Cedric Pelvet

Most teams run observability across fragmented tools: one for metrics, another for logs and traces, each with its own cost model and blind spots. In this session, you work hands-on to consolidate your observability stack on Amazon OpenSearch Service.

Learn how to improve search applications using Amazon OpenSearch Service. We'll explore implementing advanced architectural patterns using Model Context Protocol (MCP) and hybrid search features like Reciprocal Rank Fusion (RRF).

This chalk talk delves into the art of right-sizing Amazon OpenSearch Service clusters for optimal cost and performance. It explores the trade-offs between provisioned clusters and Amazon OpenSearch Serverless, tailored to different workloads such as log analytics, lexical, semantic, and sparse search.

Migrating to Amazon OpenSearch Service involves five main steps: plan, POC, deploy, data migration, and cutover. In this session, learn how to build a successful migration strategy to OpenSearch Service.

Amazon OpenSearch Service makes it easy to maximize the value of your application and log data for search and time-based analytics workloads. Whether you’re using another technology for search or analytics or running Elasticsearch or OpenSearch self-managed, Amazon OpenSearch Service provides the operational heavy lifting that makes it easy to focus on your core mission.