Prompt refinement and Lambda optimization strategies

This lesson explores observability and continuous improvement for Amazon Bedrock Agents. You’ll learn how to monitor performance, analyze logs, and implement feedback loops to enhance reliability and cost efficiency.

Intended audience

• Site Reliability Engineers (SREs)

• Cloud Operations Managers

• AI Product Owners

• Data Analysts

Learning objectives

By the end of this lesson, you’ll have the knowledge and skills you need to:

• Implement monitoring for agent activity and performance using Amazon CloudWatch.

• Log and analyze Bedrock model invocation data.

• Identify optimization opportunities based on usage metrics.

• Apply human-in-the-loop feedback cycles to improve reasoning accuracy and reliability.

Prerequisites

• Foundational understanding of AWS services (IAM, CloudWatch, Lambda).

• Basic familiarity with Amazon Bedrock.

• Experience deploying cloud applications and using monitoring/logging tools.

• Some knowledge of agentic AI workflows.