E-commerce Catalog
Browse and search a product catalog — and survive your own sale email.
Keep shoppers browsing through a seasonal sale while the search index slows and the catalog DB drops out.
Catalog browsing is read-heavy and wildly cacheable — the same bestseller pages over and over — while search queries need their own index off the browse path. Sized right, the CDN and product cache soak the sale surge and a DB outage never reaches a shopper; sized wrong, every page view is a DB read.
Components in play
- Edge CDN — Serves product pages and images from the edge.
- Catalog API — Assembles product pages; routes queries to the index.
- Catalog dispatch — Splits catalog traffic between the cache-backed browse path and the search index.
- Product cache — Hot products in memory so browsing skips the DB.
- Catalog DB — Source of truth for products, prices and stock.
- Search index — Full-text queries — facets, typos, ranking — off the browse path.
Graded on these SLOs
- ≥ 98.50%Browsing succeeds
- ≤ 100 msPage p99
- ≥ 9.0k rpsServe the sale
- ≤ 85%Sale headroom
- ≤ 8Lean footprint
The brief
Design the product catalog for a storefront like Amazon. Shoppers browse product and category pages, and run full-text searches with facets and typo tolerance. Browsing is wildly read-heavy and cacheable — the same bestsellers over and over — while search is a different access pattern entirely and shouldn't compete with browse traffic on the same store. A seasonal sale can multiply browsing overnight, and the catalog DB will pick that moment to have a bad day.
Functional
- Browse product and category pages
- Full-text search with facets (price, brand, rating)
- Update price/stock for a product
Non-functional
- Read-heavy browsing (~50:1 over writes), low-latency page loads
- Search must not degrade browse latency, or vice versa
- High availability — checkout depends on the catalog staying up
Warm-up: design decisions
Optional theory to prime the calls a senior engineer would make before you build.
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