Optimizing production agents with Amazon Bedrock AgentCore Observability
AWS Machine Learning Joshua Lacy ● Covered by 2 sources
Amazon Bedrock AgentCore Observability helps diagnose performance issues in production AI agents by identifying bottlenecks and memory problems using CloudWatch monitoring. The article provides specific CloudWatch queries and metrics to detect slow response times (e.g., P95 latency exceeding 3 seconds) and unbounded memory growth in long-running sessions, with solutions including parallelizing tool calls, optimizing prompts, and configuring memory consolidation strategies. Production best practices include setting up comprehensive instrumentation, CloudWatch alarms, and operational dashboards to proactively catch degradation before users notice it.
Why it matters
As your AI agents move from prototype to production, the challenge shifts from getting them to work to keeping them fast and efficient. Learn how to use Amazon Bedrock AgentCore Observability and Amazon CloudWatch to find performance bottlenecks and diagnose memory issues in long-running agent sessions.
