OpenSearch Project Blog

The OpenSearch Kubernetes Operator 3.0 GA release delivers production-grade rolling upgrades, TLS lifecycle management, safe scaling, and a tested migration from 2.x.

The OpenSearch Ambassador Program expands to over 30 global leaders, welcoming 11 new community advocates in our September 2026 cohort. Meet the new ambassadors driving open-source search and AI forward.

Learn what the OpenSearch Technical Steering Committee accomplished this year: modernized elections, new TAGs, FIPS compliance targets, and refreshed membership.

OpenSearch now supports running in a mode compliant with FIPS 140-3, contributed through a multi-year collaboration between SAP, SAS, and AWS.

Meet the three winners of the OpenSearch Agent Skills Hackathon. Their skills tackle log root-cause analysis, GDPR compliance, and slow-query diagnostics, all built read-only, fully auditable, and shipped with real evaluation.

OpenSearch Query Insights dashboards provide interactive visualizations for monitoring live queries, analyzing top N query performance, and viewing individual query details. This post explores each visualization and shows how to use visualizations to troubleshoot search performance issues.

Learn how the open-source AOSC plugin migrates live OpenSearch indexes—changing mappings, settings, or shard counts—without losing writes or requiring downtime.

Learn how community feedback transformed OpenSearchCon's Search track into a dedicated home for Apache Lucene practitioners. Discover the new Search & Apache Lucene track at OpenSearchCon North America 2026, September 22–24 in San Jose.

Learn how the memory retention policy in OpenSearch automatically manages the lifecycle of agentic memory, controlling storage growth while preserving specific memories.

The OpenSearch Observability TAG's first year: 10+ orgs shipped OTLP ingestion, Prometheus metrics, an open-source Observability Stack, and AI agent observability.

AI agents generate 10x the telemetry, and proprietary per-GB pricing punishes you for it. See how the open-source OpenSearch Observability Stack unifies logs, traces, and agent telemetry without vendor lock-in.

At OpenSearchCon Europe 2026, Bobby Mohammed (AWS) and Daniel Wrigley (OpenSource Connections) introduced Agentic Relevance Tuning (ART), a framework that uses specialized LLM agents to fully automate the search relevance lifecycle in OpenSearch.

Connect OpenSearch to ML models hosted on private infrastructure. Configure ML Commons connectors for VPC-hosted endpoints, private SageMaker models, and internal inference servers without exposing services to the public internet

At OpenSearchCon Europe 2026, Unnati Mishra and Akshat Khanna (Angel One) argued that privacy in search must be handled during the ingest phase rather than retroactively through access controls.

Scale Kubernetes workloads using OpenSearch query results as KEDA signals. Count 429 errors or compute p95 latency directly from your logs and traces. No extra pipeline needed.

At OpenSearchCon Europe 2026, Amazon's Shubham Chaudhary shared how bypassing Java's JVM limitations to implement native SIMD architecture achieved a 60% reduction in Lucene vector search latency.

The OpenSearch Agent Skills Hackathon is officially underway! Running from July 15 to August 17, 2026, this event offers U.S.-based developers a chance to build production-ready agentic skills, compete for a $5,000 prize pool, and potentially showcase their work at OpenSearchCon North America. Join the developer community today to start building and get your code in front of the OpenSearch maintainers.

Celebrating five years of the OpenSearch Project, true open source governance under the Linux Foundation has proven to be the most sustainable model for enterprise data infrastructure. Backed by over 2 billion downloads, OpenSearch delivers superior predictability, security, and native AI vector capabilities compared to restrictive "source-available" alternatives.

As vector search workloads scale, retrieving vectors from search results becomes a bottleneck. Vector retrieval using doc values in OpenSearch 3.7 bypasses the expensive _source vector reconstruction path, delivering 5.5x faster end-to-end retrieval and 14.7x faster server-side performance.