介绍
# Cluster API Lifecycle Management
使用 kubectl-mcp-server 的 Cluster API 工具（11 个工具）管理 Kubernetes 集群。
## 检查安装
```python capi_detect_tool() ```
## 列出集群
```python # List all CAPI clusters capi_clusters_list_tool(namespace="default")
# Shows: # - Cluster name # - Phase (Provisioning, Provisioned, Deleting) # - Infrastructure ready # - Control plane ready ```
## 获取集群详情
```python capi_cluster_get_tool(name="my-cluster", namespace="default")
# Shows: # - Spec (control plane, infrastructure) # - Status (phase, conditions) # - Network configuration ```
## 获取集群 Kubeconfig
```python # Get kubeconfig for workload cluster capi_cluster_kubeconfig_tool(name="my-cluster", namespace="default")
# Returns kubeconfig to access the cluster ```
## 机器
### 列出机器
```python capi_machines_list_tool(namespace="default")
# Shows: # - Machine name # - Cluster # - Phase (Running, Provisioning, Failed) # - Provider ID # - Version ```
### 获取机器详情
```python capi_machine_get_tool(name="my-cluster-md-0-xxx", namespace="default") ```
## 机器部署
### 列出机器部署
```python capi_machinedeployments_list_tool(namespace="default")
# Shows: # - Deployment name # - Cluster # - Replicas (ready/total) # - Version ```
### 扩缩机器部署
```python # Scale worker nodes capi_machinedeployment_scale_tool( name="my-cluster-md-0", namespace="default", replicas=5 ) ```
## 机器集
```python capi_machinesets_list_tool(namespace="default") ```
## 机器健康检查
```python capi_machinehealthchecks_list_tool(namespace="default")
# Health checks automatically remediate unhealthy machines ```
## 集群类
```python # List cluster templates capi_clusterclasses_list_tool(namespace="default")
# ClusterClasses define reusable cluster configurations ```
## 创建集群
```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 """) ```
## 创建机器部署
```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 """) ```
## 集群生命周期工作流
### 置备新集群 ```python 1. kubectl_apply(cluster_manifest) 2. capi_clusters_list_tool(namespace) # Wait for Provisioned 3. capi_cluster_kubeconfig_tool(name, namespace) # Get access ```
### 扩缩工作节点 ```python 1. capi_machinedeployments_list_tool(namespace) 2. capi_machinedeployment_scale_tool(name, namespace, replicas) 3. capi_machines_list_tool(namespace) # Monitor ```
### 升级集群 ```python 1. # Update control plane version 2. # Update machine deployment version 3. capi_machines_list_tool(namespace) # Monitor rollout ```
## 故障排查
### 集群卡在置备中
```python 1. capi_cluster_get_tool(name, namespace) # Check conditions 2. capi_machines_list_tool(namespace) # Check machine status 3. get_events(namespace) # Check events 4. # Check infrastructure provider logs ```
### 机器失败
```python 1. capi_machine_get_tool(name, namespace) 2. get_events(namespace) 3. # Common issues: # - Cloud provider quota # - Invalid machine template # - Network issues ```
## 相关技能
- [k8s-multicluster](../k8s-multicluster/SKILL.md) - 多集群操作 - [k8s-operations](../k8s-operations/SKILL.md) - kubectl 操作