#Idempotency

When workflow metadata and application data live in the same Postgres database, they can be updated in the same database transaction, which simplifies tough problems like workflow task idempotency and atomicity.

Network requests fail. Timeouts happen. Clients retry. And without idempotency keys, a single payment...

A production story about payment retries, duplicate requests, Redis, distributed locks, and how idempotency keys protect users from flaky networks.

The last couple of months, I ended up implementing idempotency in 2 different Spring Boot projects...

If you’ve ever been in a situation where you paid for pizza online, mustered the courage to begin...

Handling duplicate requests in APIs, especially in payment systems, is a headache. NestJS RedisX...

Idempotency in distributed systems is the property that saves you after the network lies, the queue...

Production-proven API patterns every backend developer needs. Rate limiting strategies, cursor vs offset pagination, idempotency keys, bulk operations, and webhook design.

A pipeline that runs twice should produce the same result as one that runs once. That property is...

In a single-machine system, an operation happens once or it fails. In a distributed system, an...

You built a Shopify integration. It works great. Until it doesn't. A customer's network drops right...

From Dev.to - java: Claude 4.5 Speculative Tooling: Why Your Java Backend Needs Idempotency or It’s Dead

Stopping duplicate requests is only part of the idempotency problem. This piece looks at why replay windows should be based on business intent and workflow lifetime, not generic middleware defaults that happen to be easy to apply.

From Dev.to - backend: Idempotency Keys in Production: The Race Conditions, Expiration Traps, and Edge Cases Most Tutorials Skip

Stripe data engineering interview questions lean Python-heavy with a payments-platform edge: six...

If you're integrating a gift card API for the first time, the vendor demo will look great. The...

Every payment flow has a silent enemy: the network. Requests time out, connections drop, users panic,...

Where keys come from, how long they live, the intent vs result contract. A 60-line Postgres-backed idempotency layer with TTL you can adapt.

Picture a replayed Kafka batch that charges customers twice. The fix is a 60-line idempotency wrapper. Here is the contract every event consumer needs.

Duplicate requests aren’t edge cases - they’re normal behavior in distributed systems. A client...