ocp-machine-management

name	ocp-machine-management
metadata	{"author":"rhoai3-demo","version":"1.0.0","platform-family":"ocp","platform-baseline":"repo","ocp-baseline":"repo","skill-group":"OpenShift Platform"}
description	Use when documenting, reviewing, or rebuilding OpenShift Container Platform machine management guidance from official OCP documentation: Machine API overview, compute machine sets, AWS compute MachineSets, provider-specific machine set fields, manual scaling, modifying machine sets, machine phases and lifecycle, deleting machines, cluster autoscaling, machine autoscaling, infrastructure machine sets, user-provisioned infrastructure machine management, control plane machine sets, control plane machine replacement, and machine health checks. Do NOT use for pod scheduling mechanics after a node exists; use ocp-nodes. Do NOT use for RHOAI hardware profiles or NVIDIA GPU Operator behavior; use rhoai-nvidia-gpu-accelerators. Do NOT run live machine operations without the env safety guard and explicit approval.

OCP Machine Management

Use this skill to ground OpenShift Machine API, compute MachineSet, autoscaling, control plane machine, and machine-health guidance in the official OpenShift Container Platform Machine management guide for the active baseline in docs/PLATFORM_BASELINE.md.

Source Grounding

Read references/source-capture.md before using product behavior. Official Red Hat documentation is product authority. This skill covers machines and machine lifecycle; it does not replace ocp-nodes for scheduling mechanics after a node exists, ocp-storage for volume behavior, or RHOAI skills for accelerator configuration.

Demo Machine Posture

For this AWS-hosted RHOAI demo:

• Use AWS compute MachineSets as the normal GitOps path for adding GPU worker capacity after the active GitOps implementation is recreated.
• For demo.redhat.com AWS GPU workers, use the Red Hat CoP GPU Operator catalog's aws-gpu-machineset component as a generation pattern only: derive from an existing worker MachineSet, then capture reviewed GPU MachineSet and MachineAutoscaler resources in Git.
• Verify the existing cluster's Machine API namespace, provider spec, failure domains, subnets, security groups, IAM/profile references, AMI/image references, labels, taints, and autoscaler annotations before authoring a new MachineSet.
• Keep exact GPU instance type, desired node count, accelerator identifier, and RHOAI hardware-profile intent aligned with rhoai-nvidia-gpu-accelerators.
• Treat scale, delete, control plane replacement, machine health checks, and autoscaler changes as live platform operations requiring the repo environment guard and explicit approval.
• Do not use MachineSets as a shortcut for pod placement; create machines here, then use ocp-nodes and RHOAI skills for scheduling and workload placement.

Machine Management Model

Use the official docs to frame:

• Machine API: OpenShift API layer for managing machine objects and provider-backed infrastructure after installation when supported.
• Compute MachineSet: manages groups of compute machines and supports scaling, labels, taints, provider-specific configuration, and special-purpose worker pools.
• Machine lifecycle: machine phases, ownership, provider state, node handoff, deletion, and replacement behavior.
• Cluster autoscaler and machine autoscaler: scale machine sets within configured limits based on pending workload demand and scale-down criteria.
• Infrastructure MachineSets: dedicated machines for infrastructure workloads when required by the cluster design.
• ControlPlaneMachineSet: automates supported control plane machine management and replacement on supported platforms.
• MachineHealthCheck: detects unhealthy machines and can trigger remediation according to the configured policy.

Workflow

1. Confirm the active OpenShift baseline in docs/PLATFORM_BASELINE.md.
2. Read references/official-doc-extraction.md.
3. Identify whether the task concerns:
   • compute MachineSet creation or modification
   • AWS provider-specific MachineSet settings
   • manual scaling or deletion
   • autoscaling with ClusterAutoscaler and MachineAutoscaler
   • infrastructure MachineSets
   • user-provisioned infrastructure
   • control plane machine sets or replacement
   • machine health checks
4. For GitOps manifests, verify the target cluster's existing machine set shape and provider spec before writing a new resource.
5. For GPU MachineSets, pair this skill with rhoai-nvidia-gpu-accelerators and keep instance type, labels, taints, replicas, and autoscaler bounds aligned with the NVIDIA/RHOAI handoff.
6. For live operations, use the repo environment guard and pair this skill with env-manage-resources, env-troubleshoot, or env-deploy-and-evaluate.
7. Validate the output with references/validation-checklist.md.

Related Skills

• Use ocp-nodes for labels, taints, node health, and pod scheduling after machines become nodes.
• Use ocp-storage for volume attachment, storage classes, and PVC behavior.
• Use ocp-node-feature-discovery for NFD-specific hardware labels.
• Use rhoai-nvidia-gpu-accelerators for GPU worker intent, accelerator labels, hardware profiles, and RHOAI/NVIDIA component handoff.
• Use project-gitops-authoring and project-manifest-review for manifests.

References

• references/source-capture.md
• references/official-doc-extraction.md
• references/validation-checklist.md
• examples/machineset-review-patterns.md