Your task
Deploy a workload to clusters. You can specify target clusters explicitly or let kubestellar-deploy find matching clusters based on requirements.
- •Get the manifest from the user or help them create one
- •Ask about target clusters or placement requirements (GPU, memory, CPU)
- •Use
deploy_appto deploy the manifest
Parameters
- •
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 the user doesn'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
Use find_clusters_for_workload and list_cluster_capabilities to help with placement decisions.
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"
Do not use any other tools besides the kubestellar-deploy MCP tools.