Practical articles on AI, DevOps, Cloud, Linux, and infrastructure engineering.
A production-focused guide to Azure DevOps: standardized YAML templates, secure service connections, rollout safety, and measurable delivery reliability.
A practical production playbook for AI systems: evaluation gates, guardrails, observability, cost control, and reliable release management.
A practical field manual for engineering teams who want AI features that survive real users, incidents, and budgets — not just demo day.
Defining monitoring as code: dashboards, alerts, and SLOs in Git. The patterns that survived the migration from clicked-together monitoring.
K8s Secrets are barely encrypted. We moved every secret to Vault with the Vault Agent injector and never went back. The setup checklist.
We test infrastructure code with three layers: validation, plan review, and integration tests. The setup that catches real bugs without slowing down PRs.
We have a few hundred shell scripts in production. The patterns that make them survive contact with reality, and the ones we've stopped writing.
Filesystem choice, mount options, IO schedulers — the per-host tweaks that actually moved disk performance for our database and storage workloads.
How processes actually live and die on Linux, the tools that show what's happening, and the patterns we use for monitoring service health.
A practical Linux hardening checklist for production hosts. The settings that earn their place via real production reasons, not the cargo-cult version.
A systematic approach to debugging Linux network issues. The tools that earn their place and the order I use them in.
A practical Linux performance tuning playbook for production servers. The kernel parameters, disk and network tweaks that earn their place, and the ones that turned out to be folklore.
