Wuhr AI Ops - AI Ops Management Platform, Providing One-Stop Ops Solutions

What is Wuhr AI Ops

Wuhr AI Ops is an intelligent operations management platform that simplifies complex operations tasks through AI technology. The platform integrates a multimodal AI assistant, supports natural language interaction to execute operations commands, and can switch between K8s cluster and Linux system command environments with one click. The platform features real-time monitoring, log analysis, CI/CD management, user permission management, and more, and supports unified management of local and remote hosts. The platform uses ELK log analysis and Grafana performance monitoring, provides visual pipeline configuration and multi-environment deployment support, and helps operations teams achieve efficient, intelligent operations management.

Main Features of Wuhr AI Ops

• Intelligent AI Assistant: Integrates multimodal AI models, supports natural language interaction and K8s/Linux command switching, and provides remote host command execution and session management.
• Real-Time Monitoring and Log Analysis: Integrates ELK log analysis and Grafana monitoring, and supports real-time log search, performance monitoring, and custom alert rules.
• CI/CD Management: Provides code building, test automation, Jenkins integration, and containerized deployment support, with deployment approval and rollback mechanisms.
• User Permission Management: Role-based access control, supporting user registration approval, fine-grained permission assignment, and operation audit logs.
• Host Management: Unified management of local and remote servers, supporting SSH connection configuration, status monitoring, and batch operations.
• Model Management: Supports access to multiple AI providers, and provides API key management and model performance testing.
• Access Management: Supports ELK and Grafana integration to enable log aggregation, search, and custom monitoring dashboard configuration.
• Toolbox: Provides common operations tools such as system diagnostics, network testing, file transfer, and batch operations.

How to Use Wuhr AI Ops

• System Requirements：
  • Operating System：Linux/macOS/Windows
  • Node.js: >= 18.0.0 (20.0+ recommended)
  • npm: >= 8.0.0 (10.0+ recommended)
  • Docker：>= 20.10.0
  • Docker Compose：>= 2.0.0
  • Memory：>= 4GB
  • Hard Disk: >= 20GB available space
• Clone the Project：

git clone https://github.com/st-lzh/wuhr-ai-ops.git
cd wuhr-ai-ops

• Installation and Deployment：
  • One-Click Installation Script：
    • Domestic Users: Run the Chinese installation script.

./install-zh.sh

• • • International Users: Run the English installation script.

./install-en.sh

• • Manual Installation：
    • Configure Environment Variables：

cp .env.example .env
# 编辑.env文件，配置数据库和AI API密钥

• • • Configure npm Registry (Domestic Users)：

npm config set registry https://registry.npmmirror.com/

• • • Download the kubelet-wuhrai Tool：

wget -O kubelet-wuhrai https://wuhrai-wordpress.oss-cn-hangzhou.aliyuncs.com/kubelet-wuhrai
chmod +x kubelet-wuhrai

• • Start the Database Service：

docker-compose up -d postgres redis pgadmin
sleep 30

• • Install Dependencies：

npm install

• • Database Initialization：

npx prisma migrate reset --force
npx prisma generate
npx prisma db push

• • Initialize Users and Permissions：

node scripts/ensure-admin-user.js
node scripts/init-permissions.js
node scripts/init-super-admin.ts

• • Initialize Preset Models：

node scripts/init-preset-models.js

• • Initialize ELK Templates：

node scripts/init-elk-templates.js

• • Build and Start the Application：

npm run build
npm start

• Access Address: Main Applicationhttp://localhost:3000
• Default Account：
  • Username：admin
  • Email：admin@wuhr.ai
  • Password：Admin123!

Project Address of Wuhr AI Ops

• GitHub Repository：https://github.com/st-lzh/Wuhr-AI-ops

Application Scenarios of Wuhr AI Ops

• Data Center Operations: Use the AI assistant to quickly troubleshoot and resolve faults, and combine real-time monitoring and log analysis modules to promptly discover performance bottlenecks and anomalies.
• Cloud Platform Operations: , through the CI/CD management module, realize automated deployment and updates of containerized applications, and combine with the monitoring module to ensure the stable operation of the cloud platform.
• Enterprise IT Operations: Use the AI assistant to perform daily operations tasks, and combine with the user permission management module to ensure the security and compliance of operations tasks.
• Development and Testing Environment Management: The AI assistant quickly configures and manages the development environment, and combines with the real-time monitoring module to ensure the stability of the development and testing environment.
• Troubleshooting and Emergency Response: Quickly obtain fault information, use the log analysis module to quickly locate the root cause of the problem, combine with the real-time monitoring module to track system status in real time, and take emergency measures promptly.