据 AlphaMoat 统计,截至 2026-09,Kubernetes Skills 累计下载 3,460 次、获 2 个星标,在全部 5,078 个 AI 技能中排名第 3,206 位,在「运维安全」分类(264 个)中排名第 207 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 102 | 3,126 | 1 | - |
| SkillHub ↗ | 101 | 3,460 | 2 | — |
各平台的计数口径不同,统计时间不一致。
可检查集群、机器和部署状态,获取工作负载集群 kubeconfig,并规划集群创建、工作节点扩缩和版本升级。应用 manifest、改变副本数或升级可能影响工作负载和基础设施成本;kubeconfig 含访问凭据。执行前应核对目标集群、配置和变更范围。
资料发布于 2026-10-29
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 3,460 | — | 2 |
| 2026-08 | 3,171 | +7.4% | 2 |
| 2026-07 | 2,953 | +9.5% | 2 |
| 2026-06 | 2,697 | +4.9% | 1 |
| 2026-05 | 2,570 | — | 2 |
| 2026-03 | 2,041 | — | 1 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
--- name: k8s-capi description: Cluster API lifecycle management for provisioning, scaling, and upgrading Kubernetes clusters. Use when managing cluster infrastructure or multi-cluster operations. license: MIT-0 metadata: author: rohitg00 version: "2.0.0" tools: 13 category: infrastructure ---
# Cluster API Lifecycle Management
Manage Kubernetes clusters using kubectl-mcp-server's Cluster API tools (11 tools).
> Requires the `capi` toolset: start kubectl-mcp-server with `--toolsets default,capi` (or `MCP_TOOLSETS=default,capi`).
## When to Apply
Use this skill when:
- User mentions: "Cluster API", "CAPI", "cluster lifecycle", "machine", "workload cluster"
- Operations: provisioning clusters, scaling nodes, upgrading Kubernetes versions
- Keywords: "provision cluster", "scale workers", "machine deployment", "cluster class"
## Priority Rules
| Priority | Rule | Impact | Tools |
|----------|------|--------|-------|
| 1 | Detect CAPI installation first | CRITICAL | `detect_ecosystem` |
| 2 | Check cluster phase before operations | HIGH | `capi_get_cluster` |
| 3 | Monitor machines during scaling | HIGH | `capi_list_machines` |
| 4 | Get kubeconfig after provisioning | MEDIUM | `capi_get_cluster_kubeconfig` |
## Quick Reference
| Task | Tool | Example |
|------|------|---------|
| Detect CAPI | `detect_ecosystem` | `detect_ecosystem()` |
| List clusters | `capi_list_clusters` | `capi_list_clusters(namespace)` |
| Get cluster kubeconfig | `capi_get_cluster_kubeconfig` | `capi_get_cluster_kubeconfig(name, namespace)` |
| Scale workers | `capi_scale_machinedeployment` | `capi_scale_machinedeployment(name, namespace, replicas)` |
## Check Installation
```python
detect_ecosystem()
```
## List Clusters
```python
# List all CAPI clusters
capi_list_clusters(namespace="default")
# Shows:
# - Cluster name
# - Phase (Provisioning, Provisioned, Deleting)
# - Infrastructure ready
# - Control plane ready
```
## Get Cluster Details
```python
capi_get_cluster(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_get_cluster_kubeconfig(name="my-cluster", namespace="default")
# Returns kubeconfig to access the cluster
```
## Machines
### List Machines
```python
capi_list_machines(namespace="default")
# Shows:
# - Machine name
# - Cluster
# - Phase (Running, Provisioning, Failed)
# - Provider ID
# - Version
```
### Get Machine Details
```python
capi_get_machine(name="my-cluster-md-0-xxx", namespace="default")
```
## Machine Deployments
### List Machine Deployments
```python
capi_list_machinedeployments(namespace="default")
# Shows:
# - Deployment name
# - Cluster
# - Replicas (ready/total)
# - Version
```
### Scale Machine Deployment
```python
# Scale worker nodes
capi_scale_machinedeployment(
name="my-cluster-md-0",
namespace="default",
replicas=5
)
```
## Machine Sets
```python
capi_list_machinesets(namespace="default")
```
## Machine Health Checks
```python
capi_list_machinehealthchecks(namespace="default")
# Health checks automatically remediate unhealthy machines
```
## Cluster Classes
```python
# List cluster templates
capi_list_clusterclasses(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_list_clusters(namespace) # Wait for Provisioned
3. capi_get_cluster_kubeconfig(name, namespace) # Get access
```
### Scale Workers
```python
1. capi_list_machinedeployments(namespace)
2. capi_scale_machinedeployment(name, namespace, replicas)
3. capi_list_machines(namespace) # Monitor
```
### Upgrade Cluster
```python
1. # Update control plane version
2. # Update machine deployment version
3. capi_list_machines(namespace) # Monitor rollout
```
## Troubleshooting
### Cluster Stuck Provisioning
```python
1. capi_get_cluster(name, namespace) # Check conditions
2. capi_list_machines(namespace) # Check machine status
3. kubectl_get(resource_type="events", namespace) # Check events
4. # Check infrastructure provider logs
```
### Machine Failed
```python
1. capi_get_machine(name, namespace)
2. kubectl_get(resource_type="events", namespace)
3. # Common issues:
# - Cloud provider quota
# - Invalid machine template
# - Network issues
```
## Related Skills
- [k8s-multicluster](../k8s-multicluster/SKILL.md) - Multi-cluster operations
- [k8s-operations](../k8s-operations/SKILL.md) - kubectl operations
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