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Hyperpod Ssm

AWS LabsOfficialPublished by AWS Labs

  • Skill
  • Tool integration
  • Cloud and DevOps
  • Apache-2.0
  • Low risk
  • Has scripts

From the author

Remote command execution and file transfer on SageMaker HyperPod cluster nodes via AWS Systems Manager (SSM). This is the primary interface for accessing HyperPod nodes — direct SSH is not available. Use when any skill, workflow, or user request needs to execute commands on cluster nodes, upload files to nodes, read/download files from nodes, run diagnostics, install packages, or perform any operation requiring shell access to HyperPod instances. Other HyperPod skills depend on this skill for all node-level operations.
— the description by AWS Labs

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The hyperpod-ssm skill serves as the primary interface for interacting with SageMaker HyperPod cluster nodes, as direct SSH access is unavailable. It leverages AWS Systems Manager (SSM) to facilitate remote command execution, file uploads, and file retrieval. The skill includes a set of helper scripts to resolve cluster information, list nodes, and manage SSM sessions, ensuring that users can perform diagnostics, install packages, and manage node-level operations effectively.

What it does

  • Executes shell commands on specific HyperPod cluster nodes.
  • Transfers files to and from cluster nodes.
  • Resolves cluster IDs and retrieves node lists for targeting.
  • Provides diagnostic command templates for system monitoring.
  • Handles SSM session management and output buffering requirements.

When to use it

  • When you need to run diagnostics or install packages on HyperPod nodes.
  • When you need to upload configuration files or scripts to cluster instances.
  • When you need to retrieve logs or output files from a specific node.
  • When you need to perform administrative tasks that require shell access.

Advantages

  • Enables secure, shell-level access to nodes where SSH is disabled.
  • Automates the complex target formatting required for HyperPod SSM sessions.
  • Includes built-in handling for common SSM output buffering issues.
  • Provides a consistent interface for managing large-scale cluster operations.

Usage examples

“Run nvidia-smi on all nodes in the cluster named my-cluster.”
The agent will use list-nodes.sh to identify all instances and then iterate through them using ssm-exec.sh to execute the nvidia-smi command.
“Upload a local script setup.sh to instance i-0123456789abcdef0 in my-cluster.”
The agent will resolve the target ID and use the --upload flag in ssm-exec.sh to transfer the file to the specified node.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/awslabs/hyperpod-ssm/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip hyperpod-ssm.zip -d .agents/skills

Documentation by AWS Labs

HyperPod SSM Access

Prerequisites

  • aws CLI v2, authenticated for the target account/Region.

  • session-manager-plugin — installed alongside the AWS CLI.

  • jq — the scripts build JSON payloads with it.

  • unbuffer (from the expect package) — wraps aws ssm start-session with a PTY so the session-manager-plugin flushes stdout instead of racing to close. Without it, calls intermittently return empty output with Cannot perform start session: EOF even when the command ran. Install with sudo yum install expect, sudo apt install expect, or brew install expect. ssm-exec.sh detects and uses it automatically; falls back with a warning if missing.

SSM Target Format

Target: sagemaker-cluster:<CLUSTER_ID>_<GROUP_NAME>-<INSTANCE_ID>

  • CLUSTER_ID: Last segment of cluster ARN (NOT the cluster name). Extract via get-cluster-info.sh.

  • GROUP_NAME: Instance group name — retrieve via list-nodes.sh.

  • INSTANCE_ID: EC2 instance ID (e.g., i-0123456789abcdef0)

Scripts

Three scripts under scripts/. Resolve cluster info and nodes once, then execute per node.

get-cluster-info.sh — Resolve cluster name → ID (call once)
scripts/get-cluster-info.sh CLUSTER_NAME [--region REGION]
# Output: {"cluster_id":"...","cluster_arn":"...","cluster_name":"...","region":"..."}
list-nodes.sh — List all nodes with pagination (call once)
scripts/list-nodes.sh CLUSTER_NAME [--region REGION] [--instance-group GROUP] [--instance-id ID]
# Output: JSON array of ClusterNodeSummaries (InstanceId, InstanceGroupName, InstanceStatus, etc.)

list-cluster-nodes paginates at 100 nodes. This script handles pagination automatically.

ssm-exec.sh — Execute command on a node (call per node)
# Execute — with pre-built target
scripts/ssm-exec.sh --target "sagemaker-cluster:CLUSTERID_GROUP-INSTANCEID" 'command' [--region REGION]

# Execute — with parts
scripts/ssm-exec.sh --cluster-id ID --group GROUP --instance-id INSTANCE_ID 'command' [--region REGION]

# Upload
scripts/ssm-exec.sh --target TARGET --upload LOCAL_PATH REMOTE_PATH [--region REGION]

# Read remote file
scripts/ssm-exec.sh --target TARGET --read REMOTE_PATH [--region REGION]

Running Commands Across Many Nodes

SSM start-session rate limit: 3 TPS per account. Plan batch size and delay accordingly.

aws ssm send-command does NOT support sagemaker-cluster: targets — only start-session works.

Manual SSM Commands

When the scripts aren't suitable, use aws ssm start-session directly with AWS-StartNonInteractiveCommand. Wrap every invocation in unbuffer — without it, stdout is intermittently empty (see Prerequisites).

cat > /tmp/cmd.json << 'EOF'
{"command": ["bash -c 'echo hello && whoami'"]}
EOF

unbuffer aws ssm start-session \
  --target sagemaker-cluster:{CLUSTER_ID}_{GROUP_NAME}-{INSTANCE_ID} \
  --region REGION \
  --document-name AWS-StartNonInteractiveCommand \
  --parameters file:///tmp/cmd.json
  • Always use a JSON file for --parameters — inline parameters break with special characters.

  • The document's command parameter is argv, not shell input. Wrap multi-statement scripts in bash -c '...' so pipes, semicolons, and redirects evaluate.

Common Diagnostic Commands

TaskCommand
Lifecycle logscat /var/log/provision/provisioning.log
Memoryfree -h
Disk/mountsdf -h && lsblk
GPU statusnvidia-smi
GPU memorynvidia-smi --query-gpu=memory.used,memory.total --format=csv
EFA/networkfi_info -p efa
CloudWatch agentsudo systemctl status amazon-cloudwatch-agent
Top processesps aux --sort=-%mem | head -20

Key Details

  • Default SSM non-interactive user is root.

  • SSM rate limit: 3 TPS per account.

  • For interactive sessions (rare), omit --document-name to get a shell.

  • Interactive commands (vim, top) are not supported via AWS-StartNonInteractiveCommand.

  • Large outputs may be truncated by SSM.

  • For troubleshooting common errors, see references/troubleshooting.md.

Files

NOTICE

Agent Plugins for AWS
Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Node.js

Security

What our scanner noticed· Low risk

  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
AWS Labs
Publisher
AWS Labs (Official)
Source
awslabs/agent-plugins · plugins/sagemaker-ai/skills/hyperpod-ssm · commit fbefb37
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • NOTICE (added by AutoGineer from NOTICE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download hyperpod-ssm.zip