Idempotency in Distributed Systems

In distributed systems, network failures or timeouts can cause operations to be accidentally repeated. For example, when you click "Submit Payment" and get a network error, you might click again because you don’t know if the first payment went through. This can lead to double payments or other unwanted duplicates. Idempotency solves this problem.

An operation is idempotent if running it multiple times has the same effect as running it once. Here's how we implement idempotency in distributed systems:

1. Idempotency Keys: Each request gets a unique ID. When the server receives a request, it first checks if it has seen this ID before. If yes, it returns the cached response instead of processing the request again.

2. Request De-duplication: The server maintains a record of processed request IDs. This record can be stored in the cache. When a new request arrives, the server checks this record before processing.

3. Natural Idempotency: Some operations are naturally idempotent. Setting a user's name to "John" multiple times has the same effect as doing it once. But incrementing a counter isn't idempotent because each operation changes the result.

Here's a comparison of different types of operations:

Implementing idempotency adds complexity but it’s crucial for building reliable distributed systems. It prevents duplicate operations and gives users confidence that retrying failed requests is safe.