Implement HybridCache with invalidation and output caching for .NET 10 applications.
npx skills add https://github.com/Maj3D10/Training-Platform --skill caching-maj3d10
Please help me install this Agent Skill. Skill: caching Source: https://github.com/Maj3D10/Training-Platform/tree/main/.agent/skills/caching Command: npx skills add https://github.com/Maj3D10/Training-Platform --skill caching-maj3d10
It helps you reduce latency and database load by caching read operations while preventing stale data, stampedes, and inefficient caching behavior.
Use case: When building a products API, cache GET /products/{id} lookups with HybridCache for fast reads, evict the specific key after PUT /products/{id} updates, and optionally cache GET / or list endpoints at the response level using output caching.
Load this caching skill and implement HybridCache GetOrCreateAsync for your read endpoints, then add targeted invalidation or tag eviction on your write endpoints.
High-intent search queries and answers about installing and using this skill.
HybridCache in .NET provides built-in stampede protection by coalescing concurrent cache misses for the same key. This mechanism prevents multiple identical database queries from executing simultaneously when a cache entry expires.
Output caching caches full HTTP endpoint responses when the entire payload can be safely reused. It is best applied to public or static-like data endpoints where the complete response can be served without user-specific modifications.
HybridCache supports distributed caching by combining local and distributed cache layers in .NET applications. This hybrid approach reduces latency while maintaining data consistency across multiple server instances.
Setting explicit TTLs and safe eviction policies involves defining precise expiration times for cached entries and configuring removal triggers. This ensures cached data is automatically purged before becoming stale or serving user-specific data incorrectly.
You should not use output caching for endpoints returning user-specific or frequently mutating data. If the payload cannot be safely reused across all requests, applying response-level caching risks serving incorrect personalized data.
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