Source: kubestellar/kubestellar-mcp/commands/deploy.md

Deploy

Deploy an app to multiple clusters with smart placement.

Usage

Deploy a workload to clusters. You can specify target clusters explicitly or let kubestellar-deploy find matching clusters based on requirements.

Examples

• “Deploy this nginx deployment to all clusters”
• “Deploy my ML model to clusters with GPUs”
• “Deploy this app to clusters with at least 16Gi memory”
• “Do a dry run of deploying this manifest”

What it does

1. Finds clusters matching your requirements (or uses all clusters)
2. Applies the manifest to each target cluster
3. Reports success/failure per cluster

MCP Tools Used

• deploy_app - Deploy an app to clusters
• find_clusters_for_workload - Find clusters matching requirements
• list_cluster_capabilities - See what each cluster can run

Implementation

Use the deploy_app tool with:

• manifest: The Kubernetes YAML manifest
• clusters: Optional list of target clusters
• gpu_type: Optional GPU type requirement (e.g., “nvidia.com/gpu”)
• min_gpu: Optional minimum GPU count
• dry_run: Set to true to preview without applying

Smart Placement

If you don’t specify clusters, kubestellar-deploy can:

• Deploy to all clusters
• Filter to clusters with specific GPU types
• Filter to clusters with minimum CPU/memory
• Filter to clusters with specific node labels