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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
$ npx -y skills add awslabs/agent-plugins --skill hyperpod-ssm --agent claude-codeHow it fires
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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
name: hyperpod-ssm description: 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. metadata: version: "1.0.0"
Target: `sagemaker-cluster:<CLUSTER_ID>_<GROUP_NAME>-<INSTANCE_ID>`
Three scripts under `scripts/`. Resolve cluster info and nodes **once**, then execute per node.
scripts/get-cluster-info.sh CLUSTER_NAME [--region REGION]
# Output: {"cluster_id":"...","cluster_arn":"...","cluster_name":"...","region":"..."}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.
# 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]
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.
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| Task | Command | | ---------------- | -------------------------------------------------------------- | | Lifecycle logs | `cat /var/log/provision/provisioning.log` | | Memory | `free -h` | | Disk/mounts | `df -h && lsblk` | | GPU status | `nvidia-smi` | | GPU memory | `nvidia-smi --query-gpu=memory.used,memory.total --format=csv` | | EFA/network | `fi_info -p efa` | | CloudWatch agent | `sudo systemctl status amazon-cloudwatch-agent` | | Top processes | `ps aux --sort=-%mem \| head -20` |
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