Monitor on-premises and multi-cloud AI agents with AgentCore Observability

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When you deploy AI agents built with frameworks like Strands Agents, LangGraph, and CrewAI, you need observability into their performance. This holds true whether they run on Amazon Elastic Kubernetes Service (Amazon EKS), Amazon Elastic Container Service (Amazon ECS), AWS Lambda, on-premises, or another cloud provider such as Google Cloud Platform (GCP) or Microsoft Azure. Amazon Bedrock AgentCore is a platform to build, connect, and optimize agents at scale, with any framework or model. Although Amazon Bedrock AgentCore Observability, a capability of Amazon Bedrock AgentCore, provides native tracing, monitoring, and analytics that local cloud monitoring tools don’t offer out of the box, it natively supports only agents deployed on AgentCore runtime in the AWS Cloud. If your agents run anywhere else, you need additional configuration to send telemetry to the dashboard. In this post, we show you how to set up observability for agents running outside AWS. You learn how to configure the AWS Distro for OpenTelemetry (ADOT) auto-instrumentation in non-AWS environments, route telemetry to the AgentCore Observability dashboard, and validate the setup end to end. The following diagram shows the end-to-end observability pipeline and how telemetry flows from agents to the AgentCore Observability dashboard.

Figure 1: End-to-end observability pipeline from agents to the AgentCore Observability dashboard Solution overview The solution uses the AWS Distro for OpenTelemetry (ADOT) running in-process with the agent application. ADOT auto-instruments the agent framework and …

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• Originalquelle / Hersteller-Advisory lesen: https://aws.amazon.com/blogs/machine-learning/monitor-on-premises-and-multi-cloud-ai-agents-with-agentcore-observability/
• Verfügbaren Patch oder Workaround einspielen und dokumentieren.