Amazon Bedrock is a fully managed service that provides access to foundational models from leading AI providers such as Anthropic, Cohere, and Meta. It allows you to build and scale generative AI applications without managing infrastructure. Amazon CloudWatch, on the other hand, collects logs from various AWS services, enabling you to monitor and verify whether those services are operating as expected. However, these logs can often be cluttered and difficult to interpret, making it challenging to identify specific issues, such as configuration errors or failures in application logic.
In this Cloud Lab, you’ll build a simple application where a Lambda function fetches a text file from an S3 bucket, translates its content into Spanish using Amazon Translate, and stores the translated version in the same bucket. Next, you’ll enable the Claude 3 Haiku model in Amazon Bedrock and integrate it into your Lambda function to analyze the CloudWatch logs generated by your application. This analysis will help identify potential misconfigurations or unexpected behavior in your Lambda function. Finally, you’ll create a custom dashboard in CloudWatch to view the analysis provided by Amazon Bedrock. This will help you visualize the model’s insights and better understand issues detected in your application’s execution.
After completing this Cloud Lab, you’ll understand how to use Amazon Bedrock models to extract meaningful insights from Amazon CloudWatch logs, improving application observability and simplifying debugging Lambda configuration and code issues.
The following is the high-level architecture diagram of the infrastructure you’ll create in this Cloud Lab:
