opensearch-best-practices

What problem does it solve?

OpenSearch development best practices for indexing, querying, search optimization, vector search, and cluster management are organized to improve performance, accuracy, and reliability of search systems.

Core Features & Use Cases

• Define explicit index mappings and appropriate data types to ensure predictable search behavior and efficient storage.
• Tune vector search and k-NN parameters, shard sizing, and ISM lifecycle to balance latency, recall, and throughput in real-world workloads.
• Implement security, monitoring, and maintenance practices to operate robust OpenSearch clusters in production, including multi-tenant access and anomaly detection.

Quick Start

Review the recommended index designs and operational policies, then apply the guidelines to your OpenSearch deployment to improve search performance and reliability.