DevOps Engineer
376 articles published
Most post-mortems produce a document and no follow-through. The format, the discipline, and the cultural moves that actually convert incidents into engineering improvements.
Three discounting mechanisms, three different commitments. The rules of thumb we use to pick, and the mistakes we made before settling on them.
When the service is slow and the network is suspect, these are the tools we reach for, in this order, with the exact flags that find the answer.
Token caching, model routing, prompt compression, and the boring discipline of measuring. The levers that cut our LLM bill 60% without touching feature scope.
pg_upgrade is fast but takes downtime; logical replication lets you cut over while the old DB still serves traffic. The runbook, the gotchas, and the post-cutover checklist.
Horizontal and vertical autoscalers solve different problems and break in different ways. The thresholds, cooldowns, and conflicts we learned the hard way.
Tracking experiments and shipping models are different problems. The MLOps tooling assumes one solution; production splits them. The patterns we use.
Vault + Kubernetes auth + Vault Agent Injector. The setup, the failure modes during pod startup, and the patterns that beat raw Kubernetes Secrets.
The single most useful Postgres extension you might not be using. The queries it surfaces, the indexes it implies, and the operational discipline of reading it weekly.
io_uring replaces epoll for new high-throughput services. The patterns that earn their place, the gotchas in older kernels, and where we'd still pick epoll.
Three caching patterns, three failure modes. The one we use most, the one that bit us, and the rule that decides which pattern fits which workload.
Picking partition counts and keys decides whether your Kafka consumers scale linearly or hit a wall. The patterns that survived rebalances, partition-count changes, and consumer-group ops.
