Semantic Caching for LLM Applications: Reducing Costs and Latency
Traditional caching requires exact matches. Users asking "What is Azure?" and "Can you explain Azure?" would generate two separate API calls. Semantic…
10 articles
Traditional caching requires exact matches. Users asking "What is Azure?" and "Can you explain Azure?" would generate two separate API calls. Semantic…
Use Redis Vector Search for efficient similarity matching at scale. Tune the similarity threshold based on your use case - higher values ensure more precise…
1. Start with exact match Simple and effective 2. Add semantic caching For variable phrasing 3. Set appropriate TTL Balance freshness and savings 4. Monitor…
Effective caching significantly reduces LLM costs and latency. Tomorrow, I will cover response streaming patterns.
Cache-aside, write-through, write-behind and refresh-ahead with Azure Cache for Redis in .NET 7 isolated Azure Functions, and when each one is the wrong choice.
Redis persistence is the configuration choice that determines what happens to your cache data when the instance restarts—and for most Azure Cache for Redis…
Redis clustering provides the horizontal scalability needed for demanding workloads while maintaining Redis's sub-millisecond performance characteristics.
Azure Cache for Redis is the caching layer I add to almost every production Azure application that has read-heavy patterns with data that doesn't change on…
Redis caching transforms application performance at scale.
Redis Enterprise: when standard caching isn't enough.