AWS solutions documentation change
Summary
Added documentation for an optional MCP Server component that enables AI-assisted analysis of load testing results through natural language interactions with tools like Amazon Q and Claude.
Security assessment
The changes introduce a new optional component (MCP Server) but don't address any security vulnerabilities. The documentation focuses on feature functionality (AI analysis of test results) without mentioning security improvements, vulnerability fixes, or security controls. No evidence of security incidents being addressed.
Diff
diff --git a/solutions/latest/distributed-load-testing-on-aws/front-end.md b/solutions/latest/distributed-load-testing-on-aws/front-end.md index c50656883..9666761b0 100644 --- a//solutions/latest/distributed-load-testing-on-aws/front-end.md +++ b//solutions/latest/distributed-load-testing-on-aws/front-end.md @@ -5 +5 @@ -Load testing APIWeb console +Load testing APIWeb consoleMCP Server (Optional) @@ -9 +9,10 @@ Load testing APIWeb console -The front end consists of a load testing API and web console you use to interact with the solution’s backend. +The front end provides the interfaces for interacting with the solution and includes: + + * A load testing API for programmatic access + + * A web console for creating, scheduling, and running performance tests + + * An optional MCP Server for AI-assisted analysis of test results and errors + + + @@ -13 +22 @@ The front end consists of a load testing API and web console you use to interact -Distributed Load Testing on AWS configures Amazon API Gateway to host the solution’s RESTful API. Users can interact with testing data securely through the included web console and RESTful API. The API acts as a "front door" for access to testing data stored in Amazon DynamoDB. You can also use the APIs to access any extended functionality you build into the solution. +Distributed Load Testing on AWS configures Amazon API Gateway to host the solution’s RESTful API. Users can interact with the load testing system securely through the included web console, RESTful API, and optional MCP Server. The API acts as a "front door" for access to testing data stored in Amazon DynamoDB. You can also use the APIs to access any extended functionality you build into the solution. @@ -23,3 +32 @@ For more information on the solution’s API, refer to the [Distributed load tes -This solution includes a web console that you can use to configure and run tests, monitor running tests, and view detailed test results. The console is a ReactJS application hosted in Amazon S3 and accessed through Amazon CloudFront. The application leverages AWS Amplify to integrate with Amazon Cognito to authenticate users. The web console also contains an option to view live data for a running test, in which it subscribes to the corresponding topic in AWS IoT Core. - -The web console is designed to demonstrate how you can interact with this load testing solution. In a production environment, we recommend customizing the web console to meet your specific needs or building your own console. +This solution includes a web console that you can use to configure and run tests, monitor running tests, and view detailed test results. The console is a ReactJS application built with [Cloudscape](https://cloudscape.design/), an open-source design system for building intuitive web applications. The console is hosted in Amazon S3 and accessed through Amazon CloudFront. The application leverages AWS Amplify to integrate with Amazon Cognito to authenticate users. The web console also contains an option to view live data for a running test, in which it subscribes to the corresponding topic in AWS IoT Core. @@ -28,0 +36,6 @@ The web console URL is the CloudFront distribution domain name which can be foun +## MCP Server (Optional) + +The optional Model Context Protocol (MCP) Server provides an additional interface for AI development tools to access and analyze load testing data through natural language interactions. This component is only deployed if you select the MCP Server option during solution deployment. + +The MCP Server enables AI agents to query test results, analyze performance metrics, and gain insights into your load testing data using tools like Amazon Q, Claude, and other MCP-compatible AI assistants. For detailed information about the MCP Server architecture and configuration, refer to [MCP Server](./MCP-Server.html) in this section. +