# Caching Strategy Review

> Use when performing caching strategy review — reviews and designs caching strategies for services, evaluating cache placement, invalidation approaches, consistency trade-offs, and capacity planning. This template helps teams make informed decisions about what to cache, where to cache it, and how to handle cache lifecycle management.

- Skill: `cloudthinker-ai/caching-strategy-review` (Agent Skill)
- Install (CLI): `npx skillmds@latest add cloudthinker-ai/caching-strategy-review`
- Raw SKILL.md: https://api.skillmd.com/api/skills/cloudthinker-ai/caching-strategy-review/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: cloudthinker-ai (https://skillmd.com/u/cloudthinker-ai)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/cloudthinker-ai/caching-strategy-review

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# Caching Strategy Review

## Phase 1: Current State Assessment

Document the existing caching setup (or lack thereof).

- [ ] Current cache technology: ___
- [ ] Cache hit ratio: ___%
- [ ] Cache miss latency (p99): ___
- [ ] Cache hit latency (p99): ___
- [ ] Origin latency without cache (p99): ___
- [ ] Cache size (current usage): ___
- [ ] Eviction rate: ___
- [ ] Cache-related incidents in last 90 days: ___

## Phase 2: Cache Candidacy Analysis

Evaluate which data should be cached.

| Data | Read Frequency | Write Frequency | Read:Write Ratio | Staleness Tolerance | Size per Entry | Cache Candidate |
|------|---------------|-----------------|------------------|--------------------|----|-----------------|
|      | High/Med/Low  | High/Med/Low    |                  | Seconds/Minutes/Hours | | Y/N |

**Decision Matrix — Cache Candidacy:**

| Criteria | Strong Candidate | Weak Candidate |
|----------|-----------------|----------------|
| Read:Write ratio | >10:1 | <2:1 |
| Staleness tolerance | Minutes to hours | Real-time required |
| Computation cost | Expensive queries or aggregations | Simple key lookups |
| Data size | Fits in memory budget | Too large for cache tier |
| Access pattern | Hot subset, power law distribution | Uniform random access |

## Phase 3: Cache Architecture Design

**Cache Placement:**

- [ ] Client-side cache (browser, mobile)
- [ ] CDN / edge cache
- [ ] API gateway cache
- [ ] Application-level cache (in-process)
- [ ] Distributed cache (Redis, Memcached)
- [ ] Database query cache

**Cache Strategy Selection:**

| Pattern | When to Use | Trade-offs |
|---------|------------|------------|
| Cache-aside (lazy loading) | General purpose, read-heavy | Cache miss penalty, potential stale data |
| Write-through | Need strong consistency | Write latency increase |
| Write-behind | Write-heavy, eventual consistency OK | Complexity, data loss risk |
| Read-through | Simplify application code | Cache dependency for all reads |
| Refresh-ahead | Predictable access patterns | Wasted refreshes for unused data |

- [ ] Selected strategy: ___
- [ ] Justification: ___

## Phase 4: Invalidation Strategy

- [ ] TTL-based expiration: ___ seconds
- [ ] Event-based invalidation (on write/update)
- [ ] Version-based invalidation (cache key includes version)
- [ ] Manual invalidation capability
- [ ] Cache warming strategy for cold starts

**Consistency Analysis:**

- [ ] Maximum acceptable staleness: ___
- [ ] Thundering herd protection (lock/collapse duplicate requests)
- [ ] Cache stampede prevention (jittered TTLs)
- [ ] Negative caching (cache misses to prevent repeated lookups)

## Phase 5: Capacity and Resilience

- [ ] Memory budget: ___
- [ ] Eviction policy: LRU / LFU / TTL / Random
- [ ] Cache cluster sizing (nodes, replicas)
- [ ] Failure mode: Graceful degradation to origin
- [ ] Circuit breaker on cache failures
- [ ] Cache is not a single point of failure
- [ ] Monitoring and alerting on hit ratio, latency, evictions

## Counter-Rationalizations

| Shortcut | Counter | Why |
|----------|---------|-----|
| "We can skip some steps for this case" | Adapt the workflow steps, don't skip them | Skipped steps are where incidents and oversights originate |
| "The user seems to already know what to do" | Complete all workflow phases with the user | The workflow catches blind spots that experience alone misses |
| "This is a minor case, full process is overkill" | Scale the process down, don't turn it off | Minor cases become major when unstructured; the process scales, not disappears |
| "I'll fill in the details later" | Complete each section before moving on | Deferred details are forgotten; real-time capture is more accurate |
| "The template output isn't necessary" | Always produce the structured output format | Structured output enables comparison, audit trails, and handoff to other teams |

## Output Format

### Summary

- **Service:** ___
- **Cache technology:** ___
- **Strategy:** ___
- **Expected hit ratio:** ___%
- **Expected latency improvement:** ___
- **Memory budget:** ___

### Action Items

- [ ] Implement selected caching strategy
- [ ] Configure TTL and invalidation rules
- [ ] Set up monitoring dashboards for cache metrics
- [ ] Add alerts for hit ratio drops and high eviction rates
- [ ] Load test with cache enabled and disabled
- [ ] Document cache warming procedure
- [ ] Plan for cache failure scenarios