OpenSearch 3.5 isavailable for download, with significant upgrades for observability workloads and search use cases, new tools to build more powerful agentic applications, and a number of enhancements to help you optimize operations.
New features for this release include:
Expanded Prometheus support for deeper insights into metric data
Enhanced search optimization through Search Relevance Workbench
Agentic memory support for self-learning applications
Increased control over query performance and efficiency
Read the blog post for highlights from the latest version, and visit therelease notes for a complete roundup of what’s new in OpenSearch 3.5.
OpenSearch 3.4’s agentic search in OpenSearch Dashboards: Hands-on use cases and examples
The introduction of OpenSearch 3.4 brought agentic search to OpenSearch Dashboards, allowing users to move beyond complex syntax and query using natural language.
This intelligent agent interprets the user's question, plans the search, and transparently delivers results, opening up possibilities for conversational e-commerce search, fast filtering, and personalized results by integrating external data.
Bringing stability and resilience to the OpenSearch Kubernetes Operator
With the 3.0 alpha release of the OpenSearch Kubernetes Operator, over 100 significant changes have been introduced. This release delivers substantial improvements in security, stability, flexibility, and operational capabilities, addressing critical bugs, feature requests, and enhancing usability.
Scaling to 1B Vectors: What DataStax Learned Using OpenSearch and JVector
"OpenSearch allows us to go beyond simple vector search into a holistic end to end search and RAG solution while keeping the advantages of having a pure Java plugin." ~ Samuel Herman, Datastax, an IBM company
If you've been wondering whether vector search can actually scale beyond demos and benchmarks into real production systems read on!
Discover how DataStax built billion-scale vector search using OpenSearch and JVector, achieving lower latency and reduced costs without relying on expensive GPU setups. Their case study reveals how strategic engineering choices, like inline vector storage and concurrent graph construction, made all the difference in production.
OpenSearch Software Foundation's Executive Director, Bianca Lewis, predicts 2026 will be the year of agent-ready databases, strategic AI adoption, and open platforms that avoid vendor lock-in while scaling innovation.
The OpenSearch Ambassador program is now accepting applications for its next cohort! We invite community members who are passionate about being advocates of the OpenSearch project to apply. But don't delay...applications close on February 16.
Have an inspiring story, video, use case, or tutorial to share? We want to hear from you! Submit your content for consideration.
Where to Find Us
For a complete list, please visit our events page.
Save the date! You will not want to miss an OpenSearchCon event in 2026. Join the OpenSearch community to learn, connect, and collaborate at one of our flagship events worldwide. Explore solutions to real-world problems, network with your peers, and explore the future of search, observability, and security applications.
The OpenSearch Project is a project of The Linux Foundation. OpenSearch is a community-driven, Apache 2.0-licensed open source search and analytics suite that makes it easy to ingest, search, visualize, and analyze data.
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