Senior Software Engineer · 10+ years
Ten years building backend systems at scale — distributed event pipelines, cloud cost optimization, and operational observability for platforms serving millions of users. I write about the failure modes I've shipped around and the patterns that held up under real traffic.
Previously
From $20,000 to $1,800/month — no infrastructure change, no migration to another service. Just a better data model.
One question surfaces more production risk than any checklist: what happens when this fails? Here's how to ask it, answer it with concrete patterns, and prove your answers hold under real load.
In 2017, before LLMs made enterprise AI mainstream, I built a multi-channel chatbot that automated L1 support at scale. Here's the architecture, the results, and what it looks like rebuilt with today's tools.
Logs alone won't save you at 3am. Here's the observability setup I use to make distributed systems debuggable by design — structured logs, distributed traces, and alerts that actually mean something.
How to keep payment and order flows consistent across microservices at scale — with real failure modes, idempotency requirements, and SQS-backed orchestration that degrades gracefully instead of deadlocking.
How to cut cluster costs by 40–70% by replacing guessed resource configs with metric-driven right-sizing — without sacrificing reliability.