Solving incidents with one-time ephemeral runbooks
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 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
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The IT Dictionary: Post-Mortems, Cargo Cults, and Dropped Databases
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 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
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Vector Databases Explained: From E-commerce Search to Molecule Research
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 FactsEpisode: MCP: The Model Context Protocol and Agent InteractionsCrossing the ChasmPicks:Warren - HanCenDa USB C Magnetic adapterJenna - Keychron Alice Layout Mechanical keyboard (And get a 5% discount on us)
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The Unspoken Challenges of Deploying to Customer Clouds
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 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
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How to build in Observability at Petabyte Scale
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 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
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.
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