Caching
Everything on CoreConcept tagged with Caching. Explore related tags below.
Related tags
Courses
From fundamentals to production — caching strategies, eviction policies, invalidation, Redis, CDN caching, and multi-level architectures. Practical patterns and a guided final project you build in your own stack (no bundled starter repo).
Articles
In-memory caching is an essential component of high-throughput web architectures, reducing database read load and accelerating API response times. When selectin…
LLM caching sounds simple until the cached answer crosses a tenant boundary, repeats stale product policy, or hides a model regression. The hard part is not sto…
A URL shortener's redirect endpoint, GET /r/{code}, looks purely read-heavy — billions of redirects against a handful of short codes created per second. But eve…
A 4-node session cache scales to 5 nodes to handle more traffic. With hash(key) % N, that single node addition changes almost every key's target node, and the c…
A shopping cart must remember items, so the product cannot be literally stateless. The useful design question is where that state lives. Keep the cart inside on…
A dashboard can look “fast” while users still wait, and a load test can report huge requests-per-second while p99 checkout times explode. Latency is how long on…
Checkout slows while product pages remain healthy. CPU is moderate, but the orders table shows rising lock waits and writes queue behind one hot index. Adding a…
A product page feels instant on the second visit because some layer reused work from the first. The useful beginner question is not “should we add Redis?” but “…
A Redis GET can be constant-time and still miss its latency target when a large Lua script is ahead of it, the client opens a new TLS connection, or the value t…
A product page is easy to cache until a price changes: the CDN still has the old response, one app instance has an older in-process value, and Redis has already…
A product page's cache key expires at 2:00:00pm. In the same instant, 5,000 concurrent requests check the cache, all get a miss, and all 5,000 independently que…
Primary relational databases (like PostgreSQL or MySQL) execute disk I/O and query compilation for every read query. As application concurrency grows to thousan…
As web applications scale to hundreds of thousands of active users, querying relational databases for every page view creates severe I/O bottlenecks and high da…
A Redis SET key value NX EX 5 lock stops a cache stampede in theory, but two implementation details separate a lock that actually works under concurrent load fr…
Want a curated collection instead? Topic hubs group the best content by subject.
Browse Topics