Practical articles on AI, DevOps, Cloud, Linux, and infrastructure engineering.
We run both ECS and EKS in production. Which we use for what, and the actual decision criteria — not the marketing comparison.
A working AWS security baseline, derived from the actual incidents we've had and the audit findings we've cleared.
We use serverless for specific patterns, not as a default. The patterns where it shines, the ones it doesn't, and the gotchas at production scale.
Building visibility into cloud costs that actually drives action. The dashboards we look at, the alerts that fire, and the queries we run.
We run our app in two AWS regions for failover. The hard parts aren't the deployment — they're data consistency, traffic shifting, and the assumptions that break when "primary" is suddenly the wrong region.
We run ~200 Lambda functions. Cold starts, memory tuning, and the cost-vs-latency trade-offs that actually move the bill.
We track the four DORA metrics plus a handful of others. The trade-off between what's measurable and what's meaningful, and how we use the numbers.
We've run canary deploys on most services for two years. The mechanics are easy; the metrics that decide "promote or roll back" are where the design is.
We use blue-green for stateful services where canary doesn't fit. The actual mechanics, the data-layer subtleties, and when blue-green isn't the right answer.
We collect ~800GB of logs per day across our fleet. The shape of our logging stack, what we keep, what we drop, and what we'd build differently.
A working Prometheus stack for a 40-node cluster: what we deploy, what we tune, and what we wish we'd known about cardinality two years ago.
A focused look at the techniques that shrink container images: which actually pay off, which are folklore, and the discipline that keeps images small over time.
