Caches that make systems feel instant.
Browser, CDN, edge, application and database caching designed as one system. Invalidation done right. Cost down, latency down, complexity contained.
The problem we solve
Caching is the single highest-leverage performance tool — and the single most common source of subtle production bugs. Cache stampedes, stale invalidations, double-keyed entries, edge serving cookies, Redis OOMing at 3am. We design caches across all five layers (browser, CDN, edge, application, database) as one coherent system, with invalidation rules nobody on your team has to second-guess.
What we deliver
- 01Browser cache headers: Cache-Control, ETag, immutable assets done correctly
- 02CDN strategy: Cloudflare, Fastly, CloudFront, Bunny — cache keys, vary, purge
- 03Edge caching with stale-while-revalidate and edge functions
- 04Application caching with Redis, Memcached, in-memory caches
- 05Database query caching, materialized views and read-replica routing
- 06Cache-aside, write-through and write-behind patterns where each fits
- 07Cache invalidation strategies including event-driven purging
- 08Cache stampede protection (single-flight, request coalescing)
- 09Per-tenant and per-user cache isolation in multi-tenant systems
- 10Cost-aware caching: when caching saves money and when it doesn't
What you receive
- Cache architecture document with diagrams and invariants
- Implementation of the cache layers we recommended
- Observability for hit rate, latency and invalidation correctness
- A runbook for the failure modes specific to caching
Stack we reach for
Ideal for
- → High-traffic sites where compute cost is becoming material
- → Apps where p95 latency is the blocker on conversion or retention
- → Teams whose Redis or CDN bills exceed their compute bill
- → Products with content that can be cached but currently isn't
- → Systems suffering from cache stampedes or invalidation bugs in production
How an engagement runs
- 01
Audit
We measure current cache hit rates, identify cold paths, profile where compute and database load comes from.
- 02
Design
Cache architecture across all layers, invalidation rules, ownership of each cache, written down.
- 03
Implementation
Roll out caches in priority order, with observability ensuring each one is doing what we intended.
- 04
Validation
Load test, correctness test, cost comparison. Document the new normal.
How to engage
Cache Audit
Measurement and recommendations with prioritized fixes — often pays for itself in cloud bill reduction.
Cache Implementation
End-to-end design and implementation of the recommended cache architecture.
Edge Performance Retainer
Continuous improvement of edge and cache infrastructure as your product grows.
Frequently asked.
01How do you handle cache invalidation?
Boring answers usually — version-bumped cache keys, event-driven purge for things that can't tolerate staleness, stale-while-revalidate for things that can. We avoid clever invalidation; it's the source of most cache bugs.
02Can caching reduce our cloud bill?
Frequently yes — sometimes by 50% or more on compute-heavy workloads. We'll measure before we promise.
03Where does Redis fit?
Application cache, session store, queue backend, rate limiter, single-flight coordinator. We use it where it earns its keep — and warn you when you're using it for things a database should do.
Have a problem worth solving well?
Tell us the outcome you want. We'll tell you what it takes — honestly, within a week, in writing.
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