tencentcloud-tke

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Tencent Cloud TKE (Kubernetes)

腾讯云TKE（Kubernetes）

Manage TKE clusters and the workloads inside them.

Setup: See tencentcloud authentication. Cluster discovery and kubeconfig retrieval go through the SDK; everything inside the cluster (pods, services, scale, restart) goes through
kubectl
against the kubeconfig we fetch.

管理TKE集群及其内部的工作负载。

配置步骤： 参考tencentcloud 认证。集群发现和kubeconfig获取通过SDK完成；集群内的所有操作（pod、service、扩容、重启）均通过
kubectl
基于我们获取的kubeconfig执行。

CLI (preferred)

CLI（推荐方式）

The skill ships

scripts/tke.py

— wraps cluster discovery, kubeconfig retrieval, and the most common in-cluster operations.

bash

TKE=$SKILL_DIR/scripts/tke.py

python3 $TKE clusters                                              # list clusters
python3 $TKE cluster cls-xxxxxxxx                                  # one cluster's details
python3 $TKE nodes cls-xxxxxxxx
python3 $TKE pools cls-xxxxxxxx                                    # node pools
python3 $TKE kubeconfig cls-xxxxxxxx --save ~/.kube/config-tke     # write kubeconfig
python3 $TKE workloads cls-xxxxxxxx -n my-namespace
python3 $TKE pods cls-xxxxxxxx -n my-namespace
python3 $TKE events cls-xxxxxxxx -n my-namespace                   # recent events
python3 $TKE scale cls-xxxxxxxx -n my-namespace --name my-deploy --replicas 4
python3 $TKE restart cls-xxxxxxxx -n my-namespace --name my-deploy

In-cluster commands shell out to

kubectl

against an SDK-fetched kubeconfig.

kubectl

must be installed in the sandbox (

pip install

doesn't ship it).

该技能提供了

scripts/tke.py

脚本——封装了集群发现、kubeconfig获取以及最常用的集群内操作。

bash

TKE=$SKILL_DIR/scripts/tke.py

python3 $TKE clusters                                              # list clusters
python3 $TKE cluster cls-xxxxxxxx                                  # one cluster's details
python3 $TKE nodes cls-xxxxxxxx
python3 $TKE pools cls-xxxxxxxx                                    # node pools
python3 $TKE kubeconfig cls-xxxxxxxx --save ~/.kube/config-tke     # write kubeconfig
python3 $TKE workloads cls-xxxxxxxx -n my-namespace
python3 $TKE pods cls-xxxxxxxx -n my-namespace
python3 $TKE events cls-xxxxxxxx -n my-namespace                   # recent events
python3 $TKE scale cls-xxxxxxxx -n my-namespace --name my-deploy --replicas 4
python3 $TKE restart cls-xxxxxxxx -n my-namespace --name my-deploy

集群内命令通过调用

kubectl

并使用SDK获取的kubeconfig执行。沙箱环境中必须安装

kubectl

（

pip install

不会安装它）。

When to Use

使用场景

List TKE clusters across regions
Check node health and node-pool resource usage
List Deployments / StatefulSets / DaemonSets in a namespace
List Services / Pods / recent Events
Scale a workload up or down
Rolling restart a Deployment (e.g. after a config change)
Fetch kubeconfig for ad-hoc
```
kubectl
```
work

跨地域列出TKE集群
检查节点健康状态和节点池资源使用情况
列出命名空间中的Deployment / StatefulSets / DaemonSets
列出Services / Pods / 近期Events
对工作负载进行扩容或缩容
对Deployment执行滚动重启（例如配置变更后）
获取kubeconfig以进行临时
```
kubectl
```
操作

Dependencies

依赖项

bash

pip install tencentcloud-sdk-python
brew install kubectl   # macOS;  apt install kubectl on Debian/Ubuntu

bash

pip install tencentcloud-sdk-python
brew install kubectl   # macOS;  apt install kubectl on Debian/Ubuntu

Quick start — list clusters

快速入门——列出集群

python

import os
from tencentcloud.common import credential
from tencentcloud.tke.v20180525 import tke_client, models

cred = credential.EnvironmentVariableCredential().get_credential()
client = tke_client.TkeClient(cred, os.environ["TENCENTCLOUD_REGION"])

req = models.DescribeClustersRequest()
req.Limit = 100
resp = client.DescribeClusters(req)
for c in resp.Clusters:
    print(c.ClusterId, c.ClusterName, c.ClusterStatus, c.ClusterVersion)

Cluster IDs look like
cls-xxxxxxxx
. The
ap-hongkong
region typically holds the production clusters;
DescribeClusters
is region-scoped — call it per region you care about.

python

import os
from tencentcloud.common import credential
from tencentcloud.tke.v20180525 import tke_client, models

cred = credential.EnvironmentVariableCredential().get_credential()
client = tke_client.TkeClient(cred, os.environ["TENCENTCLOUD_REGION"])

req = models.DescribeClustersRequest()
req.Limit = 100
resp = client.DescribeClusters(req)
for c in resp.Clusters:
    print(c.ClusterId, c.ClusterName, c.ClusterStatus, c.ClusterVersion)

集群ID格式为
cls-xxxxxxxx
。
ap-hongkong
地域通常承载生产集群；
DescribeClusters
是地域级别的接口——需要针对每个你关注的地域调用它。

Workflows

工作流程

Get cluster details + worker node count

获取集群详情及工作节点数量

python

req = models.DescribeClustersRequest()
req.ClusterIds = ["cls-xxxxxxxx"]
resp = client.DescribeClusters(req)
c = resp.Clusters[0]
print(c.ClusterName, c.ClusterStatus, c.ClusterNodeNum, c.ClusterVersion)

python

req = models.DescribeClustersRequest()
req.ClusterIds = ["cls-xxxxxxxx"]
resp = client.DescribeClusters(req)
c = resp.Clusters[0]
print(c.ClusterName, c.ClusterStatus, c.ClusterNodeNum, c.ClusterVersion)

List worker nodes (and their CVM instance types)

列出工作节点（及其CVM实例类型）

python

req = models.DescribeClusterInstancesRequest()
req.ClusterId = "cls-xxxxxxxx"
req.Limit = 100
resp = client.DescribeClusterInstances(req)
for i in resp.InstanceSet:
    print(i.InstanceId, i.InstanceRole, i.InstanceState, i.NodePoolId)

python

req = models.DescribeClusterInstancesRequest()
req.ClusterId = "cls-xxxxxxxx"
req.Limit = 100
resp = client.DescribeClusterInstances(req)
for i in resp.InstanceSet:
    print(i.InstanceId, i.InstanceRole, i.InstanceState, i.NodePoolId)

Fetch kubeconfig

获取kubeconfig

python

req = models.DescribeClusterKubeconfigRequest()
req.ClusterId = "cls-xxxxxxxx"
req.IsExtranet = True            # False for VPC-internal kubeconfig
resp = client.DescribeClusterKubeconfig(req)

python

req = models.DescribeClusterKubeconfigRequest()
req.ClusterId = "cls-xxxxxxxx"
req.IsExtranet = True            # False for VPC-internal kubeconfig
resp = client.DescribeClusterKubeconfig(req)

Save and use immediately

import os, pathlib kubeconfig = pathlib.Path(os.path.expanduser("~/.kube/config-tke-cls-xxxxxxxx")) kubeconfig.parent.mkdir(parents=True, exist_ok=True) kubeconfig.write_text(resp.Kubeconfig) print("export KUBECONFIG=" + str(kubeconfig))


> Many TKE clusters expose only the **internal** API endpoint by default. If `IsExtranet=True` returns an empty / unusable config, the cluster's public API access isn't enabled — set `IsExtranet=False` and run `kubectl` from a host inside the same VPC (e.g. CVM, jump host).


> 许多TKE集群默认仅暴露**内部**API端点。如果`IsExtranet=True`返回空或不可用的配置，说明集群未启用公网API访问——请设置`IsExtranet=False`并从同一VPC内的主机（如CVM、跳板机）运行`kubectl`。

Run kubectl commands (with the fetched kubeconfig)

执行kubectl命令（使用获取的kubeconfig）

python

import subprocess

KUBECONFIG = os.path.expanduser("~/.kube/config-tke-cls-xxxxxxxx")
NS = "acedatacloud"

def kubectl(*args):
    return subprocess.run(
        ["kubectl", f"--kubeconfig={KUBECONFIG}", *args],
        check=True, capture_output=True, text=True,
    ).stdout

print(kubectl("get", "pods", "-n", NS))
print(kubectl("get", "deploy", "-n", NS))
print(kubectl("get", "svc", "-n", NS))
print(kubectl("get", "events", "-n", NS, "--sort-by=.lastTimestamp"))

python

import subprocess

KUBECONFIG = os.path.expanduser("~/.kube/config-tke-cls-xxxxxxxx")
NS = "acedatacloud"

def kubectl(*args):
    return subprocess.run(
        ["kubectl", f"--kubeconfig={KUBECONFIG}", *args],
        check=True, capture_output=True, text=True,
    ).stdout

print(kubectl("get", "pods", "-n", NS))
print(kubectl("get", "deploy", "-n", NS))
print(kubectl("get", "svc", "-n", NS))
print(kubectl("get", "events", "-n", NS, "--sort-by=.lastTimestamp"))

Describe a misbehaving pod

排查异常Pod

python

print(kubectl("describe", "pod", "<pod-name>", "-n", NS))
print(kubectl("logs", "<pod-name>", "-n", NS, "--tail=200"))

python

print(kubectl("describe", "pod", "<pod-name>", "-n", NS))
print(kubectl("logs", "<pod-name>", "-n", NS, "--tail=200"))

Scale a Deployment

扩容Deployment

python

undefined

python

undefined

To 4 replicas. Confirm with the user before running for prod workloads.

print(kubectl("scale", "deploy/platform-backend", "-n", NS, "--replicas=4"))

undefined

print(kubectl("scale", "deploy/platform-backend", "-n", NS, "--replicas=4"))

undefined

Rolling restart a Deployment

滚动重启Deployment

python

undefined

python

undefined

Forces every pod to recycle through the rolling-update strategy.

print(kubectl("rollout", "restart", "deploy/platform-backend", "-n", NS)) print(kubectl("rollout", "status", "deploy/platform-backend", "-n", NS, "--timeout=300s"))

undefined

print(kubectl("rollout", "restart", "deploy/platform-backend", "-n", NS)) print(kubectl("rollout", "status", "deploy/platform-backend", "-n", NS, "--timeout=300s"))

undefined

List node pools (TKE concept above raw nodes)

列出节点池（TKE在原生节点之上的概念）

python

req = models.DescribeClusterNodePoolsRequest()
req.ClusterId = "cls-xxxxxxxx"
resp = client.DescribeClusterNodePools(req)
for np in resp.NodePoolSet:
    print(np.NodePoolId, np.Name, np.LifeState, np.DesiredNodesNum, np.AutoscalingGroupId)

python

req = models.DescribeClusterNodePoolsRequest()
req.ClusterId = "cls-xxxxxxxx"
resp = client.DescribeClusterNodePools(req)
for np in resp.NodePoolSet:
    print(np.NodePoolId, np.Name, np.LifeState, np.DesiredNodesNum, np.AutoscalingGroupId)

Troubleshooting flow

故障排查流程

1. python: DescribeClusters → cluster status / version
2. python: DescribeClusterInstances → any nodes "failed" / "running"
3. kubectl get events → recent failures (image pulls, scheduling, OOM)
4. kubectl get pods → which pod is in CrashLoopBackOff / ImagePullBackOff
5. kubectl describe pod <name> → conditions, events on the pod
6. kubectl logs <name> --tail=200 → application logs
7. (optional) tencentcloud-cls skill → CLS query for the same window

1. python: DescribeClusters → cluster status / version
2. python: DescribeClusterInstances → any nodes "failed" / "running"
3. kubectl get events → recent failures (image pulls, scheduling, OOM)
4. kubectl get pods → which pod is in CrashLoopBackOff / ImagePullBackOff
5. kubectl describe pod <name> → conditions, events on the pod
6. kubectl logs <name> --tail=200 → application logs
7. (optional) tencentcloud-cls skill → CLS query for the same window

Important reminders

重要提醒

Confirm scale / restart actions with the user before running for production workloads. A
```
replicas=0
```
typo takes the service down.
Kubeconfigs contain a long-lived bearer token. Treat the file like a credential —
```
chmod 600
```
, never commit, regenerate after offboarding people.
Internal vs external endpoint:
```
IsExtranet=False
```
gives a kubeconfig usable only from inside the cluster VPC. From a laptop, use
```
IsExtranet=True
```
and ensure the cluster has a public API endpoint enabled (TKE console → Cluster → Basic Info → API Server access).
Region matters. Cluster
```
cls-xxxxxxxx
```
in
```
ap-hongkong
```
is invisible from a TKE client constructed for
```
ap-guangzhou
```
.

在对生产环境工作负载执行扩容/重启操作前，务必与用户确认。如果误写
```
replicas=0
```
会导致服务下线。
Kubeconfig包含长期有效的Bearer令牌。请将该文件视为凭据——设置
```
chmod 600
```
权限，切勿提交到代码仓库，人员离职后需重新生成。
内部与外部端点：
```
IsExtranet=False
```
提供的kubeconfig仅能在集群VPC内部使用。在笔记本电脑上使用时，请设置
```
IsExtranet=True
```
并确保集群已启用公网API端点（TKE控制台 → 集群 → 基本信息 → API Server访问）。
地域至关重要。
```
ap-hongkong
```
地域的集群
```
cls-xxxxxxxx
```
无法在针对
```
ap-guangzhou
```
地域构建的TKE客户端中被发现。

Console links

控制台链接

TKE console: https://console.cloud.tencent.com/tke2/cluster
API reference: https://www.tencentcloud.com/document/product/457/31862

TKE控制台：https://console.cloud.tencent.com/tke2/cluster
API参考文档：https://www.tencentcloud.com/document/product/457/31862