What strategies exist for handling Kafka consumer failures in production?

Production Kafka consumer resilience strategies: Idempotent processing: design processing logic to be safely retried — use idempotency keys to detect and skip duplicates. Retry logic with backoff: catch transient errors (DB timeouts), retry with exponential backoff before DLQ. Circuit breaker: if downstream service is consistently failing, pause consumption temporarily to allow recovery. Poison pill handling: if one specific message always fails (bad format, unexpected data), send to DLQ after N retries without blocking healthy messages. Offset management: commit offsets only after successful processing (enable.auto.commit=false); track per-message status if partial batch processing is needed. Consumer group monitoring: alert on group rebalances, partition assignment timeouts (max.poll.interval.ms exceeded), and lag growth. Graceful shutdown: call consumer.wakeup() on SIGTERM, finish current batch, commit, then close — avoiding unnecessary rebalances and offset gaps.