Backend & Distributed Systems Assessment

Add idempotency keys and enforce uniqueness at the persistence layer

Log duplicate transactions and reconcile later

GC pauses, lock contention, or downstream dependency latency amplification

Cache indefinitely and invalidate manually when needed

Use write-through or write-behind with explicit TTL and targeted invalidation policies

Implement circuit breakers, bulkheads, and timeout isolation per dependency

Wrap both operations in a single local transaction

Use the outbox pattern with transactional writes and asynchronous publishing

Publish first, then write to the database

Ignore inconsistencies and reconcile nightly

Uneven traffic distribution and hotspotting

Store session state in distributed storage such as Redis or a database

Fail fast, apply backpressure, and shed load when limits are reached

Consistency versus availability under network partition

Assume the message queue guarantees exactly-once delivery

Design handlers to be idempotent and safe for at-least-once delivery semantics