Practical articles on AI, DevOps, Cloud, Linux, and infrastructure engineering.
The observability market is huge and the pricing is a minefield. This is the map to the tools that matter, what each is best at, and how to avoid a runaway bill.
Every CI/CD platform claims to be fast and easy. The real differences are in pricing, self-hosting, and where each one falls apart at scale. This is the map.
Woodpecker forked Drone when the license changed. Here's how the two compare for small teams and homelabs that just want simple container-native CI.
Buildkite runs the control plane and lets you own the compute; Actions keeps everything close to your repo. Here's how they actually differ once you scale.
Teams spend most of their Kubernetes time debugging, not building. This is the map to the errors that eat that time: what each one means, how to diagnose it fast, and the fix.
Cloud bills grow quietly until someone asks why. This is the map for cutting spend without cutting reliability: where the money actually goes, the levers that work, and the tools worth paying for.
Both run pipelines as CRDs inside your cluster, but they were built for different jobs. Here's how Tekton and Argo Workflows actually differ in practice.
Datadog bills climb quietly until finance forwards the invoice. Here's the playbook we run to cut spend hard while keeping every signal that matters.
One tool is built to answer questions you didn't know you had. The other watches everything at once. Here is how they actually differ in practice.
The edge is fast because it's constrained. This is the decision map for what belongs at the edge, what belongs at origin, and how compute, data, caching, and auth fit together.
Your cloud bill says $80k. Your cluster says nothing about which team burned it. Here's how OpenCost, Kubecost, and Cast AI actually split that number.
The ordered kubectl toolkit we reach for when a pod misbehaves, with the five commands we run first and what each one actually tells you.
