Build a tool to detect outdated applications with Amazon Bedrock

This blog details how to use Amazon Bedrock to create an intelligent system for detecting and managing outdated applications and modules.

Many organizations struggle with keeping their software up-to-date across large, distributed systems. Manual monitoring is time-consuming and error-prone, while existing automated solutions often lack the context needed for informed decision-making. Below solution that not only detects outdated software but also provides intelligent, actionable insights for remediation.

This solution combines several AWS services, including CloudWatch, Lambda, Bedrock, and SNS, to create a fully automated update management system. Here's how I built it, step by step, using Amazon Bedrock's Claude model to guide my development process.

I began by outlining the basic structure of my system. Using Bedrock, I prompted:

Claude provided a high-level overview and sample Python code for a Lambda function that crawls CloudWatch logs, searches for patterns indicating outdated modules, and sends notifications via SNS.

To make my system more intelligent, I asked Claude to refine the solution:

To better understand how the system would work in practice, I requested sample inputs and outputs:

Claude provided example CloudWatch log messages and a detailed sample output from the Bedrock analysis. This helped us visualize the end-to-end process and the level of detail my system could provide to administrators.

To clarify the system's architecture, I asked Claude to create a diagram:

While Claude can't generate images directly, it provided a detailed text description of the system flow, which I used to create a visual diagram. This step was crucial for understanding and communicating the system's components and their interactions.

The output is below

Finally, to position my solution effectively, I asked Claude to assume the role of an AWS Solutions Architect:

Claude provided a comprehensive introduction that outlined the challenges addressed by my solution and its specific benefits to AWS customers. This helped frame the solution in the context of real-world cloud management challenges.

The heart of my solution is a Lambda function that periodically scans CloudWatch logs for indications of outdated software. When potential issues are detected, it leverages the Claude model in Amazon Bedrock to perform an in-depth analysis. Here's a key excerpt from my Lambda function:

This function sends detected log messages to Bedrock for analysis, receiving in return a detailed report that includes confirmation of outdated status, explanation of update importance, step-by-step resolution instructions, and additional recommendations.

Sample Input (CloudWatch Log Messages):

These log messages would be detected by my Lambda function. The function would then send these to Bedrock for analysis. Here's what the output might look like:

Sample Output (Bedrock Analysis):

Fully functioning CloudFormation template with the solution, generated using Amazon Bedrock (no coding required)

The full code solution with implementation guide is posted on my GitHub here: https://github.com/johncattrall/intelligent-application-update-management-system

By leveraging Amazon Bedrock and other AWS services, I've created an intelligent system that not only detects outdated software but provides contextual, actionable information for remediation. This solution demonstrates the power of combining traditional cloud services with AI capabilities to solve complex operational challenges.

I encourage you to explore how you can integrate similar AI-powered solutions into your own AWS environments. The possibilities are endless, and I'm excited to see what you'll build next!

This blog post outlines the development process, highlighting how Amazon Bedrock was used at each step to guide the creation of the solution. It provides a mix of high-level overview and technical details, making it suitable for a wide range of AWS blog readers.