mcpbeat

Hyperpod Issue Report

awslabs/hyperpod-issue-report

Generate comprehensive issue reports from HyperPod clusters (EKS and Slurm) by collecting diagnostic logs and configurations for troubleshooting and AWS Support cases. Use when users need to collect diagnostics from HyperPod cluster nodes, generate issue reports for AWS Support, investigate node failures or performance problems, document cluster state, or create diagnostic snapshots. Triggers on requests involving issue reports, diagnostic collection, support case preparation, or cluster troubleshooting that requires gathering logs and system information from multiple nodes.

20k tokens
context cost
the whole folder, loaded on every use
4
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
850
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/awslabs/agent-plugins --skill hyperpod-issue-report

The instruction itself

8 sections, as written by the author

HyperPod Issue Report

Collect diagnostic logs from HyperPod cluster nodes via SSM, store results in S3. Supports both EKS and Slurm clusters with auto-detection. Uses the bundled scripts/hyperpod_issue_report.py for reliable parallel collection.

Prerequisites

  • AWS CLI configured with permissions: sagemaker:DescribeCluster, sagemaker:ListClusterNodes, ssm:StartSession, s3:PutObject, s3:GetObject, eks:DescribeCluster
  • Python 3.8+ and uv (see uv installation docs for install options)
  • SSM Agent running on target nodes; node IAM roles need s3:GetObject/s3:PutObject on the report bucket
  • For EKS clusters: kubectl installed and configured (see Workflow step 2)

Workflow

1. Gather Information

Collect from the user:

  • Cluster identifier (required): accepts cluster name or full cluster ARN (e.g., arn:aws:sagemaker:us-west-2:123456789012:cluster/abc123)
  • AWS region (required unless extractable from ARN)
  • S3 path for report storage (required, e.g. s3://bucket/prefix). If the user doesn't have a bucket, create one (e.g., s3://hyperpod-diagnostics-<account-id>-<region>)
  • Issue description (optional)
  • Target scope: all nodes, specific instance groups, or specific node IDs (optional)
  • Additional commands to run on nodes (optional)

2. Verify Environment

aws sts get-caller-identity
aws sagemaker describe-cluster --cluster-name <name-or-arn> --region <region>

If the S3 bucket doesn't exist, create it:

aws s3 mb s3://<bucket-name> --region <region>

For EKS clusters (check Orchestrator.Eks in describe-cluster output):

  • Ensure kubectl is installed (which kubectl). If missing, install it for the current platform.
  • Configure kubeconfig using the EKS cluster name from the describe-cluster response:
   aws eks update-kubeconfig --name <eks-cluster-name> --region <region>

3. Run the Collection Script

uv run scripts/hyperpod_issue_report.py \
  --cluster <cluster-name-or-arn> \
  --region <region> \
  --s3-path s3://<bucket>[/prefix]

Use --help for all options including --instance-groups, --nodes, --command, --max-workers, and --debug. Note: --instance-groups and --nodes are mutually exclusive. Node identifiers accept instance IDs (i-*), EKS names (hyperpod-i-*), or Slurm names (ip-*).

4. Present Results

After collection, the script shows statistics and offers interactive download. Report the S3 location and offer to:

  • Download the report locally
  • Help analyze collected diagnostics (see references/collection-details.md for what's in each file)
  • Prepare a summary for AWS Support

Troubleshooting

See references/troubleshooting.md for error handling, large cluster tuning, and known limitations.

How to use it

Copy the folder

Take awslabs/hyperpod-issue-report from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.