1 min read
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…
Redis
10 articles
1 min read
Implementing Semantic Caching for LLM Applications
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 min read
Caching Strategies for LLM Cost Reduction
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…
1 min read
Caching Strategies for LLM Applications
Effective caching significantly reduces LLM costs and latency. Tomorrow, I will cover response streaming patterns.
7 min read
Implementing Redis Caching Patterns with Azure Functions
Redis is a popular in-memory data store that can be used as a cache. Azure Functions is a serverless compute service that can be used to run code on-demand…
2 min read
Redis Persistence Options in Azure: RDB and AOF Explained
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…
1 min read
Redis Clustering in Azure: Scaling for High-Throughput Workloads
Redis clustering provides the horizontal scalability needed for demanding workloads while maintaining Redis's sub-millisecond performance characteristics.
1 min read
Azure Cache for Redis: High-Performance Caching Strategies
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…
1 min read
Azure Cache for Redis: Caching Patterns
Redis caching transforms application performance at scale.
1 min read
Azure Cache for Redis Enterprise: High Performance Caching
Redis Enterprise: when standard caching isn't enough.