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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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
Project Yellow Brick Road: Creative, Practical, and Unconventional Engineering
Share Episode ⸺ Episode Sponsor: Rootly AI - https://dev0ps.fyi/rootlyai Paul Conroy, CTO at Square1, joins the show to prove that the best defense against malicious bots isn't always a firewall—sometimes, it’s creative data poisoning. Paul recounts a legendary story from the Irish property market where a well-funded competitor attempted to solve their "chicken and egg" problem by scraping his company's listings. Instead of waiting years for lawyers, Paul’s team fed the scrapers "Project Yellow Brick Road": fake listings that placed the British Prime Minister at 10 Downing Street in Dublin and the White House in County Cork. The result? The competitor’s site went viral for all the wrong reasons, forcing them to burn resources manually filtering junk until they eventually gave up and targeted someone else. >We also dive into the high-stakes world of election coverage, where Paul had three weeks to build a "coalition builder" tool for a national election. The solution wasn't a complex microservice architecture, but a humble Google Sheet wrapped in a Cloudflare Worker. Paul explains how they mitigated Google's rate limits and cold start times by putting a heavy cache in front of the sheet, leading to a crucial lesson in pragmatism: data that is "one minute stale" is perfectly acceptable if it saves the engineering team from building a complex invalidation strategy. Practically wins. >Finally, the conversation turns to the one thing that causes more sleepless nights than malicious scrapers: caching layers. Paul and the host commiserate over the "turtles all the way down" nature of modern caching, where a single misconfiguration can lead to a news site accidentally attaching a marathon runner’s photo to a crime story. They wrap up with picks, including a history of cryptography that features the Pope breaking Spanish codes and a defense of North Face hiking boots that might just be "glamping" gear in disguise. >🎯 Picks: Warren - The North Face Hedgehog Gore-tex Hiking ShoesPaul - The Code Book
Special: The DORA 2025 Critical Review
Share Episode "Those memes are not going to make themselves." >Dorota, CEO of Authress, joins us to roast the 2025 DORA Report, which she argues has replaced hard data with an AI-generated narrative. From the confusing disconnect between feeling productive and actually shipping code to the grim reality of a 30% acceptance rate, Warren and Dorota break down why this year's report smells a lot like manure. >We dissect the massive 142-page 2025 DORA Report. Dorota argues that the report, which is now rebranded as the "State of AI-Assisted Software Development", feels less like a scientific study of DevOps performance and more like a narrative written by an intern using an LLM prompt. The duo investigates the "stubborn results" where AI apparently makes everyone feel like a 10x developer, where the hard results tell a different story. AI actually increases software and product instability — failing to improve. >The conversation gets spicy as they debate the "pit of failure" that is feature flags (often used as a crutch for untested code) and the embarrassing reality that GitHub celebrates a mere 30% code acceptance rate as a "success." Dorota suggests that while AI raises the floor for average work, it completely fails when you need to solve complex problems or, you know, actually collaborate with another human being. >In a vivid analogy, Dorota compares reading this year's report to the Swiss Spring phenomenon — the time of year when farmers spray manure, leaving the beautiful landscape smelling...unique. The episode wraps up with a reality check on the physical limits of LLM context windows (more tokens, more problems) and a strong recommendation to ignore the AI hype cycle in favor of a much faster-growing organism: a kitchen countertop oyster mushroom kit. >💡 Notable Links: AI as an amplifier truism fallacyDORA 2025 ReportDevOps Episode: VS Code & GitHub CopilotWhere is the deluge of new software - Impact of AI on software productsImpact of AI on Critical Thinking🎯 Picks: Warren - The Maximum Effective Context WindowDorota - Mushroom Grow Kit
Browser Native Auth and FedCM is finally here!
Share Episode ⸺ Episode Sponsor: Incident.io - https://dev0ps.fyi/incidentio "My biggest legacy at Google is the amount of systems I broke." — Sam Goto joins the show with a name that strikes fear into engineering systems everywhere. As a Senior Staff Engineer on the Chrome team, Sam shares the hilarious reality of having the last name "Goto," which once took down Google's internal URL shortener for four hours simply because he plugged in a new computer. >Sam gets us up to speed with Federated Credentials Management (FedCM), as we dive deep into why authentication has been built despite the browser rather than with it, and why it’s time to move identity from "user-land" to "kernel-land". This shift allows for critical UX improvements for logging in all users irrespective of what login providers you use, finally addressing the "NASCAR flag" problem of infinite login lists. >Most importantly, he shares why you don't need to change your technology stack to get all the benefits of FedCM. Finally, Sam details the "self-sustaining flame" strategy (as opposed to an ecosystem "flamethrower"), revealing how they utilized JavaScript SDKs to migrate massive platforms like Shopify and 50% of the web's login traffic without requiring application developers to rewrite their code. >💡 Notable Links: HSMs + TPM in production environmentsGet involved: FedCM W3C WGThe FedCM spec GitHub repoTPAC Browser Conference🎯 Picks: Warren - Book: The Platform RevolutionSam - The 7 Laws of Identity and Short Story: The Egg By Andy Weir
Are we building the right thing?
Share Episode ⸺ Episode Sponsor: Incident.io - https://dev0ps.fyi/incidentioElise, VP and Head of UX at Unleash, joins us to talk all about UX. Self identifying as probably "The annoying lady in the room" and a career spanning nearly 30 years—starting before "UX" was even a job title — joins us to dismantle the idea that User Experience is just about moving pixels around. Here we debate the friction between engineering, sales, and the customer. We get to the bottom of whether or avoiding end-user interaction, understand, and research is a career-limiting move for staff+ engineers. Or should you avoid forcing a world-class developer to facilitate a call with a non-technical user if it makes them uncomfortable?Warren calls out the "Pit of Failure" often faced by teams as they seek to introduce feature flags. They can become a crutch, leading teams to push untested code into production simply because they can toggle it off—a scenario he calls the "pit of failure".And Elise dives into a great story recounting her consulting days where a company spent a fortune on a branding agency that demanded conflicting "primary colors" for a mainframe application used 8 hours a day. Her low-tech solution to prove them wrong? Listen and find out, this episode is all about bringing UX to Engineering.💡 Notable Links:Ladder of Leadership - Book: Turn the Ship Around!🎯 Picks:Warren - Growth.Design Case StudiesElise - Paper on Generative UI: LLMs are Effective UI Generators
Why Your Code Dies in Six Months: Automated Refactoring
Share Episode ⸺ Episode Sponsor: Incident.io - https://dev0ps.fyi/incidentioWarren is joined by Olga Kundzich, Co-founder and CTO of Moderne, to discuss the reality of technical debt in modern software engineering. Olga reveals a shocking statistic: without maintenance, cloud-native applications often cease to function within just six months. And from our experience, that's actually optimistic. The rapid decay isn't always due to bad code choices, but rather the shifting sands of third-party dependencies, which make up 80 to 90% of cloud-native environments.We review the limitations of traditional Abstract Syntax Trees (ASTs) and the introduction of OpenRewrite's Lossless Semantic Trees (LSTs). Unlike standard tools, LSTs preserve formatting and style, allowing for automated, horizontal scaling of code maintenance across millions of lines of code. This fits perfectly in to the toolchain that is the LLMs and open source ecosystem. Olga explains how this technology enables enterprises to migrate frameworks—like moving from Spring Boot 1 to 2 — without dedicating entire years to manual updates.Finally, they explore the intersection of AI and code maintenance, noting that while LLMs are great at generating code, they often struggle with refactoring and optimizing existing codebases. We highlight that agents are not yet fully autonomous and will always require "right-sized" data to function effectively. Will is absent for this episode, leaving Warren to navigate the complexities of mass-scale code remediation solo.💡 Notable Links:DevOps Episode: We read codeDevOps Episode: Dynamic PRs from incidentsOpenRewriteLarger Context Windows are not better🎯 Picks:Warren - Dell XPS 13 9380Olga - Claude Code
AI, IDEs, Copilot & Critical Thinking
Share EpisodeMicrosoft's John Papa, Partner General Manager of Developer Relations for all things dev and code joins the show to talk developer relations...from his Mac. He reveals his small part in the birth of VS Code (back when its codename was Ticino) after he spent a year trying a new editor every month.The conversation dives deep into "Agentic AI," where John predicts developers will soon become "managers of agents". But is it all hype? John and Warren debate the risks of too much automation (no, AI should not auto-merge your PRs) and the terrifying story of a SaaS built with "zero handwritten code" that immediately got hacked because the founder was "not technical".The episode highlights John's jaw-dropping war stories from Disney, including a mission-critical hotel lock system (for 5,000+ rooms) that was running on a single MS Access database under a desk. It’s a perfect, cringeworthy lesson in why "we don't have time to test" is the most expensive phrase in tech, and why we need a human in the loop. John leaves us with the one question we must ask of all new AI features: "Who asked for that?"Notable FactsImpact of AI on Critical Thinking paperLLMs raise the floor not the ceilingDevOps Episode: How far along with AI are we?Picks:Warren - Shokz OpenFit 2John - Run Disney
Solving incidents with one-time ephemeral runbooks
Episode Sponsor: Attribute - https://dev0ps.fyi/attributeIn this episode, we're joined by Lawrence Jones, Founding Engineer at Incident.io. The conversation focuses on the challenges of managing incidents in highly regulated environments like FinTech, where the penalties for downtime are harsh and require a high level of rigor and discipline in the response process. Lawrence details the company's evolution, from running a monolithic Go binary on Heroku to moving to a more secure, robust setup in GCP, prioritizing the use of native security primitives like GCP Secret Manager and Kubernetes to meet the obligations of their growing customer base.We spotlight exactly how a system can crawl GitHub pull requests, Slack channels, telemetry data, and past incident post-mortems to dynamically generate an ephemeral runbook for the current incident.Also discussed are the technical challenges of using RAG (Retrieval-Augmented Generation), noting that they rely heavily on pre-processing data with tags and a service catalog rather than relying solely on less consistent vector embeddings to ensure fast, accurate search results during a crisis.Finally, Lawrence stresses that frontier models are no longer the limiting factor in building these complex systems; rather, success hinges on building structured, modular systems, and doing the hard work of defining objective metrics for improvement.Notable FactsCloud Secrets management at scaleEpisode: Solving Time Travel in RAG DatabasesEpisode: Does RAG Replace keyword search?Picks:Warren - Anker Adpatable Wall-Charger - PowerPort Atom IIILawrence - Rocktopus & The Checklist Manifesto
The IT Dictionary: Post-Mortems, Cargo Cults, and Dropped Databases
Episode Sponsor: Attribute - https://dev0ps.fyi/attributeWe're joined by 20 year industry veteran and DevOps advocate, Adam Korga, celebrating the release of his book IT Dictionary. In this episode we quickly get down to the inspiration behind postmortems as we review some cornerstone cases both in software and in general technology.Adam shares how he started in the industry, long before DevOps was a coined term, focused on making systems safer and avoiding mistakes like accidentally dropping a production database. we review the infamous incidents of accidental database deletion, by LLMs and human's alike.And of course we touch on the quintessential postmortems in civil engineering, flight, and survivorship bias from World War II through analyzing bullet holes on returning planes.Notable FactsAdam's book: IT DictionaryKnight Capital: the 45 minute nightmareWork Chronicles Comic: Will my architecture work for 1 Million users?Picks:Warren - Cuitisan CANDL storage containersAdam - FUBAR
Vector Databases Explained: From E-commerce Search to Molecule Research
Jenna Pederson, Staff Developer Relations at Pinecone, joins us to close the loop on Vector Databases. Demystifies how they power semantic search, their role in RAG, and also unexpected applications.Jenna takes us beyond the buzzword bingo, explaining how vector databases are the secret sauce behind semantic search. Sharing just how "red shirt" gets converted into a query that returns things semantically similar. It's all about turning your data into high-dimensional numerical meaning, which, as Jenna clarifies, is powered by some seriously clever math to find those "closest neighbors."The conversation inevitably veers into Retrieval-Augmented Generation (RAG). Jenna reveals how databases are the unsung heroes giving LLMs real brains (and up-to-date info) when they’re prone to hallucinating or just don’t know your company’s secrets. They complete the connection from proprietary and generalist foundational models to business relevant answers.Notable FactsEpisode: MCP: The Model Context Protocol and Agent InteractionsCrossing the ChasmPicks:Warren - HanCenDa USB C Magnetic adapterJenna - Keychron Alice Layout Mechanical keyboard
The Unspoken Challenges of Deploying to Customer Clouds
This episode we are joined by Andrew Moreland, co-founder of Chalk. Andrew explains how their company’s core business model is to deploy their software directly into their customers’ cloud environments. This decision was driven by the need to handle highly sensitive data, like PII and financial records, that customers don't want to hand over to a third-party startup. The conversation delves into the surprising and complex challenges of this approach, which include managing granular IAM permissions and dealing with hidden global policies that can block their application. Andrew and Warren also discuss the real-world network congestion issues that affect cross-cloud traffic, a problem they've encountered multiple times. Andrew shares Chalk's mature philosophy on software releases, where they prioritize backwards compatibility to prevent customer churn, which is a key learning from a competitor.Finally, the episode explores the advanced technical solutions Chalk has built, such as their unique approach to "bitemporal modeling" to prevent training bias in machine learning datasets. As well as, the decision to move from Python to C++ and Rust for performance, using a symbolic interpreter to execute customer code written in Python without a Python runtime. The episode concludes with picks, including a surprisingly popular hobby and a unique take on high-quality chocolate.Notable FactsFact - The $1M hidden Kubernetes spendGiraffe and Medical Ruler training data biasSOLID principles don't produce better code?Veritasium - The Hole at the Bottom of MathEpisode: Auth Showdown on backwards compatible changesPicks:Warren - Switzerland Grocery Store ChocolateAndrew - Trek E-Bikes
How to build in Observability at Petabyte Scale
We welcome guest Ang Li and dive into the immense challenge of observability at scale, where some customers are generating petabytes of data per day. Ang explains that instead of building a database from scratch—a decision he says went "against all the instincts" of a founding engineer—Observe chose to build its platform on top of Snowflake, leveraging its separation of compute and storage on EC2 and S3.The discussion delves into the technical stack and architectural decisions, including the use of Kafka to absorb large bursts of incoming customer data and smooth it out for Snowflake's batch-based engine. Ang notes this choice was also strategic for avoiding tight coupling with a single cloud provider like AWS Kinesis, which would hinder future multi-cloud deployments on GCP or Azure. The discussion also covers their unique pricing model, which avoids surprising customers with high bills by providing a lower cost for data ingestion and then using a usage-based model for queries. This is contrasted with Warren's experience with his company's user-based pricing, which can lead to negative customer experiences when limits are exceeded.The episode also explores Observe’s "love-hate relationship" with Snowflake, as Observe's usage accounts for over 2% of Snowflake's compute, which has helped them discover a lot of bugs but also caused sleepless nights for Snowflake's on-call engineers. Ang discusses hedging their bets for the future by leveraging open data formats like Iceberg, which can be stored directly in customer S3 buckets to enable true data ownership and portability. The episode concludes with a deep dive into the security challenges of providing multi-account access to customer data using IAM trust policies, and a look at the personal picks from the hosts.Notable LinksFact - Passkeys: Phishing on Google's own domain and It isn't even newEpisode: All About OTELEpisode: Self Healing SystemsPicks:Warren - The Shadow (1994 film)Ang - Xreal Pro AR Glasses
The Open-Source Product Leader Challenge: Navigating Community, Code, and Collaboration Chaos
In a special solo flight, Warren welcomes Meagan Cojocar, General Manager at Pulumi and a self-proclaimed graduate of “PM school” at AWS. They dive into what it’s like to own an entire product line and why giving up that startup hustle for the big leagues sometimes means you miss the direct signal from your users. The conversation goes deep on the paradox of open-source where direct feedback is gold, but dealing with license-shifting competitors can make you wary. From the notorious HashiCorp kerfuffle to the rise of OpenTofu, they explore how Pulumi maintains its commitment to the community amidst a wave of customer distrust.Meagan highlights the invaluable feedback loop provided by the community, allowing for direct interaction between users and the engineering team. This contrasts with the "telephone game" that can happen in proprietary product development. The conversation also addresses the recent industry shift and then immediate back-peddling from open-source licenses, discussing the subsequent customer distrust and how Pulumi maintains its commitment to the open-source model.And finally, the duo tackles the elephant in the cloud: LLMs, and extends on the early MCP episode. They debate the great code quality vs. speed trade-off, the risk of a "botched" infrastructure deployment, and whether these models can solve anything more than a glorified statistical guessing game. It's a candid look at the future of DevOps, where the real chaos isn't the code, but the tools that write it. The conversation concludes with a philosophical debate on the fundamental capabilities of LLMs, questioning whether they can truly solve "hard problems" or are merely powerful statistical next-word predictors.Notable FactsVeritasium - the Math that predicts everythingFact - Don't outsource your customer support: Clorox sues CognizantCloudFlare uses an LLM to generate an OAuth2 LibraryPicks:Warren - Rands Leadership CommunityMeagan - The Manager's Path by Camille Fournier
The Open-Source Product Leader Challenge: Navigating Community, Code, and Collaboration Chaos
Share EpisodeIn a special solo flight, Warren welcomes Meagan Cojocar, General Manager at Pulumi and a self-proclaimed graduate of “PM school” at AWS. They dive into what it’s like to own an entire product line and why giving up that startup hustle for the big leagues sometimes means you miss the direct signal from your users. The conversation goes deep on the paradox of open-source where direct feedback is gold, but dealing with license-shifting competitors can make you wary. From the notorious HashiCorp kerfuffle to the rise of OpenTofu, they explore how Pulumi maintains its commitment to the community amidst a wave of customer distrust.Meagan highlights the invaluable feedback loop provided by the community, allowing for direct interaction between users and the engineering team. This contrasts with the "telephone game" that can happen in proprietary product development. The conversation also addresses the recent industry shift and then immediate back-peddling from open-source licenses, discussing the subsequent customer distrust and how Pulumi maintains its commitment to the open-source model.And finally, the duo tackles the elephant in the cloud: LLMs, and extends on the earlier MCP episode. They debate the great code quality vs. speed trade-off, the risk of a "botched" infrastructure deployment, and whether these models can solve anything more than a glorified statistical guessing game. It's a candid look at the future of DevOps, where the real chaos isn't the code, but the tools that write it. The conversation concludes with a philosophical debate on the fundamental capabilities of LLMs, questioning whether they can truly solve "hard problems" or are merely powerful statistical next-word predictors.Notable Links:Veritasium - the Math that predicts everythingFact - Don't outsource your customer support: Clorox sues CognizantCloudFlare uses an LLM to generate an OAuth2 LibraryPicks::Warren - Rands Leadership CommunityMeagan - The Manager's Path by Camille Fournier
FinOps: Holding engineering teams accountable for spend
In this episode of Adventures in DevOps, we dive into the world of FinOps, a concept that aims to apply the DevOps mindset to financial accountability. Yasmin Rajabi, Chief Strategy Officer at CloudBolt, joins us to demystify, as we acknowledge the critical challenge of bringing together financial accountability and engineering teams who often are not paying attention to the business.The discussion further explores the practicalities of FinOps in the context of cloud spending and Kubernetes. Yasmin highlights that a significant amount of waste in organizations comes from simply not turning off unused systems and not right-sizing resources. She explains how tools like Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) can help, but also points out the complexities of optimizing across horizontal and vertical scaling behaviors. The conversation touches on "shame back reporting" as a way to provide visibility into costs for engineering teams, although the conversation emphasizes that providing tooling and insights is more effective than simply telling developers to change configurations.The episode also delves into the evolving mindset around cloud costs, especially with the rise of AI and machine learning workloads. While historically engineering salaries eclipsed cloud spending, the increasing hardware requirements for ML and data workloads are making cost optimization a more pressing concern. Spending-conscious teams are increasingly asking about GPU optimization, even if AI/ML teams are still largely focused on limitless spending to drive unjustified "innovation". The conclude by discussing the challenges of on-premise versus cloud deployments and the importance of addressing "day two problems" regardless of the infrastructure choice.PicksWarren - Lions and Dolphins cannot make babiesAimee - The Equip Protein Powder and Protein BarYasmin - Bone Broth drink by 1990 Snacks