DevOpsLinks

One end of the spectrum is pure human ops muscle: control rooms, runbooks, and the stuff that keeps live systems from face-planting on game day. The other end is agents rewriting the SDLC and Linux bugs that remind you the fundamentals still bite, so pick your comfort zone and then read the rest anyway.

🧠 How incidents can teach us about what’s already working well
📺 The Human Infrastructure: How Netflix Built the Operations Layer Behind Live at Scale
🚨 The most severe Linux threat to surface in years catches the world flat-footed
📉 The Silent Failure of Reliability Metrics at Scale: Lessons Learned from a Decade of Broken Metrics
🔁 The Software Development Lifecycle Is Dead
🤖 Ubuntu's Next Chapter: Local AI, Confined Agents, and a Bet Against the Cloud-First OS

Ship less mystery, leave more artifacts.

Happy coding!
FAUN.dev() Team

Join IaCConf 2026 to learn how top IaC leaders from companies like Google, Sanofi, and AHEAD are solving the hardest problems in cloud provisioning, state management, and platform engineering.

May 14. Free to attend. Register now.

Learn how to build intelligent, scalable platforms with AI — from self-service developer portals to AI-driven observability. This hands-on cohort equips engineers, SREs, and tech leaders with real-world frameworks to design smarter platforms and boost developer productivity

Register here.

Ubuntu makes local inference a native capability with inference snaps. It delivers silicon-optimized model bits under snap confinement.

It ships implicit AI: first-class speech-to-text/TTS and opt-in agentic workflows for desktop and server automation.

Canonical favors open-weight models, exposes read-only analysis, enforces scoped action permissions, records full audit trails, and builds silicon partnerships.

Are Your APIs Ready for AI Agents? A Hands-on Workshop on May 23rd

AI agents are beginning to autonomously call APIs, chain services, and create integrations that most platforms were never designed to handle. This hands-on masterclass on Designing AI-ready APIs helps architects and developers build governed, predictable API ecosystems using OpenAPI, Overlay, and Arazzo.

Learn how to add guardrails, improve discoverability, and safely evolve existing APIs for automated consumption.

FAUN.dev readers get an exclusive 40% discount using code FAUN40.

Cloud Native CI/CD with GitLab: From Commit to Production Ready is a complete, hands-on path to becoming the person on your team who actually understands GitLab CI/CD, not just the YAML, but the architecture underneath.

You'll start with the fundamentals: jobs, stages, the container registry, your first working pipeline; and build up to the parts most engineers learn the hard way in production: reusable definitions with extends and includes, DAGs for non-sequential execution, artifact strategies, conditional logic and workflow rules, parallelism and matrix builds, runner and executor internals, and cloud-native runners on Kubernetes - with caching, autoscaling, and observability wired in. The final chapters walk through multi-stage continuous deployment with HelmandKubernetes end to end.

23 chapters. Hands-on throughout. Designed so beginners can follow it linearly and experienced engineers can jump straight to the chapter they need.

Written by Aymen El Amri - founder of FAUN.dev(), author of multiple cloud-native engineering books, and trainer to thousands of DevOps and platform engineers worldwide.

→ Explore the course

Publicly released exploit code for a critical privilege escalation vulnerability in Linux, known as CopyFail (CVE-2026-31431), allows attackers to gain root access across all vulnerable distributions with a single piece of code. The researchers from Theori disclosed the vulnerability 5 weeks after notifying the Linux kernel security team, who patched it in several versions, but many distributions had not yet incorporated the fixes at the time of disclosure. The exploit poses a serious threat to data centers and personal devices, enabling attackers to compromise systems and containers.

A famous optical illusion developed by Edward H. Adelson shows that two squares, despite appearing different in shade, are actually the same gray. This illusion demonstrates how the brain processes light, shadow, and objects when interpreting visual signals from the optic nerve. Studying such illusions can provide insight into how the visual system normally functions, just as analyzing incidents can help identify how systems typically succeed.

Netflix has massively scaled its live content, now streaming over nine shows per day with up to 17.9M peak viewers per game, thanks to a complex Broadcast Operations Center, strict transmission quality standards, and a tiered human operations model, including specialized engineering teams and dedicated Control Operators.

At scale, observability breaks when SLIs and metrics mix different behaviors and lose clear meaning.
Complexity grows: more event types, extra labels, and rising cardinality. That bloats queries, slows evaluation pipelines, and distorts Prometheus, PromQL, and Elastic metrics.

Why this matters: Teams must treat metrics like paid resources. Constrain index scopes. Curb label cardinality. Preserve SLI semantics.

AI agents collapse the classic SDLC - requirements, design, implementation, testing, review, deployment - into an intent-driven loop. They generate code, tests, and pipelines together. They commit to main. Automated verification runs. Deployment and release split with feature flags.

Graphs that teach > graphs that impress. Turn any code, or knowledge base (Karpathy LLM wiki), into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.

The Zero-Server Code Intelligence Engine - GitNexus is a client-side knowledge graph creator that runs entirely in your browser. Drop in a repo or ZIP file, and get an interactive knowledge graph wit a built in Graph RAG Agent. Perfect for code exploration

Utilyze measures how efficiently your GPU is doing useful work, not just whether it's busy. It runs live against your workload with negligible overhead.

 Windows pod system for Linux

Faultline is a deterministic CLI for CI failure diagnosis

Did you know that Kubernetes can show you "time travel" behavior, where a client sees an older object state after a newer one, even when etcd is perfectly consistent? The reason is that the API server serves most reads from an in-memory watch cache, and in HA setups a freshly started or lagging API server can have a watch cache behind etcd's actual state, so an informer that relists against it can go backwards in resourceVersion. That is why client-go informers rely on list then watch with strict resourceVersion tracking, and why the newer WatchList mechanism was added: to keep informers from time traveling when they reconnect to a different API server instance.

"DevOps promised speed, so we automated the path to production and made mistakes arrive faster too. SRE promised reliability, so we built feedback loops that keep us honest about what we actually run. Cloud promised elasticity, and delivered a monthly reminder that every abstraction eventually gets a bill."

— SenseiOne

You're the person who can fix anything in the cluster at 2am, and every incident reinforces it. The tribal knowledge premium feels like seniority now, but in 18 months it's the reason you can't get promoted, can't take a real vacation, and watch platform engineers with worse instincts get the architect role because their work left artifacts and yours left Slack threads.