# Case Study: Caching an E-Commerce Catalogue — Caching Strategies & CDN Design

Source: https://www.skillbyai.com/en/caching-strategies/p-case

> Design a complete caching strategy for a high-traffic product catalogue.

## Putting the layers together

A shop with 2 million products sees 30,000 requests per second at sale peaks, 95% of them reads. The design: **static assets** are fingerprinted and cached for a year at the CDN and in browsers. **Product and category pages** are rendered by the app and cached at the CDN with `s-maxage=300`, `stale-while-revalidate=60` and `stale-if-error=600`, tagged with product, category and brand IDs. **Product data** is cached in Redis with cache-aside, versioned keys and a 10-minute TTL with jitter, plus a 1-second in-process L1 for the hottest keys. A **change data capture** stream from the products and prices tables deletes Redis keys and purges CDN tags on every committed change. **Prices and stock** shown on pages may be up to a few seconds stale, but **checkout re-reads** them from the database inside the order transaction. **Search results** for the top queries are micro-cached for 15 seconds. Monitoring tracks edge and Redis hit ratios, origin load, purge latency and evictions; load tests run warm and cold.

## The design in one table

Each layer has an explicit freshness rule and invalidation path.

```text
data                   where cached                 TTL / freshness             invalidation
---------------------  ---------------------------  --------------------------  -----------------------
JS/CSS/images          browser + CDN                1 year, immutable           new file name
product/category HTML  CDN                          s-maxage 300, swr 60        purge by tag via CDC
product JSON           Redis (+ 1 s local L1)       600 s +/- 10% jitter        delete key via CDC
price/stock on page    Redis                        <= 30 s                     delete key via CDC
price/stock at checkout  not cached                 always current              n/a (read DB in txn)
top search queries     CDN micro-cache              15 s, stale-if-error 300    TTL only
user cart/account      not shared-cached            private / no-store          n/a
```

## Write the freshness contract down

The table above is the most useful artefact in a caching design. It tells product managers what staleness to expect and tells engineers where each invalidation must happen.

**Quiz:** In the case study, why does checkout read price and stock directly from the database?

- [x] Decisions that charge money or commit stock must use current data, even if pages show slightly stale values
- [ ] Redis cannot store prices
- [ ] CDNs block checkout pages
- [ ] Databases are faster than Redis

*Answer:* Decisions that charge money or commit stock must use current data, even if pages show slightly stale values. Display may tolerate staleness; transactions must use the source of truth.