#Exactly-Once

Articles about Exactly-Once — exploring patterns, best practices, and real-world implementations in production systems.

1 post tagged with exactly-once. ← All posts

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Pratik Dhanave · ·7 min read

Fault Tolerance and Exactly-Once — Not Losing or Double-Counting

A stream-processing job runs forever, which means it will experience failures — nodes crash, networks partition, processes restart. The question isn't whether failure happens but what happens to your results when it does: do you lose events, double-count them, or get exactly the right answer anyway? Fault tolerance, and the famous "exactly-once" guarantee, are what separate a toy stream processor from one you can trust with money. This post is about surviving failure correctly.

A forever-running job will fail, so the delivery guarantee matters: at-most-once (may lose), at-least-once (may duplicate), or exactly-once (correct as if neither). How checkpointing and replayable sources achieve exactly-once semantics, and choosing the guarantee by need — with idempotency as the pragmatic route.

#Stream Processing#Fault Tolerance#Exactly-Once#Distributed Systems#Data Engineering#Real-Time

All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.