Adventures in DevOps

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

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 "guess-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.

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 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 proceduralMelinda - Wavelength - Party Game

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

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

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

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

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 StudiesElise - Paper on Generative UI: LLMs are Effective UI Generators

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

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 Links:Impact 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

Share Episode ⸺ Episode Sponsor: Attribute - https://dev0ps.fyi/attributeIn the wake of one of the worst AWS incidents in history, 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 Links:Cloud 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

Share Episode ⸺ 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 Links:Adam'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

Share Episode ⸺ Episode Sponsor: Attribute - https://dev0ps.fyi/attributeJenna 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 Links:Episode: MCP: The Model Context Protocol and Agent InteractionsCrossing the Chasm🎯 Picks:Warren - HanCenDa USB C Magnetic adapterJenna - Keychron Alice Layout Mechanical keyboard (And get a 5% discount on us)

Share EpisodeThis 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 Links:Fact - 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 changes🎯 Picks:Warren - Switzerland Grocery Store ChocolateAndrew - Trek E-Bikes

Share EpisodeWe 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 Links:Fact - Passkeys: Phishing on Google's own domain and It isn't even newEpisode: All About OTELEpisode: Self Healing Systems🎯 Picks:Warren - The Shadow (1994 film)Ang - XREAL Pro AR Glasses

Share Episode                  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 everythingFact - Don't outsource your customer support: Clorox sues CognizantCloudFlare uses an LLM to generate an OAuth2 Library🎯 Picks:         Warren - Rands Leadership CommunityMeagan - The Manager's Path by Camille Fournier

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

Get ready for a lively debate on this episode of Adventures in DevOps. We're joined by Brian Pontarelli, founder of FusionAuth and CleanSpeak. Warren and Brian face off by diving into the controversial topic of multitenant versus single-tenant architecture. Expert co-host Aimee Knight joins to moderate the discussion. Ever wondered how someone becomes an "auth expert"? Warren spills the beans on his journey, explaining it's less about a direct path and more about figuring out what it means for yourself. Brian chimes in with his own "random chance" story, revealing how they fell into it after their forum-based product didn't pan out.Aimee confesses her "alarm bells" start ringing whenever multitenant architecture is mentioned, jokingly demanding "details" and admitting her preference for more separation when it comes to reliability. Brian makes a compelling case for his company's chosen path, explaining how their high-performance, downloadable single-tenant profanity filter, CleanSpeak, handles billions of chat messages a month with extreme low latency. This architectural choice became a competitive advantage, attracting companies that couldn't use cloud-based multitenant competitors due to their need to run solutions in their own data centers.We critique cloud providers' tendency to push users towards their most profitable services, citing AWS Cognito as an example of a cost-effective solution for small-scale use that becomes cost-prohibitive with scaling and feature enablement. The challenges of integrating with Cognito, including its reliance on numerous other AWS services and the need for custom Lambda functions for configuration, are also a point of contention. The conversation extends to the frustrations of managing upgrades and breaking changes in both multitenant and single-tenant systems and the inherent difficulties of ensuring compatibility across different software versions and integrations. The episode concludes with a humorous take on the current state and perceived limitations of AI in software development, particularly concerning security.PicksWarren - Scarpa Hiking shoes - Planet Mojito SuadeAimee - Peloton TreadBrian - Searchcraft and Fight or Flight

Episode Sponsor: PagerDuty - Checkout the features in their official feature release: https://fnf.dev/4dYQ7gLThis episode dives into a fundamental question facing the DevOps world: Did Kubernetes truly win the infrastructure race because it was the best technology, or were there other, perhaps less obvious, factors at play? Omer Hamerman joins Will and Warren to take a hard look at it. Despite the rise of serverless solutions promising to abstract away infrastructure management, Omer shares that Kubernetes has seen a surge in adoption, with potentially 70-75% of corporations now using or migrating to it. We explore the theory that human nature's preference for incremental "step changes" (Kaizen) over disruptive "giant leaps" (Kaikaku) might explain why a solution perceived by some as "worse" or more complex has gained such widespread traction.The discussion unpacks the undeniable strengths of Kubernetes, including its "thriving community", its remarkable extensibility through APIs, and how it inadvertently created "job security" for engineers who "nerd out" on its intricacies. We also challenge the narrative by examining why serverless options like AWS Fargate could often be a more efficient and less burdensome choice for many organizations, especially those not requiring deep control or specialized hardware like GPUs. The conversation highlights that the perceived "need" for Kubernetes' emerges often from something other than technical superiority.Finally, we consider the disruptive influence of AI and "vibe coding" on this landscape, how could we not? As LLMs are adopted to "accelerate development", they tend to favor serverless deployment models, implicitly suggesting that for rapid product creation, Kubernetes might not be the optimal fit. This shift raises crucial questions about the trade-offs between development speed and code quality, the evolving role of software engineers towards code review, and the long-term maintainability of AI-generated code. We close by pondering the broader societal and environmental implications of these technological shifts, including AI's massive energy consumption and the ongoing debate about centralizing versus decentralizing infrastructure for efficiency.Links:​Comparison: Linux versus E. coliPicks​Warren - Surveys are great, and also fill in the Podcast SurveyWill - Katana.networkOmer - Mobland and JJ (Jujutsu)

In this episode, Aimee Knight, an expert in Site Reliability Engineering (SRE) whose experience hails from Paramount and NPM, joins the podcast to discuss her journey into SRE, the challenges she faced, and the strategies she employed to succeed. Aimee shares her transition from a non-traditional background in JavaScript development to SRE, highlighting the importance of understanding both the programming and infrastructure sides of engineering. She also delves into the complexities of SRE at different scales, the role of playbooks in incident management, and the balance between speed and quality in software development.Aimee discusses the impact of AI and machine learning on SRE, emphasizing the need for responsible use of these tools. She touches on the importance of understanding business needs and how it affects decision-making in SRE roles. The conversation also covers the trade-offs in system design, the challenges of scaling applications, and the importance of resilience in distributed systems. Aimee provides valuable insights into the pros and cons of a career in SRE, including the importance of self-care and the satisfaction of mentoring others.The episode concludes with us discussing some of the hard problems such as the on-call burden for large teams, and the technical expertise an org needs to maintain higher complexity systems. Is the average tenure in tech decreasing, we discuss it and do a deep dive on the consequences in the SRE world.Picks​The Adventures In DevOps: SurveyWarren's Technical BlogWarren: The Fifth Discipline by Peter SengeAimee: Sleep Token (Band) - Caramel, GraniteWill: The Bear Grylls Celebrity Hunt on NetflixJillian: Horizon Zero Dawn Video Game