Practical articles on AI, DevOps, Cloud, Linux, and infrastructure engineering.
We used to ship code and turn it on in the same breath, so every deploy was a bet. Feature flags split those two events apart and made rollbacks a config toggle.
We had the same 180-line build workflow copy-pasted into 60 repos. Fixing one bug meant 60 PRs. Here's the reusable-workflow setup that made it one.
We rotated a leaked AWS access key that a workflow had committed to logs. Switching GitHub Actions to OIDC federation meant no static AWS keys exist to leak in the first place.
Our M-series laptops built arm64, our CI built amd64, and prod pulled whichever tag won the race. Buildx and a manifest list ended the chaos.
A prompt tweak that helped one case quietly broke twenty others. Here's the CI eval harness we built so that never ships silently again.
After running both in production across a dozen clusters, here's where Flux and Argo CD actually differ and which one we'd reach for now.
State drift is silent until a deploy fails or an outage reveals it. The scheduled plan-and-diff pipeline that surfaces console hotfixes and manual edits while they're still cheap to reconcile.
Most CI caches either miss constantly or restore stale junk. The cache-key discipline, scope boundaries, and measurements that turned our pipeline cache from theatre into real minutes saved.
Production monitoring catches user-facing issues. CI failures stay invisible until someone notices the merge queue is stuck. The metrics and alerts that make pipelines observable.
SBOMs and signed attestations sound like checkboxes until you need to answer "did this artifact come from our pipeline?" The minimum viable supply-chain story we run.
Walk through a working GitHub Actions workflow — install, test, build, deploy — for a tiny Node app. Every line explained.
Three layers of pooling, three different jobs. We learned the hard way which to use when. Real numbers from a 8k-connection workload.
