Day 41: Ditching print() for AWS Lambda Powertools (Structured Logging)

Building my AI Financial Agent has taught me a lot about cloud infrastructure, but today I learned a crucial lesson about Observability. Up until now, I was logging custom metrics and errors using a helper function that basically did print(json.dumps(log_entry)). It worked, but it felt hacky and didn't integrate natively with AWS X-Ray or standard CloudWatch query syntax. The Upgrade Today, I stripped out the manual JSON dumping and brought in aws_lambda_powertools. Here is what changed: Context Injection: I configured the EventBridge scheduler to pass a specific JSON payload containing the user's name and ID. Global Logging State: Using the Powertools Logger, I can inject user_id at the start of the handler. Every subsequent log message, even deep inside helper functions like my Bedrock invocation, automatically includes this data. No more passing user_id around as a function argument. Dynamic Prompts: I hooked this new dynamic identity directly into the Amazon Nova prompt. The AI no