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Kliv in i en oändlig värld av stories

Lyssna när som helst, var som helst

Warren Parad

Will Button

Join us in listening to the experienced experts discuss cutting edge challenges in the world of DevOps. From applying the mindset at your company, to career growth and leadership challenges within engineering teams, and avoiding the common antipatterns. Every episode you'll meet a new industry veteran guest with their own unique story.

Adventures in DevOps

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 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 PlatformCloudFlare - Feature Flag causes outageAWS - Graceful degredationBuilding for 5 nines reliabilityEpisode: Latency is always more important than freshnessEpisode: DORA 2025 Report🎯 Picks:
 • Warren - 
Show: Bosch - LA Detective procedural • Melinda - 
Wavelength - Party Game

DevOps trifecta: documentation, reliability, and feature flags

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 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 Map • Dorota - 
GEOMETRICAL Pocket tripod

The Productivity Delusion: Gizmos, Resentment Metrics, and the Art of Deleting Code

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 Shoes • Paul - 
The Code Book

Project Yellow Brick Road: Creative, Practical, and Unconventional Engineering

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 "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 Window • Dorota - 
Mushroom Grow Kit

Special: The DORA 2025 Critical Review

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 Revolution • Sam - 
The 7 Laws of Identity • and 
Short Story: The Egg By Andy Weir

Browser Native Auth and FedCM is finally here!

In this episode, we sit down with Barzan Mozafari, MIT alum and University of Michigan professor, to explore how AI-driven automation is revolutionizing cloud database optimization. Barzan shares his experiences in bridging academia and industry, and how his work in AI-powered database tuning is reshaping cloud infrastructure efficiency.

We discuss the challenges of AI adoption in cloud computing, addressing concerns like implementation risks, security, and trust in autonomous agents. Barzan explains how machine learning models can optimize performance, reduce cloud costs, and automate database management, freeing engineers from tedious manual tuning.

Additionally, we explore the future of AI in database systems, the evolving landscape of public and private datasets, and what the next decade holds for data-driven automation. Whether you're a DevOps engineer or a database architect, this episode is packed with insights into the intersection of AI and cloud technology.

🎯 Picks:
 • Warren - 
L8 Conference 2024 (Warsaw) • Barzan - 
Book: Never Split the Difference by Chris Voss • Jillian - 
Infinity Nikki (Open-world dress-up game)

Optimizing Cloud Databases with novel algorithms

Will is absent this week due to an infrastructure issue, so Warren and Jillian take the reins in a fascinating discussion with Hikari Senju, founder of Omneky. Hikari shares how AI is revolutionizing ad technology by automatically generating creative assets tailored to different audiences and platforms. His insights reveal how businesses can scale their advertising while maintaining brand consistency and reducing content creation costs.

The conversation explores the balance between automation and human oversight, the ethical implications of AI-driven marketing, and how the ad personalization technology is evolving. Hikari also dives into the infrastructure behind Omneky, discussing cloud-based AI deployment, model selection, and strategies for ensuring ad content stays fresh and relevant. If you've ever wondered how AI is reshaping the future of advertising.

🎯 Picks:
 • Warren - 
Dune • Hikari - 
Accelerando • Jillian - 
Data Discovery with Dabble of DevOps AI

AI-Powered Ads: How digital marketing is transforming

Share Episode ⸺ Episode Sponsor: Incident.io - https://dev0ps.fyi/incidentio
 
 Elise, 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 Studies • Elise - 
Paper on Generative UI: LLMs are Effective UI Generators

Are we building the right thing?

Share Episode ⸺ Episode Sponsor: Incident.io - https://dev0ps.fyi/incidentio

Warren 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 9380 • Olga - 
Claude Code

Why Your Code Dies in Six Months: Automated Refactoring

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 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 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 everything • Fact - 
Don't outsource your customer support: Clorox sues CognizantCloudFlare uses an LLM to generate an OAuth2 Library🎯 Picks:
 • Warren - 
Rands Leadership Community • Meagan - 
The Manager's Path by Camille Fournier

DevOps trifecta: documentation, reliability, and feature flags

Lyssna när som helst, var som helst

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