Bedrock Agent & Tools - Tracing Best practises

I understand most of bedrock agent userss will have a use case where you have implemented multiple Lambda functions with a Bedrock Agent to perform different tasks and are looking for guidance in Debugging the API calls and responses from the Agent and lambda functions.

Here are some of the approaches that we have been using and found quite effective to track and trace agents and usage of their tools

• Enable Tracing for the Agent: When invoking the agent, set the debug parameter to true. This will enable detailed tracing for the agent's execution, including the tools (Lambda functions) invoked and their responses. The trace will be printed to the console or returned as part of the agent's response, depending on how you invoke the agent. [1] Example (Python):

python result = agent.run(query, debug=True)

• Log Within Lambda Functions: Within each of your Lambda functions (tools), add logging statements to capture relevant information and events. You can use AWS Lambda's built-in logging capabilities or integrate with a centralized logging service like Amazon CloudWatch Logs. [2] Example (Python):

python import logging
logger = logging.getLogger(__name__)
def lambda_handler(event, context):
http://logger.info (f"Received event: {event}") # Your Lambda function's logic here http://
logger.info (f"Returning result: {result}") return result

• Correlate Logs Using Request IDs or Tracing IDs: To correlate logs across multiple Lambda functions and the agent, you can use request IDs or tracing IDs. Pass a unique ID as part of the event or context to your Lambda functions and include it in your log statements. This will allow you to trace the flow of events across different components of your system.


import logging
import uuid
def lambda_handler(event, context):
request_id = event.get("request_id", str(uuid.uuid4()))
logger = logging.getLogger(__name__)
logger = logging.LoggerAdapter(logger, {"request_id": request_id})
logger.info(f"Received event: {event}")
logger.info(f"Returning result: {result}")
return result


• Use AWS X-Ray for Distributed Tracing: AWS X-Ray is a service that can help you analyze and debug distributed applications, including Lambda functions. By integrating X-Ray with your Bedrock application, you can trace requests as they travel through your Lambda functions and gain insights into their performance and potential issues. [3] - Enable X-Ray tracing for your Lambda functions by adding the necessary configuration. - Instrument your Lambda functions with X-Ray tracing code to capture relevant information and events. - Use the X-Ray console or integrate with other monitoring tools to analyze the traces and identify potential bottlenecks or issues.

• Implement Advanced prompts : By using advanced prompts, you can enhance your agent's accuracy through modifying these prompt templates to provide detailed configurations. You can also provide hand-curated examples for few-shot prompting, in which you improve model performance by providing labeled examples for a specific task. [4] By combining the built-in tracing mechanism, custom logging within your Lambda functions, and distributed tracing with AWS X-Ray, you can gain better visibility into the API calls, events, and interactions happening within your Bedrock agent and its associated tools. This can help you debug issues more effectively and trace errors back to their source across multiple Lambda functions.

• Reference

  • Trace events in Amazon Bedrock - Amazon Bedrock
  • Best practices for your debugging environment - AWS Lambda
  • What is AWS X-Ray? - AWS X-Ray
  • Advanced prompts in Amazon Bedrock - Amazon Bedrock