Labs ›product catalogue with search on AWS0 / 9 steps
Step 1 of 9 · Intro
Design a product catalogue with search on AWS
Keep one source of truth, and add a search index and a cache that can fail without taking lookups down.
How it works
›Aurora is the system of record. Lookups by id go to ElastiCache first and fall through to Aurora on a miss (cache-aside).
›OpenSearch answers text queries and filters. It is a derived copy, filled by an indexing pipeline, so it is eventually consistent and can be rebuilt from Aurora.
›Requests here split evenly between the two paths, since the model sends traffic to every connected component in proportion to its size.
›Limits come from AWS documentation (default quotas in us-east-1). Where AWS publishes no figure, such as how many requests a container or database handles, the lab states its assumption on the component.
What you'll build
Cache-aside lookups at 2,000 requests a second
A search index alongside, at 5,000
A plan to keep the index fresh
A design where losing the index leaves lookups working