newsAWS Machine LearningTrust 88 · LabPublished 4d agoLive · 4d ago
Debugging production agents with Amazon Bedrock AgentCore Observability
In this post, you learn how to debug production agent failures using built-in observability capabilities. We walk through common failure patterns, show how to analyze agent behavior with traces and metrics, and provide structured workflows for resolving issues such as infinite loops and tool invocation failures. This is Part 1 of a two-part series. Part 2 covers performance optimization and memory management.
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paperA Multi-Dataset Benchmark for Evaluating LLM Agents in Microservice Failure DiagnosispaperEntity Binding Failures in Tool-Augmented AgentspaperTraceLab: Characterizing Coding Agent Workloads for LLM ServingpaperSWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction Testsrepoawslabs/fullstack-solution-template-for-agentcorerepotrpc-group/trpc-agent-gorepolitefuse/litefuse
Related across the graph
paperTraceLab: Characterizing Coding Agent Workloads for LLM Servingrepotrpc-group/trpc-agent-gorepoawslabs/fullstack-solution-template-for-agentcorerepolitefuse/litefusepaperA Multi-Dataset Benchmark for Evaluating LLM Agents in Microservice Failure DiagnosispaperEntity Binding Failures in Tool-Augmented AgentspaperSWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction TeststoolAgentTrace
