Optimizing LLM Performance With Caching Strategies in OpenSearch

Optimizing LLM Performance With Caching Strategies in OpenSearch - ‪Uri Rosenberg‬‏ & Sherin Chandy, Amazon Web Services As organizations increasingly integrate Large Language Models (LLMs) with OpenSearch, managing computational resources and costs becomes crucial. This session explores how caching techniques can enhance LLM performance within the OpenSearch ecosystem. We’ll dive deep into implementing LLM caching strategies that complement OpenSearch’s architecture, focusing on improving query response times and reducing resource consumption. The session will cover various caching approaches including Exact vs Semantic matching, custom implementations, and integration patterns with OpenSearch’s existing caching mechanisms. Through hands-on examples and theoretical foundations, attendees will learn how to effectively implement LLM caching in their OpenSearch deployments to achieve better performance and resource utilization. This session is ideal for OpenSearch developers and administrators looking to optimize their LLM integrations.