Kubernetes Skills

# Cluster API Lifecycle Management

Manage Kubernetes clusters using kubectl-mcp-server's Cluster API tools (11 tools).

Check Installation

```python capi_detect_tool() ```

List Clusters

```python # List all CAPI clusters capi_clusters_list_tool(namespace="default")

# Shows: # - Cluster name # - Phase (Provisioning, Provisioned, Deleting) # - Infrastructure ready # - Control plane ready ```

Get Cluster Details

```python capi_cluster_get_tool(name="my-cluster", namespace="default")

# Shows: # - Spec (control plane, infrastructure) # - Status (phase, conditions) # - Network configuration ```

Get Cluster Kubeconfig

```python # Get kubeconfig for workload cluster capi_cluster_kubeconfig_tool(name="my-cluster", namespace="default")

# Returns kubeconfig to access the cluster ```

Machines

List Machines

```python capi_machines_list_tool(namespace="default")

# Shows: # - Machine name # - Cluster # - Phase (Running, Provisioning, Failed) # - Provider ID # - Version ```

Get Machine Details

```python capi_machine_get_tool(name="my-cluster-md-0-xxx", namespace="default") ```

Machine Deployments

List Machine Deployments

```python capi_machinedeployments_list_tool(namespace="default")

# Shows: # - Deployment name # - Cluster # - Replicas (ready/total) # - Version ```

Scale Machine Deployment

```python # Scale worker nodes capi_machinedeployment_scale_tool( name="my-cluster-md-0", namespace="default", replicas=5 ) ```

Machine Sets

```python capi_machinesets_list_tool(namespace="default") ```

Machine Health Checks

```python capi_machinehealthchecks_list_tool(namespace="default")

# Health checks automatically remediate unhealthy machines ```

Cluster Classes

```python # List cluster templates capi_clusterclasses_list_tool(namespace="default")

# ClusterClasses define reusable cluster configurations ```

Create Cluster

```python kubectl_apply(manifest=""" apiVersion: cluster.x-k8s.io/v1beta1 kind: Cluster metadata: name: my-cluster namespace: default spec: clusterNetwork: pods: cidrBlocks: - 192.168.0.0/16 services: cidrBlocks: - 10.96.0.0/12 controlPlaneRef: apiVersion: controlplane.cluster.x-k8s.io/v1beta1 kind: KubeadmControlPlane name: my-cluster-control-plane infrastructureRef: apiVersion: infrastructure.cluster.x-k8s.io/v1beta1 kind: AWSCluster name: my-cluster """) ```

Create Machine Deployment

```python kubectl_apply(manifest=""" apiVersion: cluster.x-k8s.io/v1beta1 kind: MachineDeployment metadata: name: my-cluster-md-0 namespace: default spec: clusterName: my-cluster replicas: 3 selector: matchLabels: cluster.x-k8s.io/cluster-name: my-cluster template: spec: clusterName: my-cluster version: v1.28.0 bootstrap: configRef: apiVersion: bootstrap.cluster.x-k8s.io/v1beta1 kind: KubeadmConfigTemplate name: my-cluster-md-0 infrastructureRef: apiVersion: infrastructure.cluster.x-k8s.io/v1beta1 kind: AWSMachineTemplate name: my-cluster-md-0 """) ```

Cluster Lifecycle Workflows

Provision New Cluster ```python 1. kubectl_apply(cluster_manifest) 2. capi_clusters_list_tool(namespace) # Wait for Provisioned 3. capi_cluster_kubeconfig_tool(name, namespace) # Get access ```

Scale Workers ```python 1. capi_machinedeployments_list_tool(namespace) 2. capi_machinedeployment_scale_tool(name, namespace, replicas) 3. capi_machines_list_tool(namespace) # Monitor ```

Upgrade Cluster ```python 1. # Update control plane version 2. # Update machine deployment version 3. capi_machines_list_tool(namespace) # Monitor rollout ```

Troubleshooting

Cluster Stuck Provisioning

1. ```python
2. capi_cluster_get_tool(name, namespace) # Check conditions
3. capi_machines_list_tool(namespace) # Check machine status
4. get_events(namespace) # Check events
5. # Check infrastructure provider logs
6. ```

Machine Failed

1. ```python
2. capi_machine_get_tool(name, namespace)
3. get_events(namespace)
4. # Common issues:
5. # - Cloud provider quota
6. # - Invalid machine template
7. # - Network issues
8. ```

Related Skills

• k8s-multicluster - Multi-cluster operations
• k8s-operations - kubectl operations