correctnessstream-processingdeduppayments
Exactly-Once Processing (Practical)
Achieve effective exactly-once outcomes via idempotency, transactions, and dedup rather than magic guarantees.
Definition
Practical exactly-once combines at-least-once delivery with idempotent writes and dedup/transactional boundaries.
When To Use
- Financial, billing, and inventory updates where duplicates are unacceptable.
- ETL/streaming jobs with replay and checkpointing needs.
- Cross-service workflows that must avoid double side effects.
When Not To Use
- Low-value telemetry where at-least-once with aggregation is sufficient.
- Without durable state to track processed operations.
- When system complexity cost outweighs correctness benefit.
Tradeoffs
- Improves correctness, but increases storage and coordination overhead.
- Reduces duplicate side effects, with added latency on dedup checks.
- Supports safe replay, while requiring strong key design and retention policy.
Common Failure Modes
- Dedup state eviction too early reintroduces duplicates.
- Producer retries with new keys bypass idempotency guarantees.
- Checkpoint/offset corruption causes partial replay inconsistency.
Interview Framing
Use this structure when the interviewer asks for this pattern explicitly.
State where duplicates can enter, where they are absorbed, and how replay is verified end-to-end.
Related Project Deep Dives
Event Deduplication Platform for Idempotent Processing
Design a platform that removes duplicate events across distributed pipelines with low latency.
Change Data Capture (CDC) Pipeline
Design a system that captures database changes in real-time and streams them to downstream systems with schema evolution support, exactly-once delivery, and multi-database compatibility.
Related Concepts
Idempotency Keys
Guarantee repeated client retries do not create duplicate side effects.
Transactional Outbox Pattern
Atomically persist business state and event records in one DB transaction, then publish asynchronously.
Change Data Capture (CDC)
Stream database changes from logs to downstream systems with low-latency propagation.