Optimizing Stripe API performance in Lambda with caching strategies

Summary

The post addresses performance, cost, latency, and rate-limiting challenges that arise when applications make high-volume requests to Stripe's API from AWS Lambda. It presents a two-level cache using ElastiCache for Redis as the first layer and DynamoDB as the durable second layer, with Lambda coordinating cache reads, Stripe retrieval, and writes. On a miss, the function checks Redis, then DynamoDB, fetches the customer from Stripe if necessary, and stores the response in both layers with one-hour Redis and 24-hour DynamoDB TTLs. The DynamoDB design uses composite keys, a GSI for cache-type and timestamp queries, TTL cleanup, and environment-specific capacity settings; the post also discusses Redis connection pooling, Lambda sizing, capacity planning, cost control, monitoring, and webhook-based invalidation.

Takeaways

1. 1

   Redis is checked before DynamoDB, while Stripe is called only when the requested data is absent from both cache layers.

2. 2

   The example assigns cached data a one-hour Redis expiry and a 24-hour DynamoDB TTL, with DynamoDB configured for automatic expired-item cleanup.

3. 3

   The design uses DynamoDB composite keys and a GSI to support multiple item types, stale-entry queries, and bulk cache invalidation.