event-replay-strategy

To safely replay SaaS events, you need a strategy that includes consumer idempotency checks, batch processing with throttling, and a dry-run mode to verify safety before live execution. This approach supports outbox-based replay and Kafka offset resets.

Bootstrapping a new event sourcing consumer is best achieved by replaying historical events from an outbox source. You can perform a selective replay filtered by tenants, aggregates, or event types to populate the new consumer's derived data accurately.

Yes, consumer idempotency is a mandatory prerequisite before replaying Kafka events. Ensuring duplicates are harmless prevents data corruption during full or selective replays, allowing safe recovery and offset resets without side effects.

Yes, you can run a selective event replay across specific tenants, aggregates, or event types. Using a configurable replay gate, the system filters historical outbox events, allowing targeted data correction without processing the entire event store.

Dry-run mode works by simulating the outbox event replay process without applying live changes. It allows you to verify consumer idempotency and replay safety for a defined period, such as the last 7 days, before committing to a live replay.

To replay events from a point in time, you can perform a Kafka offset reset. This replay strategy supports offset resets alongside outbox-source paths, allowing you to reprocess historical events and correct derived data safely.