite this massive cost, the industry rarely discusses or optimizes how we read code. So we've brought in Tudor Girba, CEO at Feenk to help us rethink, just how software engineering should be done. Instead of relying on manual reading and generic text editors, teams must shift toward building deterministic, contextual tools to directly extract information and answer questions about their systems. The suggested solution? Contextual and composable micro-tools writen by everyone focused on exposing just the right information at the right time. This creates the opportunity for structural interrogation of your solution. And how many tools should we? We'll if one example of tool is testing, and 50% or more of your code can be tests, imagine what percentage of your software should be actually production related! Most importantly, generic tools fall short, but where can we find how to build the right tools, listen in to find out.... 💡 Notable Links: ✨ Episode: IDE & Copilot & Critical ThinkingBook: Moldable software developmentWardley MapGuest Request: Formal Verification🎯 Picks: Warren - The real stuff: Underwood Ranches SrirachaTudor - The beaches of Normandy
DR: Staying resilient in the cloud
Share Episode Welcome back to another hopefully, relief from architectural existential dread. This week, we've pulled in Seth Eliot from Arpio, (Ar-Pi-O, RPO, get it?), to dive headfirst into the beautiful, deeply expensive illusion that migrating your legacy infrastructure to a major hyperscaler magically grants it instant immortality. It doesn't. We break down the shared responsibility model for resilience, which was conveniently cribbed straight from the security model, and analyze how the foundational promise of automated fault isolation boundaries routinely crumbles. From cloud providers sticking multiple "independent" availability zones inside the exact same physical building, to multi-AZ cascading anomalies, to regional power grid failures, it's clear your provider's abstractions aren't nearly as resilient as their marketing slides suggest. Discussed within is the "Thundering Herd" phenomenon, that can't be ignored even when the failover clusters are designed correctly. From cross-organization KMS re-encryption loops to the horror of fragmented application logs across CloudFront edge regions, at the end of the day, true resilience isn't achieved by forcing your engineering team to implement features, it's about architecting your baseline, confidentiality for the inevitability of production burning to the ground. 💡 Notable Links: ✨ Episode: Eat your security vegetables✨ Episode: Matt vibecodes✨ Episode: on DNS and isolation🎯 Picks: Warren - Book: Moldable software developmentSeth - Lockpick set
Eat your security vegetables
Share Episode This week's adventure tackles the absolute absurdity of modern enterprise infrastructure, where a single company can easily find itself running multiple different CI/CD platforms due to unchecked mergers and acquisitions. We've brought in Chris Farris, AWS Security Hero and consults with companies via Securosis. And dig deep to find the security cracks and philosophize about the real world impacts of tech debt in the AI age. Management rarely prioritizes standardization, leaving security teams to defend a chaotic swamp of mixed cloud providers, GitHub repositories, and nostalgic on-prem Bitbucket instances. We define this accumulated technical debt not as some abstract concept, but as literal potholes on the infrastructure Autobahn—annoying speed bumps that permanently damage velocity and set organizations up for an inevitable disaster. We contrast this with the evolution from old-school sysadmins cutting their fingers on rack screws to modern engineers spinning up entire architectures with a few lines of code, noting that the ease of deployment has far outpaced our willingness to clean up our own mess. The crisis is only accelerating now that the cost of writing code (but not having to maintain it) is rapidly approaching zero. While letting an AI agent autonomously build a website or manipulate an AWS sandbox over a single Saturday afternoon sounds magical, it creates a terrifying volume of unreviewed, context-devoid software. Compounding this systemic frailty, massive cloud provider layoffs mean the crucial institutional memory and human operational experience required to survive are walking right out the door. We expose the fundamental flaw of modern agentic tooling: they completely lack fine-grained access control, operating on a dangerous all-or-nothing identity model. Until autonomous agents are engineered with actual conscience, consequence, and common sense, security teams will continue fighting a losing battle against a digital supply chain. 💡 Notable Links: Chris' Article on AI Tech DebtBreaking Open Source: Malus - ArticleVercel Security Incident✨ Episode: 🎯 Picks: Warren - Rick & Morty S02 + S03Chris - Risky Business: The latest actually good cybersecurity news
Automatic Data Pipelining: One More Turtle Ahead
Share Episode We grabbed Donald Nguyen, co-founder and CTO at Corvic, to discuss the absurd complexities of enterprise data and multimodal inference. We explore how organizations habitually hoard mountains of useless, "dead" data just out of the sheer fantascy that someone might ask for it later. We highlight the fundamental disconnect where data collectors using tools like Airbyte and Kafka speak a completely different language than the business consumers analyzing it in Excel. True scale isn't just about managing petabytes; it's the absolute nightmare of extracting subjective business meaning from flat PDFs and invoices. In the deep-end of vector embeddings, we're challenging translating data into a different semantic universe requires imposing a heavy business bias. Auditors and artists will view the exact same invoice completely differently, meaning your embedding model selection is incredibly subjective to the business context. The industry's desperate search for actual AI success stories beyond basic workflow automation is still ongoing as we laugh—and cry—at the reality that companies are likely budgeting 50% of an engineer's salary for LLM token usage, effectively enabling product managers to burn cash on infinite loops to generate prototype code. Reasonable or unreasonable? And lastly, we tackle the existential dread of securing autonomous AI agents. Because fine-grained access control for agent actions is basically an unsolved fantasy, we must treat their execution environments as entirely untrusted, relying on rigid sandboxes like AWS Firecracker VMs. Prompt injection attacks are an inevitable flaw of the transformer architecture, and the industry's best defense mechanism seems to be wrapping models inside of other models to validate the outputs. It is quite literally turtles all the way down, and the winner of enterprise security is simply the organization that manages to put one more turtle ahead of the attackers. 💡 Notable Links: Kuuk Thaayorre Aboriginal Tribe - Cardinal Directions✨ Episode: Generating automatic integrations at scale🎯 Picks: Warren - Dr. NEMO: Clockwise circle pitDonald - Book: InvestiGators
The Human Value Versus AI Legacy Code
Share Episode Down to business with GitHub's Cassidy Williams, Senior Director of Developer Advocacy at GitHub, where we try to untangle the existential dread of modern software development. It includes the sheer absurdity of managing a platform that officially crossed the one billion commit mark in 2025. Currently absorbing a completely unreasonable 275 million commits per week, GitHub's technical debt is naturally showing its age under the weight of AI agents aggressively creating pull requests. And with company's own copilot advocating for more, we explore the daily reality of being the internet's punching bag during an outage, and how the "Tiny Wins" buy back developer affection by still shipping the critical features. Which of course is a small signal in the sea of the industry's collective identity crisis: vibe coding and the valley of AI-generated garbage. Discussed is one suggested solution of strongly typed languages which are skyrocketing in popularity because we desperately need rigid guardrails to babysit the hallucinated code our non-human agents are frantically pushing to production. Things have gotten so dire that we commiserate on missing the good old days of Stack Overflow, where instead of a chatbot agreeably telling you your terrible idea is great, a grumpy human engineer would just ruthlessly roast your architecture honestly. 💡 Notable Links: Cassidy's post on Typed LanguageCassidy's newsletterBook: 4-Hour Work Week✨ Episode: Typed Languages✨ Episode: Vibecoding✨ Episode: Productivity Isn't Real🎯 Picks: Warren - Book: The Light EatersCassidy - Obsidian Offline Wiki
Who needs a server?
Share Episode Founder of Bespinian and long-time cloud solutions architect, Lena Fuhrimann, sits down with us to clarify the widespread confusion around serverless architecture. We discuss how serverless is often incorrectly equated solely with Function as a Service (FaaS), when it actually represents a broader spectrum on the abstraction ladder—including managed AI inference, container platforms, and databases. Lena shares her early career traps of building a fragmented landscape of sixty "nano-services" and explains why starting with a well-architected monolith and progressively breaking out microservices based on distinct resource or lifecycle requirements is a much saner approach. Then we shift to drivers behind cloud migrations, emphasizing that the primary financial benefit of serverless isn't necessarily shrinking the monthly cloud provider bill, but rather optimizing your most expensive resource: engineering time. By offloading mundane infrastructure patching to the cloud provider, teams can focus entirely on delivering tangible business value to customers. But cost is still there too. We also explore the psychological challenges of adopting new paradigms, sharing a fascinating story of bridging the gap for a VM-loving engineer by introducing immutable infrastructure concepts through Packer and Ansible before fully transitioning them to containers. And of course we tackle the dreaded topic of "cold starts" and why complex workarounds—like building custom Lambda warmers to periodically call APIs—often defeat the core benefits of reduced total cost of ownership. 💡 Notable Links: BespinianBook: Drive — Motivation 3.0✨ Episode: Typed Languages, Haskell, and building monoliths🎯 Picks: Warren - Better thank coffee: Himmelstau teaLena - Home Assistant open source project and Autrix Clocks
How to build a monolith the right way
Share Episode We sit down with Ian Duncan, senior staff engineer on the stability team at Mercury, to discuss the delicate balance of choosing your tech stack and the implications. That means explore the concept of the novelty budget or frequently known as "Choose Boring Technology". It emphasizes why companies should carefully spend their innovation tokens on things that actually move the needle, rather than reinventing the wheel. Mercury leverages simple technology like Postgres and EC2 instances alongside high-innovation bets like Haskell and Nix to maintain stability. The conversation unpacks the hidden complexities of over-relying on standard tools, sharing a cautionary tale about using a Postgres table as a massive queuing system until it consumed all the database resources and caused login failures. To solve architectural scaling without descending into nanoservice madness, we jump to discussing monolithic build systems. By leveraging hermetically sealed, modular build targets, teams can achieve massive parallelism and avoid endless local rebuilds while maintaining a single coherent view of the codebase. We also advocate for separating management tools from primary systems by utilizing dedicated control planes, and touch on the rising popularity of durable execution frameworks like Temporal to handle resilient workflows. And it turns out Ian might be a bigger advocate of microservices that he thought! 💡 Notable Links: Ian's blogBook: Blah Blah BlahUsing Innovation TokensNovelty budgetBuck2🎯 Picks: Warren - Why Archers Didn’t Volley FireIan - Band - Gloryhammer
Infrastructure as code: why you can never avoid thinking
Share Episode We explore the past and AI-driven future of Infrastructure as Code with Cloud Posse's Eric Osterman, discussing various IaC traumas. Erik maintains the world's largest repository of open-source IaC modules. Looking back at the dark ages of infrastructure, from the early days of raw CloudFormation and Capistrano to the rise and fall of tools like Puppet and Chef, we discuss the organic, messy growth of cloud environments. Where organizations frequently scale a single AWS account into a tangled web rather than adopting a robust multi-account architecture guided by a proper framework. The conversation then shifts to the modern era of rapid integration of infrastructure development. While generating IaC with large language models can be incredibly fast, it introduces severe risks if left unchecked, and we explore how organizations can protect themselves by relying on Architectural Decision Records (ADRs) and predefined "skills". The hopeful goal of ensuring autonomous deployments are compliant, reproducible, and secure instead of relying on hallucinated architecture. Finally, we tackle the compounding issue of code review in an age where developers can produce a year's worth of engineering slop progress in a single week. 💡 Notable Links: Atmos frameworkCheckov - IaC ValidationCode Rabbit✨ Episode: Agent Skills✨ Episode: All about MCPs🎯 Picks: Warren - Project Hail MaryErik - Everybody's free to wear sunscreen & Book: The 10X Rule
GPU versus CPU: What is engineering really doing for us
Share Episode We sit down with Jaikumar Ganesh, Head of Engineering at AnyScale, to explore the intricacies of heterogeneous compute. He unpacks the growing CPU/GPU divide, detailing how ML pipelines require precise orchestration — using CPUs for data reading and writing while leveraging expensive, massive-die GPUs for chunking and embedding. Warren brings the insight that, with AI agents rapidly changing how software is created, building is now a requirement of the business-focused team. And our guest shares how sales and marketing departments are increasingly using tools like Cursor and Claude to develop their own workflow automations. We discuss the challenges that this shift begs: what is engineering really doing for us? JK emphasizes that the core responsibility of the engineering organization is reliability. While anyone can generate code, running stable production software requires the deep "battle scars", robust observability, and meticulous release processes that only a dedicated engineering team can provide. That results in needing to find the right talent. But, finding the talent to maintain this critical infrastructure isn't easy, which is why JK advocates for highly creative hiring strategies. He shares incredible success stories of bypassing traditional recruiting by running hiring ads in foreign-language movies at local movie theaters and setting up booths at social food festivals to find uniquely qualified candidates. 🎯 Picks: Warren - Archer's Don't Fire VolleysJK - Book: The Explorer's Gene
Upskilling your agents
Share Episode In this adventure, we sit down with Dan Wahlin, Principal of DevRel for JavaScript, AI, and Cloud at Microsoft, to explore the complexities of modern infrastructure. We examine how cloud platforms like Azure function as "building blocks". Which of course, can quickly become overwhelming without the right instruction manuals. To bridge this gap, one potential solution we discuss is the emerging reliance on AI "skills"—specialized markdown files. They can give coding agents the exact knowledge needed to deploy poorly documented complex open-source projects to container apps without requiring deep infrastructure expertise. And we are saying the silent part outloud, as we review how handing the keys over to autonomous agents introduces terrifying new attack vectors. It's the security nightmare of prompt injections and the careless execution of unvetted AI skills. Which is a blast from the past, and we reminisce how current downloading of random agent instructions to running untrusted executables from early internet sites. While tools like OpenClaw purport to offer incredible automation, such as allowing agents to scour the internet and execute code without human oversight, it's already led us to disastrous leaks of API keys. We emphasize the critical necessity of validating skills through trusted repositories where even having agents perform security reviews on the code before execution is not enough. Finally, we tackle the philosophical debate around AI productivity and why Dorota's LLMs raise the floor and not the ceiling is so spot on. The standout pick requires mentioning, a fascinating 1983 paper titled "Ironies of Automation" by Lisanne Bainbridge. This paper perfectly predicts our current dilemma: automating systems often leaves the most complex, difficult tasks to human operators, proving that as automation scales, the need for rigorous human monitoring actually increases, destroying the very value that was attempting to be captured by the original innovation. 💡 Notable Links: Agent Skill MarketplaceAI Fatigue is realEpisode: Does Productivity even exist?🎯 Picks: Warren - Paper: Ironies of Automation (& AI)Dan - Tool: SkillShare
There's no way it's DNS...
Share Episode How much do you really know about the protocol that everything is built upon? This week, we go behind the scenes with Simone Carletti, a 13-year industry veteran and CTO at DNSimple, to explore the hidden complexities of DNS. We attempt to uncover why exactly DNS is often the last place developers check during an outage, drawing fascinating parallels between modern web framework abstractions and network-level opaqueness. Simone shares why his team relies on bare-metal machines instead of cloud providers to run their Erlang-based authoritative name servers, highlighting the critical need to control BGP routing. We trade incredible war stories, from Facebook locking themselves out of their own data centers due to a BGP error, to a massive 2014 DDoS attack that left DNSimple unable to access their own log aggregation service. The conversation also tackles the reality of implementing new standards like SVCB and HTTPS records, and why widespread DNSSEC adoption might require an industry-wide mandate. And of course we have the picks, but I'm not spoiling this weeks, just yet... 💡 Notable Links: Episode: IPv6SVCB + HTTPS DNS Resource Records RFC 9460Avian Carrier RFC 1149🎯 Picks: Warren - Book: One Second AfterSimone - Recommended Diving locations in Italy
Getting better at networking
Share Episode we are joined by Daan Boerlage, CTO at Mavexa as we tackle the long-awaited arrival of IPv6 in cloud infrastructure. Here, we highlight how migrating to an IPv6-native setup eliminates public/private subnet complexity and expensive NAT gateways natively. As well as entirely sidestepping the nightmare of IP collisions during VPC peering. Beyond the financial savings of ditching IPv4 charges, we explore the technical superiority of IPv6. Daan breaks down just how mind-bogglingly large the address space is, and focuses on how it solves serverless IP exhaustion while systematically debunking the pervasive myth that NAT is a security feature. We also discuss how IPv6's end-to-end connectivity, paving the way for next-generation protocols like QUIC, HTTP/3, and WebTransport. The episode rounds out with a cathartic venting session about legacy architecture, detailing a grueling nine-year migration away from a central shared database that ironically culminated in a move to Salesforce. Almost by design, Daan recommends his pick, praising its intuitive use of signals and fine-grained reactivity over React. And Warren's pick explores storing data in the internet itself by leveraging the dwell time of ICMP ping packets. 💡 Notable Links: FOSDEM talk on the internet of threadsHilbert Map of IPv6 address space🎯 Picks: Warren - Harder Drive: what we didn't want or needDaan - SolidJS
Varied Designer Does Vibecoding: Why testing always wins
Share Episode In this episode, we examine how the software industry is fundamentally changing. We're joined by our expert guest, Matt Edmunds, a long-time UX director, principal designer, and Principal UX Consultant at Tiny Pixls. The episode kicks, analyzing how early AI implementation in Applicant Tracking Systems (ATS) created rigid hiring processes that actively filter out the varied candidates who actually bring necessary diversity to engineering teams. Of course we get to the world of "vibe coding", and revisit the poor LLM usage highlighted in the DORA 2025 report, exploring how professionals without traditional software engineering backgrounds are leveraging models to generate functional code. Matt details his hands-on experience using the latest models of Claude Opus and Gemini Pro, successfully building low-level C virtual audio driver in 30 minutes drive by personal needs. We discuss the inherent challenges of large context windows, and coin the term "guest-driven development". To combat these hallucinations, Matt shares his strategy of using question-based prompting and anchoring the AI with comprehensive test files and documented schemas, which the models treat as an undeniable source of truth. Beyond the code, we look at the broader economic and physical limitations of the current AI boom, noting that AI providers are operating at massive financial losses while awaiting hardware efficiency improvements. 💡 Notable Links: Oatmeal on hating AI ArtEpisode: DORA 2025 Report🎯 Picks: Warren - Book: Start With WhyMatt - Book: Creativity, Inc.
DevOps trifecta: documentation, reliability, and feature flags
Share Episode We dive into the shifting landscape of developer relations and the new necessity of optimizing documentation for both humans and LLMs. Melinda Fekete joins from Unleash, and suggests transitioning to platform to help get this right by utilizing LLMs.txt files to cleanly expose content to AI models. The conversation then takes a look at the June GCP outage, which was triggered by a single IAM policy change. This illustrates that even with world-class CI/CD pipelines, deploying code using runtime controls such as feature flags is still risky. Feature flags can't even save GCP and other cloud providers, so what hope do the rest of us have. Finally, we discuss the practical implementation of these systems, advocating for "boring technology" like polling over streaming to ensure reliability, and conducting internal "breakathons" to test features before a full rollout. 💡 Notable Links: Diátaxis - Who is article this for?Fern - Docs PlatformEpisode: Latency is always more important than refreshnessEpisode: DORA 2025 Report🎯 Picks: Warren - Show: Bosch - LA Detective proceduralMelinda - Wavelength - Party Game
The Productivity Delusion: Gizmos, Resentment Metrics, and the Art of Deleting Code
Share Episode Dorota, CEO of Authress, returns to apply the US Supreme Court’s definition of obscenity to a scandalous topic: Engineering Productivity. In a world obsessed with AI-driven efficiency, Dorota and Warren argue that software development productivity has nothing to do with manufacturing "gizmos" and everything to do with feelings. They dismantle the factory-floor mentality that equates typing speed with value, suggesting instead that the most productive work often happens while staring out a train window or disassociating in the shower. >The conversation takes a dark turn into the reality of performance reviews. If productivity is subjective, how do you decide who gets promoted? Dorota proposes the "Resentment Metric"—ignoring Jira tickets in favor of figuring out who the team has secret concerns fo. They also roast the "100% utilization" fallacy, noting that a fully utilized highway is just a parking lot, and the same logic applies to engineering teams that don't schedule downtime for actual thinking. >Ultimately, they land on a definition of productivity that would make any optimizer proud: deleting things. If the best code is no code, then the most productive engineer is the one removing waste, deleting replicas, and emptying S3 buckets. The episode wraps up with a credit-card-sized transformer (it's a tripod) and a book recommendation on why your international colleagues might be misinterpreting your silence. >💡 Notable Links: DevOps Episode: DORA 2025 ReportResearch: Happy software developers solve problems better🎯 Picks: Warren - Book: The Culture MapDorota - GEOMETRICAL Pocket tripod