Practical articles on AI, DevOps, Cloud, Linux, and infrastructure engineering.
You always have known vulnerabilities. The question is how you triage, patch, and respond. The discipline we run after a few real incidents and a lot of routine work.
Three terms that get mixed up constantly. The actual differences, where each one sits in the request path, when you reach for which, and where the same tool plays all three roles.
Helm gives you a lot of rope. The patterns we used that backfired, the ones we replaced them with, and what to skip if you're starting today.
We run three different job queue systems across our services. The patterns that work across all of them, the differences that matter, and the operational gotchas.
We adopted Backstage for service catalogs and templates. What works, what was over-engineered for our size, and what we'd do differently.
We run a chaos game day each quarter. The scenarios that surfaced real problems, the ones that didn't, and the operational discipline that makes the practice pay back.
Run your first three Kubernetes objects — Pod, Deployment, Service — on a local cluster, then understand why each one exists and how they fit together.
Walk through a working GitHub Actions workflow — install, test, build, deploy — for a tiny Node app. Every line explained.
Walk through your first Dockerfile, container run, and image push in 30 minutes. No theory dumps — just the commands and what each one is doing.
We use feature flags on roughly every customer-facing change. The provider tradeoff, the patterns that hold up, and the failure modes that show up only after a couple of years.
How we run OpenTelemetry across ~40 services. The instrumentation that earns its place, the patterns we abandoned, and what tracing actually catches that metrics don't.
Three layers of pooling, three different jobs. We learned the hard way which to use when. Real numbers from a 8k-connection workload.
