Use this skill whenever the user needs to manage vSphere Kubernetes Service (VKS) — Supervisor clusters, vSphere Namespaces, and TKC cluster lifecycle. Directly handles: check VKS compatibility, create/delete namespaces, create/scale/upgrade/delete TKC clusters, get kubeconfig, check Harbor registry. Always use this skill for "create Kubernetes cluster", "scale workers", "upgrade K8s version", "create namespace", "get kubeconfig", or any VKS/TKC task. Do NOT use for vanilla VM operations (use vmware-aiops), non-vSphere Kubernetes (e.g., kubeadm, EKS, AKS), or AVI/AKO load balancing (use vmware-avi). For networking use vmware-nsx.
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Use this skill whenever the user needs to manage vSphere Kubernetes Service (VKS) — Supervisor clusters, vSphere Namespaces, and TKC cluster lifecycle. Directly handles: check VKS compatibility, create/delete namespaces, create/scale/upgrade/delete TKC clusters, get kubeconfig, check Harbor registry. Always use this skill for "create Kubernetes cluster", "scale workers", "upgrade K8s version", "create namespace", "get kubeconfig", or any VKS/TKC task. Do NOT use for vanilla VM operations (use vmware-aiops), non-vSphere Kubernetes (e.g., kubeadm, EKS, AKS), or AVI/AKO load balancing (use vmware-avi). For networking use vmware-nsx.
vmware-policy auto-installed as Python dependency (provides @vmware_tool decorator and audit logging). All write operations audited to ~/.vmware/audit.db (SQLite, via vmware-policy) with a local JSON-Lines mirror at ~/.vmware-vks/audit.log. Credentials: Each vCenter target requires a per-target password env var in ~/.vmware-vks/.env following the pattern VMWARE_VKS_<TARGET_NAME_UPPER>_PASSWORD (e.g., target "vcenter-01" → VMWARE_VKS_VCENTER_01_PASSWORD). Passwords are never logged, never echoed, never included in audit entries. Kubeconfig tokens returned by get_supervisor_kubeconfig and get_tkc_kubeconfig are short-lived vCenter session tokens, not persistent credentials.
VMware VKS
Disclaimer: This is a community-maintained open-source project and is not affiliated with, endorsed by, or sponsored by VMware, Inc. or Broadcom Inc. "VMware" and "vSphere" are trademarks of Broadcom. Source code is publicly auditable at github.com/zw008/VMware-VKS under the MIT license.
Supervisor must be vSphere 8.x+ with WCP enabled — supervisor check returns pass/fail. If fail, no amount of TKC commands will work; resolve at vSphere/WCP layer first.
K8s version: pick a TKR version that's still supported by VMware (not EOL). New clusters on EOL versions look fine until you need a CVE patch and there isn't one.
VM class sizing: best-effort-* for dev, guaranteed-* for prod. A best-effort worker can be evicted under host pressure — production workloads need guaranteed.
Storage policy: must already exist in vCenter. list_supervisor_storage_policies first and pass the returned policy ID (not the display name); creating a TKC against a missing policy fails after CP boot, leaving partial state.
Control-plane count: 1 for dev, 3 for prod (HA). Cannot upgrade from 1→3 without recreating; choose right the first time.
Namespace quota: TKC consumes CP + worker × (cpu, memory) from namespace quota. If quota is too tight, workers fail to schedule with no obvious error.
TKC API version: auto-detected at runtime via the K8s discovery API (prefers cluster.x-k8s.io/v1 when the Supervisor serves it, falls back to v1beta1 on vSphere 8.0). No manual selection needed; advanced callers can override via the api_version parameter on generate_tkc_yaml().
Steps:
vmware-vks supervisor check --target prod → must pass
vmware-vks tkc versions -n <ns> → pick a non-EOL TKR
(If new namespace) vmware-vks namespace create dev --storage-policy <policy> --cpu <enough-for-cp+workers> --apply --dry-run then real
vmware-vks tkc create dev-cluster -n dev --version <tkr> --control-plane 1 --workers 3 --vm-class best-effort-large --apply --dry-run then real
Wait for phase=running (typically 10-15 min); do not assume success on apply return
vmware-vks kubeconfig get dev-cluster -n dev -o ./kubeconfig — write to file, do not paste tokens into the agent context
Scale Workers for Load Testing
Judgment: scaling is fast but reverse-scaling is destructive — workers are deleted, in-flight pods lost. Treat scale-down like a delete.
tkc get dev-cluster -n dev → record current worker count and any pending pods
Verify new workers reach Ready in kubectl get nodes before sending traffic
Scale-down: drain pods first via kubectl drain on the to-be-deleted nodes, THEN tkc scale --workers 3. Skipping drain causes pod restarts on remaining nodes — measurable user impact.
Confirm namespace quota leftover supports the new size — quota is enforced at scheduling, not at scale request
Namespace Resource Management
Judgment: quota changes are atomic but consequences are not. Reducing quota below current usage doesn't evict pods — they keep running, but no new pods schedule, looking like a "namespace is broken" symptom.
namespace list → see all namespaces and their phase
storage -n dev → check current CPU/memory/storage usage; never reduce quota below current usage + 20% headroom
namespace update dev --cpu <new> --memory <new> --dry-run → preview, then real
Validate by attempting a small pod scale-up; if it pends with Insufficient cpu, quota is still the bottleneck
Architecture
User (Natural Language)
↓
AI Agent (Claude Code / Goose / Cursor)
↓ reads SKILL.md
↓
vmware-vks CLI ─── or ─── vmware-vks MCP Server (stdio)
│
├─ Layer 1: pyVmomi → vCenter REST API
│ Supervisor status, storage policies, Namespace CRUD, VM classes, Harbor
│
└─ Layer 2: kubernetes client → Supervisor K8s API endpoint
TKC CR apply / get / delete (cluster.x-k8s.io/v1beta1)
Kubeconfig bearer token from POST /wcp/login (Supervisor JWT)
↓
vCenter Server 8.x+ (Workload Management enabled)
↓
Supervisor Cluster → vSphere Namespaces → TanzuKubernetesCluster
Usage Mode
Scenario
Recommended
Why
Local/small models (Ollama, Qwen)
CLI
~2K tokens vs ~8K for MCP
Cloud models (Claude, GPT-4o)
Either
MCP gives structured JSON I/O
Automated pipelines
MCP
Type-safe parameters, structured output
MCP Tools (20 — 13 read, 7 write)
All accept optional target parameter to specify a named vCenter.
list_namespaces, list_supervisor_storage_policies and list_vm_classes return the family
list envelope — {items, returned, limit, total, truncated, hint} — rather than a bare array.
Read the rows from items; truncated says whether the listing is complete, so it never has
to be guessed from the row count. These three read their collection in one un-paged call, so
total is the real count and truncated is always false.
Category
Tool
Type
Supervisor
check_vks_compatibility
Read
get_supervisor_status
Read
list_supervisor_storage_policies
Read
Namespace
list_namespaces
Read
get_namespace
Read
create_namespace
Write
update_namespace
Write
delete_namespace
Write
list_vm_classes
Read
TKC
list_tkc_clusters
Read
get_tkc_cluster
Read
get_tkc_available_versions
Read
create_tkc_cluster
Write
scale_tkc_cluster
Write
upgrade_tkc_cluster
Write
delete_tkc_cluster
Write
Access
get_supervisor_kubeconfig
Read
get_tkc_kubeconfig
Read
get_harbor_info
Read
list_namespace_storage_usage
Read
create_namespace / create_tkc_cluster — defaults to dry_run=True, returns a YAML plan for review. Pass dry_run=False to apply.
delete_namespace — requires confirmed=True and rejects if TKC clusters still exist (prevents orphaned clusters).
delete_tkc_cluster — requires confirmed=True and checks for running workloads. Rejects if found unless force=True.
Credential handling: get_supervisor_kubeconfig and get_tkc_kubeconfig return short-lived session tokens (not long-lived credentials). Tokens are derived from the authenticated vCenter session and expire when the session ends. Kubeconfig output is intended for local kubectl use — agents should write it to a file (-o <path>) rather than displaying tokens in conversation context.
Full capability details and safety features: see references/capabilities.md
Full CLI reference with all flags and interactive creation: see references/cli-reference.md
Troubleshooting
"VKS not compatible" error
Workload Management must be enabled in vCenter. Check: vCenter UI → Workload Management. Requires vSphere 8.x+ with Enterprise Plus or VCF license.
Namespace creation fails with "storage policy not found"
List policies first: vmware-vks supervisor storage-policies, then pass the Policy ID column value (not the display name) as --storage-policy.
TKC cluster stuck in "Creating" phase
Check Supervisor events in vCenter. Common causes: insufficient resources on ESXi hosts, network issues with NSX-T, or storage policy not available on target datastore.
Validating Supervisor auth (POST /wcp/login)
Supervisor/TKC Kubernetes auth uses a JWT obtained from POST https://<vcenter>/wcp/login (HTTP Basic → JSON session_id bearer token), not the pyVmomi SOAP session key. To validate this end-to-end against your real Supervisor, run:
vmware-vks preflight-auth [--target <name>]
It performs the real login (no mocks) and reports, per target: vCenter reachable → /wcp/login HTTP status → parseable session_id → does the JWT authenticate a trivial Supervisor K8s API call. A healthy result is all four steps ✓ PASS ending in target '<name>': /wcp/login auth flow validated end-to-end. (exit code 0). On failure each step prints a teaching message — e.g. a 404 on /wcp/login means the endpoint path differs on your Supervisor version (capture the real path), a 401 on the K8s probe means session_id is not the bearer token on your version. It never tracebacks — every failure is status output.
Kubeconfig retrieval fails
Supervisor API endpoint must be reachable from the machine running vmware-vks. Check firewall rules for port 6443.
Scale operation has no effect
Verify the cluster is in "Running" phase before scaling. Clusters in "Creating" or "Updating" phase reject scale operations.
Delete namespace rejected unexpectedly
The namespace delete guard prevents deletion when TKC clusters exist inside. Delete all TKC clusters in the namespace first, then retry.
In-memory kubeconfig (v1.5.18+): kubeconfig for the Supervisor and TKC clusters — which embeds the vCenter session bearer token — is built as a Python dict and loaded into the kubernetes client via load_kube_config_from_dict(). The token never touches disk during normal MCP/CLI flow, eliminating the previous temp-file TOCTOU window. The explicit kubeconfig get -o <path> CLI export still writes to the user-chosen path for kubectl use.
vmware-policy is automatically installed as a dependency — no manual setup needed.
