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The container platform tailored for Kubernetes multi-cloud, datacenter, and edge management
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来源文件:README.md
The container platform tailored for Kubernetes multi-cloud, datacenter, and edge management
English | 中文
KubeSphere is a distributed operating system for cloud-native application management, using Kubernetes as its kernel. It provides a plug-and-play architecture, allowing third-party applications to be seamlessly integrated into its ecosystem. KubeSphere is also a multi-tenant container platform with full-stack automated IT operation and streamlined DevOps workflows. It provides developer-friendly wizard web UI, helping enterprises to build out a more robust and feature-rich platform, which includes most common functionalities needed for enterprise Kubernetes strategy, see Feature List for details.
The following screenshots give a close insight into KubeSphere. Please check What is KubeSphere for further information.
| Workbench | Project Resources |
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| CI/CD Pipeline | App Store |
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🎮 KubeSphere Lite provides you with free, stable, and out-of-the-box managed cluster service. After registration and login, you can easily create a K8s cluster with KubeSphere installed in only 5 seconds and experience feature-rich KubeSphere.
🖥 You can view the Demo Video to get started with KubeSphere.
KubeSphere 4.x adopts a microkernel + extension components architecture (codename LuBan). The core part (KubeSphere Core) only includes the essential basic functions required for system operation, with independent functional modules split and provided in the form of extension components. Users can dynamically manage the extension components during system operation. With the extension capabilities, KubeSphere can support more application scenarios and meet the needs of different users.

🎉 KubeSphere v4.1.2 was released! It brings enhancements and better user experience, see the Release Notes For 4.1.2 for the updates.
KubeSphere can run anywhere from on-premise datacenter to any cloud to edge. In addition, it can be deployed on any version-compatible Kubernetes cluster. KubeSphere consumes very few resources, and you can optionally install additional extensions after installation.
Run the following commands to install KubeSphere on an existing Kubernetes cluster:
helm upgrade --install -n kubesphere-system --create-namespace ks-core https://charts.kubesphere.io/main/ks-core-1.1.3.tgz --debug --wait
KubeSphere is hosted on the following cloud providers, and you can try KubeSphere by one-click installation on their hosted Kubernetes services.
You can also install KubeSphere on other hosted Kubernetes services within minutes, see the step-by-step guides to get started.
👨💻 No internet access? Refer to the Air-gapped Installation.
You can reach the KubeSphere community and developers via the following channels:
:hugs: Please submit any KubeSphere bugs, issues, and feature requests to KubeSphere GitHub Issue.
:heart_decoration: The KubeSphere team also provides efficient official ticket support to respond in hours. For more information, click KubeSphere Online Support.
Participation in the KubeSphere community is governed by the Code of Conduct.
The security process for reporting vulnerabilities is described in SECURITY.md.
The user case studies page includes the user list of the project. You can leave a comment to let us know your use case.
KubeSphere is a member of CNCF and a Kubernetes Conformance Certified platform
, which enriches the CNCF CLOUD NATIVE Landscape.
name: vector
description: Use when installing or configuring the WizTelemetry Data Pipeline (vector) extension for KubeSphere, which provides data collection, transformation, and routing for observability data including logs, auditing, events, and notificationsWizTelemetry Data Pipeline is an extension based on vector (https://vector.dev/) that provides the ability to collect, transform, and route observability data. It is a core dependency for other WizTelemetry extensions like Logging, Auditing, Events, and Notification.
REQUIRED: Complete all steps in order before generating InstallPlan.
⚠️ CRITICAL: DO NOT proceed until target clusters are determined.
Step 1.1: Get available clusters
kubectl get clusters -o jsonpath='{.items[*].metadata.name}'
Step 1.2: Determine target clusters
Ask user (if not specified):
Available clusters: host, dev
Which clusters do you want to deploy Vector to?
Ask user for (if not provided):
OpenSearch endpoint URL (required)
http://<node-ip>:30920 or https://opensearch.example.com:9200OpenSearch credentials (required)
admin)DO NOT proceed to Step 3 until user provides both endpoint and credentials.
MUST do this to get the latest version:
kubectl get extensionversions -l kubesphere.io/extension-ref=vector -o jsonpath='{range .items[*]}{.spec.version}{"\n"}{end}' | sort -V | tail -1
This outputs the latest version (e.g., 1.1.4). Note this down - you'll use it in the InstallPlan.
⚠️ IMPORTANT: Complete prerequisite steps (1-3) BEFORE this step.
⚠️ CRITICAL: InstallPlan metadata.name MUST be vector. DO NOT use any other name.
Based on your selections:
⚠️ CRITICAL: config field is YAML format. You MUST:
⚠️ CRITICAL: All placeholders MUST be replaced with actual values. DO NOT leave them as placeholders.
apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
name: vector
spec:
extension:
name: vector
version: <VECTOR_VERSION> # From Step 3
enabled: true
upgradeStrategy: Manual
config: |
agent:
sinks:
opensearch:
auth:
strategy: basic
user: <OPENSEARCH_USER>
password: <OPENSEARCH_PASSWORD>
endpoints:
- <OPENSEARCH_ENDPOINT>
clusterScheduling:
placement:
clusters:
- <TARGET_CLUSTERS>
Replace placeholders:
<VECTOR_VERSION>: From Step 2 (e.g., 1.1.4)<OPENSEARCH_ENDPOINT>: User-provided endpoint (e.g., http://<node-ip>:30920)<OPENSEARCH_USER>: User-provided username (default: admin)<OPENSEARCH_PASSWORD>: User-provided password<TARGET_CLUSTERS>: User-confirmed cluster names⚠️ DO NOT generate InstallPlan until all placeholders have real values.
After applying InstallPlan, you MUST wait for deployment to complete:
# Wait for Vector pods to be ready (on each cluster)
kubectl wait --for=condition=Ready pods -n kubesphere-logging-system -l app.kubernetes.io/instance=vector --timeout=300s
# Verify deployment status
kubectl get pods -n kubesphere-logging-system -l app.kubernetes.io/instance=vector
Show deployment summary to user:
apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
name: vector
spec:
extension:
name: vector
version: <VECTOR_VERSION> # From Step 2
enabled: true
upgradeStrategy: Manual
config: |
agent:
sinks:
opensearch:
auth:
strategy: basic
user: <OPENSEARCH_USER>
password: <OPENSEARCH_PASSWORD>
endpoints:
- <OPENSEARCH_ENDPOINT>
exportMetrics:
enabled: true
clusterScheduling:
placement:
clusters:
- <TARGET_CLUSTERS>
| Parameter | Type | Default | Description |
|---|---|---|---|
agent.role | string | "Agent" | Role identifier |
agent.image.tag | string | "0.53.0-debian" | Vector image tag |
agent.resources.requests.cpu | string | "100m" | CPU request |
agent.resources.requests.memory | string | "100Mi" | Memory request |
agent.resources.limits.cpu | string | "2000m" | CPU limit |
agent.resources.limits.memory | string | "2000Mi" | Memory limit |
agent.service.ports | list | see values.yaml | Service ports |
agent.exportMetrics.enabled | bool | false | Enable metrics export |
| Parameter | Type | Required | Description |
|---|---|---|---|
agent.sinks.opensearch.endpoints | list | Yes | OpenSearch endpoint URLs |
agent.sinks.opensearch.auth.strategy | string | Yes | Authentication strategy (set to basic) |
agent.sinks.opensearch.auth.user | string | Yes | Username for authentication |
agent.sinks.opensearch.auth.password | string | Yes | Password for authentication |
agent.sinks.opensearch.tls.verify | bool | No | Enable TLS verification (default: false) |
Example:
agent:
sinks:
opensearch:
endpoints:
- http://<node-ip>:30920
auth:
strategy: basic
user: admin
password: admin
tls:
verify: false
If Docker root directory is not /var/lib:
agent:
extraVolumes:
- name: docker-root
hostPath:
path: /path/to/docker
type: ''
extraVolumeMounts:
- name: docker-root
mountPath: /path/to/docker
# View extension installation status
kubectl get installplan vector
# View extension version
kubectl get extensionversions -l kubesphere.io/extension-ref=vector
# View all Vector pods
kubectl get pods -n kubesphere-logging-system -l app.kubernetes.io/name=vector
# View agent pods
kubectl get pods -n kubesphere-logging-system -l app.kubernetes.io/name=vector,app.kubernetes.io/component=agent
# View agent logs
kubectl logs -n kubesphere-logging-system -l app.kubernetes.io/name=vector,app.kubernetes.io/component=agent --tail=100
apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
name: vector
spec:
extension:
name: vector
version: <VECTOR_VERSION>
enabled: true
upgradeStrategy: Manual
config: |
agent:
sinks:
opensearch:
auth:
strategy: basic
user: <OPENSEARCH_USER>
password: <OPENSEARCH_PASSWORD>
endpoints:
- <OPENSEARCH_ENDPOINT>
clusterScheduling:
placement:
clusters:
- <TARGET_CLUSTERS>
Uninstall from all clusters:
kubectl delete installplan vector
Uninstall from specific cluster:
To remove Vector from a specific cluster, update the InstallPlan by removing that cluster from clusterScheduling.placement.clusters:
apiVersion: kubesphere.io/v1alpha1
kind: InstallPlan
metadata:
name: vector
spec:
extension:
name: vector
version: <VECTOR_VERSION>
enabled: true
upgradeStrategy: Manual
config: |
agent:
sinks:
opensearch:
auth:
strategy: basic
user: <OPENSEARCH_USER>
password: <OPENSEARCH_PASSWORD>
endpoints:
- <OPENSEARCH_ENDPOINT>
clusterScheduling:
placement:
clusters:
- <REMAINING_CLUSTERS> # Remove the cluster you want to uninstall from
installationMode: Multicluster:
agent (tag: agent) is deployed to all selected member clusters# View Vector configmap
kubectl get configmap -n kubesphere-logging-system -l app.kubernetes.io/name=vector
# View specific config
kubectl get configmap -n kubesphere-logging-system vector-config -o yaml
# Check if sinks are configured correctly
kubectl get secret -n kubesphere-logging-system vector-sinks -o yaml
| Issue | Solution |
|---|---|
| Pods not starting | Check if OpenSearch is accessible |
| Data not flowing | Verify sink configuration and network connectivity |
| Agent not on member cluster | Check multicluster installation settings |
| Out of memory | Increase resource limits in configuration |
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