Blazor k8s

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• Colorful and intuitive display of Kubernetes resources.
• Yaml-defined fields are analyzed and displayed in a tree structure, accompanied by documentation. Additionally, translation using a large model is available, eliminating concerns about forgetting definitions.
• Detailed explanations of Kubernetes resource fields, ensuring no ambiguity about the number of options and their meanings.Official documentation with clickable links.
• Integration of official examples in a directory tree format, allowing easy browsing, reference, and field copying.
• Support efficient editing of YAML resources, enabling writing YAML fields on one side of the page while referring to field definitions at the same time.
• Support displaying corresponding Service and Ingress on the Pod page, and support displaying backend Pods on the Service and Ingress pages.
• Generation of Yaml 、Problem analysis、Security checks using a large model.
• Support conversational k8s functionality operations, such as semantic commands to check the running status of pods in the default namespace.
• Display resource usage dynamically (requires installation of metric server), and support viewing detailed statistical data* Integration of page functionalities such as kubectl describe, kubectl explain, kubectl top and other high-frequency commands. These can be accessed with a simple click on the user interface.
• Inspection functionality added to the cluster page, conducting common error checks on major resource objects and providing detailed lists.
• Supports Chinese, English, as well as French, German, Italian, Russian, Spanish, French, Japanese, Korean, and 12 languages.
• Visualize the relationships and states between workload resources intuitively through a topology diagram.

☀️ License

k8s install

Create a small Kubernetes cluster using KinD、MiniKube

KinD way

• install KinD on mac with brew.

brew install kind

• Create a new Kubernetes cluster.

kind create cluster --name k8sgpt-demo

Deploy BlazorK8s to a cluster and experience it:

kubectl apply yaml

kubectl apply -f https://raw.githubusercontent.com/weibaohui/blazork8s/main/deploy/deployment.yaml

• View the ui： By default, it uses NodePort for access. Please visit port 31999, or configure Ingress on your own. http://NodePortIP:31999

Start a Docker image to experience it

x86 Run

Note: When using Docker Desktop, you need to handle the access domain address of the API server yourself. Ensure that it is accessible within the Docker environment.

docker run -it --rm    -v ~/.kube/:/root/.kube/ -p 4000:8080 ghcr.io/weibaohui/blazork8s:0.2.0

ARM Run (Mac M1/2/3)

docker run -it --rm    -v ~/.kube/:/root/.kube/ -p 4000:8080 ghcr.io/weibaohui/blazork8s:0.2.0-arm

• View：http://IP:4000 (!Do not use 127.0.0.1/localhost!)

Debug

 git clone git@github.com:weibaohui/blazork8s.git
 cd blazork8s/BlazorApp
 dotnet watch run

Interface Language Configuration

The interface defaults to displaying in Chinese. To set a default display in another language, modify the appsettings.json in the source code's BlazorApp directory or the image's /app/appsettings.json.

"SimpleI18n": {
"LocaleFilesPath": "wwwroot/lang",
"DefaultCultureName": "LANGUAGE"
}

The available values for LANGUAGE include

{
  "en-US": "English",
  "zh-CN": "中文(Chinese)",
  "es": "Español (Spanish)",
  "ru": "Русский (Russian)",
  "pt-br": "Português (Portuguese)",
  "pl": "Polski (Polish)",
  "ko": "한국어 (Korean)",
  "ja": "日本語 (Japanese)",
  "fr": "Français (French)",
  "de": "Deutsch (German)",
  "hi": "हिंदी (Hindi)",
  "it": "Italiano (Italian)"
}

ChatGPT config

• √ MoonShot AI
• √ Ollama
• √ Google Gemini
• √ Ali Qwen
• √ iFlytek Spark
• √ OpenAI
• √ One-API same as OpenAI

Modify the appsettings.json in the BlazorApp directory or /app/appsettings.json in the image.

  "AI": {
    "Enable": true, //enabled
    "Select": "OpenAI" //choose a model from below
  },
  "OpenAI": {
    "Token": "sk-xxx",
    "Model": "gpt-3.5-turbo",
    "BaseUrl": "https://api.openai.com/v1"
  },
  "GeminiAI": {
    "APIKey": "AIxxxxxxx7dd3494880a7920axxxxxxxxx",
    "Model": "gemini-pro"
  }

Effectiveness

DocTree expands YAML definitions in a tree-like structure, no longer worry about forgetting the definitions.

Explanation of Field Meanings

Click on the question mark next to the field on the resource details page.

• Use kubectl to obtain Kubernetes explanations
• Using a configured AI large model for intelligent interpretation, the results are as follows:
  
  

Generate deployment YAML

Intelligent Analysis

Added intelligent analysis and security analysis buttons on each resource.

Workload Diagram

Visualize the relationships and states between workload resources intuitively through a topology diagram

List of inspectable resources

• Node
• Pod
• Deployment
• StatefulSet
• ReplicaSet
• CronJob
• Ingress
• Service/Endpoints
• PersistentVolumeClaim
• NetworkPolicy
• HorizontalPodAutoscaler
  
  

UI preview

click me