Course Overview: What You’ll Learn in AI Caching Strategies: CDN, Redis, and Application-Layer Patterns

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AI Caching Strategies: CDN, Redis, and Application-Layer Patterns

Make slow apps fast with the right cache in the right place. From the browser-to-database hierarchy to Redis patterns, CDN edge caching, and AI-assisted cache invalidation strategies.

What You Will Learn

Map your application’s cache hierarchy (browser, CDN, app, DB) and know which layer owns each kind of data.
Design cache keys and TTLs that avoid thundering-herd storms without locking yourself out of invalidation.
Pick the right Redis eviction policy (allkeys-lru, volatile-lfu, noeviction) for your workload and prove it with numbers.
Use CDN edge caching with Vary headers, stale-while-revalidate, and origin-shield patterns to survive traffic spikes.
Implement read-through, write-through, and write-behind patterns correctly — and know when each one fails.
Instrument hit rate, eviction rate, and cache-miss p99 latency so performance regressions are caught in hours, not weeks.
Use AI-assisted analysis to diagnose cache-poisoning, hot-key, and cascading-failure incidents under pressure.

Full Course Breakdown

LESSON 2

The Cache Hierarchy: Browser, CDN, Application, Database — Knowing Where to Cache

The four-layer map every backend engineer needs — what each layer is good at, and the one question that tells you where a piece of data belongs.

LESSON 3

Cache Keys, TTLs, and the Thundering Herd Problem

How to design cache keys that don’t collide, TTLs that don’t stampede, and the single-flight pattern that survives Black Friday.

LESSON 4

Cache Invalidation: The Hardest Problem, and Four Patterns That Work

TTL expiry, event-driven purge, versioned keys, and soft expiry — the four invalidation strategies and the failure mode of each.

LESSON 5

Redis as an Application Cache: LRU, LFU, and Eviction Strategies

Pick the right Redis eviction policy for your workload, and build the metrics that tell you when you chose wrong.

LESSON 6

CDN and Edge Caching: What to Put There, What Never to Put There

Vary headers, cache-control, stale-while-revalidate, origin shields — the production CDN checklist.

LESSON 7

Read-Through vs Write-Through vs Write-Behind: Pick One and Defend It

The three cache-interaction patterns, the failure mode of each, and the decision tree for which one fits your workload.

LESSON 8

Observability for Caches: Hit Rate, Eviction Rate, and Metrics That Catch Regressions

The five cache metrics that matter, the alerts that pay for themselves, and the AI-assisted analysis that finds hot keys in 90 seconds.

Who This Course Is For

Backend engineers owning an app that’s starting to feel slow under real traffic.
Platform engineers standing up Redis, Varnish, or a CDN for the first time.
SREs who inherited a caching layer that ‘works’ but is a black box during incidents.
Full-stack developers who need one end-to-end understanding of where caches live and what they each do.

What Makes This Course Different

Hierarchy-first: every lesson anchors back to the four-layer cache diagram so you never lose the map.
Pattern-based: read-through, write-through, write-behind, cache-aside, each with the failure mode it owns.
Production-oriented: every lesson references a real incident type (stampedes, poisoning, hot keys, cascading eviction).
AI-pragmatic: shows exactly where AI-assisted analysis saves time in an incident, and where it just adds noise.

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