OpenSearchProj

OpenSearch 3.7 ships with native Prometheus integration, bringing logs, traces, and metrics into a single interface for querying, alerting, and SLO tracking. Parameterized dashboards now adapt across services and environments without rerunning queries. Vector retrieval runs up to 5.5x faster for AI-powered applications, hybrid search gains new normalization and ranking techniques, and you can preview Index State Management policy changes before they apply. Read the blog and download 3.7: opensearch.org/blog/explore-o…

#OpenSearchCon North America 2026 🔍 📍 San Jose | Sept 22-24 Session Highlight: Sokratis Papadopoulos (CERN) shares a fully open source approach to monitoring large-scale deployments. View the session: bit.ly/4vpPJyM Register now + save: bit.ly/3NXhWNN

The OpenSearch Agent Skills Hackathon opens July 15 for US-based participants. Build innovative Agent Skills for OpenSearch, contribute to the community, and compete for a $5,000 prize pool. Winning skills may be open sourced through the official OpenSearch Agent Skills GitHub repo and highlighted at OpenSearchCon NA. Learn more and be the first in line to register: bit.ly/443K3iM

Debugging incidents shouldn’t require jumping between tools. The OpenSearch Observability Stack unifies metrics, traces, and logs in one OpenTelemetry-native platform. Follow a complete RCA workflow, from service health signals to trace waterfalls and correlated logs, without leaving the UI. Read more: bit.ly/3STLfTE

The era of “collect everything” is changing. Poor-quality telemetry leads to unreliable dashboards, alerts, and AI-driven insights. Join Shenoy Pratik Gurudatt from @AWS to explore the Instrumentation Score, a vendor-neutral framework for auditing and improving observability data before it reaches your OpenSearch cluster. Learn how high-fidelity instrumentation can reduce MTTR, improve analysis, and unlock more value from the OpenSearch Observability Stack: bit.ly/4f2V4r7

Enterprise search relevance starts with understanding intent, not just matching keywords. Dom Couldwell, Product Manager for OpenSearch at @IBM, explores how query intent, journey intent, and product intent help search systems deliver results aligned with user goals. While vector search improves semantic understanding, hybrid retrieval balances relevance with transparency, explainability, and the trust required for enterprise-scale adoption. Read the OpenSearchCon EU session recap: bit.ly/4fqfGtk

AI is redefining what enterprises expect from search and observability. Bianca Lewis, Executive Director of the OpenSearch Software Foundation, explores why context matters, how hybrid search balances lexical and semantic retrieval, and what open infrastructure means for the next generation of AI. Read the interview from Dataquest: bit.ly/4ePQmga

CrowdStrike, Freshworks, and @AWS all shared their migration stories at OpenSearchCon India 2026. If you are thinking about moving off proprietary search, these are the sessions to watch first: bit.ly/4vVgzzZ

OpenSearch vs. the Black Box: One Stack for Observability & AI Agent Evaluation takes place July 22 at 11:00 AM PDT. Join Dotan Horovits, OpenSearch Ambassador, and Rekha Thottan to learn how OpenSearch and OpenTelemetry help monitor applications, trace AI agent behavior, and evaluate outputs before production. Register: bit.ly/4vqBppP @TheNewStack

Sessions on this year's #OpenSearchCon North America agenda: 🔍 "The LLM Said What?! A Survival Guide" 🪵 "Dead Logs Don't Lie" 📏 "Cluster Sizing Without Guessing" 👻 "Index Lifecycle Decisions That Will Haunt You at 10B Docs" Curious now? Come see them live! Full schedule: bit.ly/3PWzpqM Sept 22-24 | San Jose 👉 bit.ly/3NXhWNN

For CIOs evaluating how to modernize enterprise search for the AI era, vector databases are becoming core infrastructure for semantic, multimodal, and context-aware retrieval. The CIO Decision Brief explains how OpenSearch unifies full-text and vector search to improve relevance, reduce infrastructure cost, and accelerate AI adoption at scale. Download the brief: bit.ly/4aJA9Xv

400 terabytes of logs per day. 100 million logs per day on Kubernetes. Those are not benchmark numbers. They are production workloads from teams that shipped their talks at OpenSearchCon India 2026. Five observability sessions are now live. Rashmi Ramanathan and Buden Shaik from @FreshworksInc explain how ODD replaced ELK at 400TB scale. Sravanthi Naga from @Pega covers performance engineering for a Kubernetes observability platform at 100M logs daily. Jeevitha G walks through turning noisy logs into actionable insights with Fluent Bit, OpenSearch, and RAG. Bharav Patel from @AWS covers advanced data transformation pipelines with PPL. And the Freshworks team shows how they built a full observability suite inside OpenSearch Dashboards. If you are running any kind of log infrastructure, at least one of these will be directly useful. bit.ly/4eSuFdV

Data Prepper 2.16 introduces new capabilities for modern observability pipelines, including pull-based Prometheus scraping, direct ingestion into OpenSearch Time-Series Database, experimental pull-based ingestion, and expanded OpenTelemetry support. Learn how the release improves how teams collect, process, and scale metrics and logs with OpenSearch: bit.ly/4wAvXSq

Building an AI agent is the easy part. Keeping it reliable, observable, and safe in production is where most teams hit a wall. Four sessions from OpenSearchCon India 2026 address that wall directly. Shubham Kumar and Ramya Bhat from AWS show how to build context-aware agents with persistent memory backed by OpenSearch. Chanpreet Singh and Shatakshi Pandey from Amazon tackle search-confidence guardrails so your agents stop returning low-quality results. Hitesh Subnani and Smita Singh from AWS bring in the Strands framework for observability and coordination across agent workflows. Abdul Muneer Kolarkunnu from NetApp InstaClustr and Sakshi Nasha covers running all of this on private LLMs, for teams with data sovereignty requirements. If you are building with AI agents, this is a practical set of sessions that skips the hype and gets into the real engineering. All four are now on the OpenSearch YouTube channel: bit.ly/4eSuFdV

How do enterprises modernize search for the AI era? Traditional search was built around keywords, but users now expect answers that understand context and intent. Modernizing Search is a guide to building AI-powered retrieval with vector search, semantic understanding, and RAG. It provides a practical framework for implementing intelligent, scalable search with OpenSearch. Download the ebook: bit.ly/4vmAve7

2 billion downloads. 15,000+ community members. 1M+ monthly visitors. OpenSearch is scaling as a community-driven foundation for search, analytics, and AI. In this episode of Front Page, Bianca Lewis, Executive Director of the OpenSearch Software Foundation, discusses open governance, hybrid search, and how OpenSearch helps organizations build AI applications more efficiently. Watch: bit.ly/44eQi3u

Bringing the family to #OpenSearchCon North America (Sept 22-24, San Jose)? 👋 We're offering complimentary onsite child care for kids up to 12. RSVP by August 23. Spots are limited and late sign-ups can't be accommodated. Save your spot: bit.ly/4gS68Zc Register for the event: bit.ly/3NXhWNN

Join OpenSearch at We Are Developers World Congress EU — Hall 2 at Booth 2_16! @KrisFreedain, OpenSearch Ambassador, will be on the ground connecting with developers building search, observability, and AI-native data systems in production. Conversations will focus on scalable open data infrastructure, real-world AI use cases, and how OpenSearch is being used across modern architectures: bit.ly/4vlUxGe

Search relevance is still one of the hardest problems in AI applications. Human evaluation does not scale, and offline metrics only tell part of the story. This OpenSearch tutorial shows how to use LLM-as-a-Judge to automate relevance evaluation, generate judgments, and build a more repeatable approach to measuring search quality. A practical guide for teams building AI-powered search experiences. Learn here: bit.ly/4b4Hf8O

Keyword search served us well for decades. But when users expect to find things by meaning rather than exact match, the rules change. Four talks from OpenSearchCon India 2026 cover this shift from every angle. Karan Yadav from @Microsoft walks through building intelligent search with OpenSearch vector search. Chintan Agrawal from @AWS digs into GPU acceleration on OpenSearch 3.0 for workloads that demand real scale. OpenSearch Ambassador Jon Handler covers vector DB best practices for teams building in production. And the AWS search analysis session shows you where your pipeline is actually losing relevance. All four are now on the OpenSearch YouTube channel: bit.ly/4eSuFdV