Cache Invalidation and Versioning

What you'll walk away with

Explain the core ideas behind Cache Invalidation and Versioning
Run the sample Redis command or code and verify its output
Apply the technique correctly to the Tutorial Platform and production scenarios

Build the mental model

Cache correctness needs more than a TTL. Use targeted deletion on entity updates, key versions for schema changes, and dependency mapping for list caches. A logical namespace version can switch traffic without deleting many keys immediately, while old keys disappear through expiry.

Connect it to a real scenario

When tutorial 42 changes, delete its detail key and affected category-list keys. Move from `v1` to `v2` when the payload schema changes. For bulk imports, increment `catalog:namespace-version` so new requests use a fresh namespace.

TTL is a safety net
Targeted invalidation improves freshness
Put schema or namespace versions in keys

Try the working example

shell

SET catalog:namespace-version 7
SET catalog:v7:tutorial:42 '{"title":"Redis"}' EX 300
DEL catalog:v7:tutorial:42
DEL catalog:v7:list:data:page:1
INCR catalog:namespace-version

You should see

You can selectively invalidate entries or roll the whole catalog to a new namespace.

5-minute try-it

Create a dependency table of cache keys invalidated when an author is renamed.

One important caution

Versioning without expiry leaves old namespaces consuming memory indefinitely.

Redis — Keyspace Notifications — Redis

Easy traps

Versioning without expiry leaves old namespaces consuming memory indefinitely.
Validate sample commands on a local or test instance with recoverable data before applying them to production Redis.

Exercise

Create a dependency table of cache keys invalidated when an author is renamed.

You'll know it worked when: You can selectively invalidate entries or roll the whole catalog to a new namespace.