Why Idempotency Breaks in Real Systems
Modern distributed systems expose APIs that trigger state-changing operations such as payments, orders, the account acquisition process, or account updates. In such environments, the chance of duplicate transactions being initiated is quite high and unavoidable due to network retries, a Kafka rebalancer issuing multiple requests, load balancers, and other factors. Without proper safeguards, these duplicate transactions/requests can lead to data inconsistency, financial discrepancies, and variations in business invariants.
Idempotency is a well-established technique used to ensure that repeated executions of the same request produce a single, consistent outcome. While idempotency can be enforced at the application level using in-memory caches or request deduplication logic, these approaches would fail for a horizontally scaled microservice architecture, where multiple application instances may process requests concurrently and across numerous different regions.
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