• 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.
• Generation of Yaml using a large model.
• Problem analysis using a large model.
• Security checks using a large model.
• Dynamic display of resource usage (requires installation of the metric server).
• Integration of page functionalities such as kubectl Describe, kubectl explain, 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.

Create a small Kubernetes cluster using KinD、MiniKube

• install KinD on mac with brew.

brew install kind

• Create a new Kubernetes cluster.

kind create cluster --name k8sgpt-demo

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. https://NodePortIP:31999

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:0.1.3

• View：web ui

 git clone [email protected]:weibaohui/blazork8s.git
 cd blazork8s/BlazorApp
 dotnet watch run

• √ Google Gemini
• √ ali Qwen
• √ iFlytek Spark
• √ OpenAI
• TBD (Baidu and other models...)

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

  "AI": {
    "Enable": true, //enabled
    "Select": "QwenAI" //choose a model
  },
   "QwenAI": {
    "APIKey": "sk-xxxxxxx7dd3494880a7920axxxxxxxxx",
    "Prompt": {
      "error": "Concisely, in the role of a Kubernetes expert, assess the provided output for any issues. Clearly list the problematic components, potential causes, and recommend appropriate actions:",
      "security": "Concisely, in the role of a Kubernetes expert, assess the provided output for any issues. Clearly list the problematic components, potential causes, and recommend appropriate actions:"
    }
  },
  "XunFeiAI": {
    "APPID": "xxxxxx",
    "APISecret": "XXXjYzgzY2E0ZTkwxxxxxxYxMDJkYTBl",
    "APIKey": "xxxxxxx7dd3494880a7920axxxxxxxxx",
    "Prompt": {
      "error": "Concisely, in the role of a Kubernetes expert, assess the provided output for any issues. Clearly list the problematic components, potential causes, and recommend appropriate actions:",
      "security": "Concisely, in the role of a Kubernetes expert, assess the provided output for any issues. Clearly list the problematic components, potential causes, and recommend appropriate actions:"
    }
  },

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

Added intelligent analysis and security analysis buttons on each resource.

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

click me