Using the Troubleshooting Agent - Amazon EMR
Supported Deployment ModesSupported Interfaces

Using the Troubleshooting Agent

Supported Deployment Modes

Apache Spark Troubleshooting Agent for Amazon EMR supports comprehensive analysis capabilities for failed Spark workloads, including automated error diagnosis, performance bottleneck identification, code recommendations and actionable suggestions for improved application performance for the following Spark deployment mode:

  • EMR on EC2

  • EMR Serverless

  • AWS Glue

Please refer to Features and Capabilities to understand the detailed features, capacities and limitations.

Supported Interfaces

Troubleshooting Cells within Amazon SageMaker Notebooks

A demonstration of troubleshooting experience with Amazon SageMaker Notebooks. For any Notebook cell failure, you can ask the Amazon SageMaker Notebook Agent to troubleshoot the failure to request the analysis followed by possible code fix if the error resulted from code, by clicking the Fix with AI button.

Troubleshooting Glue and EMR Spark applications with Kiro CLI

Start Kiro CLI or your AI Assistant and verify the loaded tools for the troubleshooting process.


...
 sagemaker-unified-studio-mcp-code-rec (MCP)
 - spark_code_recommendation    not trusted
 
 sagemaker-unified-studio-mcp-troubleshooting (MCP)
 - analyze_spark_workload       not trusted
...

Now you are ready to start the Spark troubleshooting agent workflow.

A demonstration of the troubleshooting experience with Kiro CLI. You can simply start the Troubleshooting process with the following prompt:


Analyze my Glue job. The job name is "xxx" and the job run id is "xxx"

Integration With Other MCP Clients

The configuration described in Setup for Troubleshooting Agent can also be used in other MCP Clients and IDEs to connect to the Managed MCP server:

  • Integration With Cline - To use the MCP Server with Cline, modify the cline_mcp_settings.json and add the configuration above. Consult Cline's documentation for more information on how to manage MCP configuration.

  • Integration With Claude Code To use the MCP Server with Claude Code, modify the configuration file to include the MCP configuration. The file path varies depending on your operating system. Refer to https://code.claude.com/docs/en/mcp for detailed setup.

  • Integration With GitHub Copilot - To use the MCP server with GitHub Copilot, follow the instruction in https://docs.github.com/en/copilot/how-tos/provide-context/use-mcp/extend-copilot-chat-with-mcp to modify the corresponding configuration file and follow the instructions per each IDE to activate the setup.