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This conference talk explores how to transform Kubernetes logs into actionable insights using generative AI for more efficient troubleshooting. Learn how to build an AI-driven observability solution that addresses the challenge of sifting through massive volumes of logs in distributed microservices environments. The presenters, Tiago Reichert and Lucas Duarte from AWS, demonstrate a step-by-step approach to implementing a conversational troubleshooting system using Large Language Models (LLMs). Discover how to configure Fluent Bit collectors to gather systemd logs, Kubernetes events, and application logs, stream them to scalable object storage, and construct a vector database that enables natural language interaction with log data. Gain practical knowledge to implement GenAI observability in your own Kubernetes clusters, reducing downtime and simplifying the troubleshooting process across multiple clusters.
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