Topic
4 articles on Distributed Systems, written from production systems rather than documentation.
Throughput is the easy part. The hard part is a consumer restart mid-batch, two replicas double-counting an event, or a slow model call on the ingest path.
Cron jobs and reprocessors are trivial with one replica and dangerous with three. Leader election lets multiple replicas run without duplicating one-off work.
CAP theorem is usually taught as an abstract triangle. In production it's one question: what should this service return when it can't reach another node?
Batching helps throughput and hurts latency. Caching helps latency and can hurt consistency. Most performance debates are about which number matters more.
Whether it needs designing from scratch or rescuing from its own success, tell me what you’re building and I’ll tell you how I’d architect it.
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