caching-strategy

Design caching strategies with TTLs and invalidation for APIs and CDNs.

Updated Apr 8, 2026
One-click install
npx skills add https://github.com/s3nex-com/sdlc-skills-library --skill caching-strategy-s3nex-com
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: caching-strategy
Source: https://github.com/s3nex-com/sdlc-skills-library/tree/main/skills/phase2/caching-strategy
Command: npx skills add https://github.com/s3nex-com/sdlc-skills-library --skill caching-strategy-s3nex-com

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Caching decisions are hard, error-prone, and impact latency and data freshness. This skill provides a structured framework to select caching layers, patterns, TTLs, and invalidation strategies that align with data volatility and service SLAs.

Core Features & Use Cases

  • Guidance on when to cache, where to cache (edge vs origin), and how to pick patterns (cache-aside, read-through, write-through, write-behind, refresh-ahead).
  • TTL and invalidation strategy recommendations, including event-driven and version-key approaches.
  • Observability guidance to ensure safe and reliable caching with performance benefits.

Quick Start

Assess a service's data access patterns and propose a caching strategy including layer choice, TTLs, and invalidation approach.

Frequently Asked Questions about caching-strategy

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
When do I need a caching strategy for my API and what problem does it solve?

A caching strategy is needed to reduce latency and manage data freshness for APIs. It provides a structured framework to select optimal caching layers and patterns that align with data volatility and service SLAs.

How do I choose between cache-aside, read-through, and write-through caching patterns?

Choosing a caching pattern depends on your data access patterns. This skill guides selecting between cache-aside, read-through, write-through, write-behind, and refresh-ahead patterns to optimize latency for specific workloads.

What's the best way to handle cache invalidation and specify TTLs?

The best way to handle cache invalidation is matching the approach to data volatility. This skill recommends TTL specifications and invalidation strategies using event-driven and version-key approaches to ensure correctness.

How do I decide whether to cache at the edge or the origin for my CDN configuration?

Deciding whether to cache at the edge or origin depends on your latency requirements and data freshness SLAs. This skill helps identify optimal caching layers for CDN configurations and edge caches.

What observability guardrails do I need to ensure safe and reliable caching?

Observability guardrails for safe caching require monitoring cache hits, misses, and invalidation events. This skill provides observability guidance to ensure performance benefits without sacrificing data correctness.

Does this caching framework work for services with strict data freshness SLAs?

Yes, this caching framework is designed for strict data freshness SLAs. It aligns TTLs and invalidation approaches with data volatility to ensure correctness while reducing latency.