OpenSearchCon India 2026

We want to show that a fully open-source log management stack (OpenSearch + Data Prepper + OpenSearch Dashboards) can run at ~400TB-per-day scale with few extensions. We hope to get feedback from others running ODD at scale, exchange patterns for plugin development and operations, and encourage more teams to adopt and contribute to the ODD ecosystem.

It details a massive ODD deployment utilizing ~1,500 OpenSearch nodes to handle 6 GB/s data volume. Key takeaways are Extensibility (Pluggable data prepper), Cost Efficiency (S3 remote snapshots as cold storage), and Open Source Commitment (using official OpenSearch ecosystem). Attendees will grasp ODD scaling and extension potential.

It showcases how the ODD stack manages high-throughput pipelines and multi-datasource UIs, reducing reliance on proprietary vendors. It presents extension patterns using Data Prepper and OSD plugins for custom observability (RUM, synthetics, traces, profiles, alerts). This promotes open source observability through a reusable reference architecture and operational patterns, encouraging OpenSearch ecosystem adoption and contribution.

Description
Join us to explore the latest performance improvements in OpenSearch, highlighting the integration of Lucene’s bulk collection API and enhancements to the gRPC Search API. This session will dive into how bulk collection optimizes aggregation execution, delivering measurable gains across analytical workloads by batching operations and reducing computational overhead. We will also cover the expanded features of the gRPC Search API in OpenSearch 3.4, which now supports new query types, improved bulk requests, and multiple document formats. To make these concepts clear and practical, we will showcase live demos illustrating performance boosts in aggregation workloads and expanded query handling through gRPC. Attendees will gain a clear understanding of how these advancements significantly enhance efficiency and broaden query capabilities in real‑world use cases. Key takeaways include understanding Lucene’s bulk collection benefits, learning about new gRPC query types, and discovering improvements in bulk request handling and document format support.

This session explores how to build a comprehensive code security platform using OpenSearch's powerful analytics capabilities enhanced with AI agentic workflows. I'll demonstrate how to implement a system that continuously monitors, analyzes, and remediates security vulnerabilities across your codebase. Attendees will learn how to leverage OpenSearch for storing and analyzing code security telemetry, while implementing agentic AI workflows that autonomously identify patterns, prioritize vulnerabilities, and suggest remediation strategies.

Key topics include:
• Configuring OpenSearch for efficient storage and querying of code security data
• Implementing vector search to identify similar vulnerability patterns across repositories
• Building AI agents that autonomously scan, analyze, and classify security issues
• Creating agentic workflows that coordinate specialized security analysis tasks
• Developing automated remediation suggestions using LLM-powered agents
• Visualizing security insights through OpenSearch Dashboards

This session provides a practical blueprint for security teams looking to scale their code security.

Large Language Models (LLMs) power some of today’s most advanced AI applications-from chatbots to intelligent copilots-yet monitoring their complex behavior remains a major challenge. This session demonstrates how OpenTelemetry’s auto-instrumentation capabilities, combined with OpenSearch’s powerful analytics, provide end-to-end observability for LLM-based systems.

You’ll learn how to automatically collect rich telemetry data-traces, metrics, and logs-from your LLM applications with minimal manual effort using OpenTelemetry and libraries like OpenLIT. See how this data flows into OpenSearch, enabling real-time analysis, anomaly detection, and performance monitoring tailored specifically for AI workloads.

By the end of this talk, you will get the tools and best practices to build scalable, AI-driven observability pipelines that keep your LLM applications reliable and performant.