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AWS Reserved Instances vs Savings Plans vs Spot — When Each Fits
Three discounting mechanisms, three different commitments. The rules of thumb we use to pick, and the mistakes we made before settling on them.
Linux Network Debugging — tcpdump, ss, and eBPF in Anger
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.
LLM Cost Optimization in Production — What Actually Moves the Bill
Token caching, model routing, prompt compression, and the boring discipline of measuring. The levers that cut our LLM bill 60% without touching feature scope.
Postgres Logical Replication for Zero-Downtime Major Upgrades
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.
Kubernetes HPA and VPA — Tuning From Production Pain
Horizontal and vertical autoscalers solve different problems and break in different ways. The thresholds, cooldowns, and conflicts we learned the hard way.
MLOps — Model Registry vs MLflow Tracking, And When You Need Both
Tracking experiments and shipping models are different problems. The MLOps tooling assumes one solution; production splits them. The patterns we use.
HashiCorp Vault as a Secrets Backend for Kubernetes
Vault + Kubernetes auth + Vault Agent Injector. The setup, the failure modes during pod startup, and the patterns that beat raw Kubernetes Secrets.
pg_stat_statements — Postgres Query Analysis Without Guessing
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.
Linux io_uring — Async I/O Patterns We Use
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.
Caching Patterns — Read-Through, Write-Through, Cache-Aside in Practice
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.
Kafka Partition Strategies — Scaling Consumers Without Reshuffling Everything
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.
Agentic Ops — When (and When Not) to Use AI Agents for Incident Response
AI agents for incident triage sound great in demos. We've tried it in production. The patterns that earn their keep, the ones that backfire, and where humans still beat agents.