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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.
Hitesh Subnani is a Solutions Architect at AWS with specialized expertise in Search, Analytics, and Data Warehouse technologies. With a comprehensive background in data engineering and architecture, he brings a wealth of technical knowledge to complex cloud infrastructure challenges... Read More →
I’m an SDET who loves turning complex problems into reliable automation solutions. Curious about AI, databases, and emerging technologies, I contribute to open source, enjoy talking about AI, and believe in learning by teaching.
