DevOps-AI-Sentinel

Project Description

DevOps AI Sentinel is an advanced open-source monitoring and analytics platform designed to streamline DevOps workflows by providing real-time monitoring, predictive analytics, anomaly detection, and automated resolution suggestions. It integrates seamlessly with popular DevOps tools like Kubernetes, Docker, Jenkins, and Azure DevOps, empowering teams to proactively identify issues, minimize downtime, and optimize system performance.

By leveraging AI and machine learning, DevOps AI Sentinel goes beyond traditional monitoring solutions, enabling dynamic thresholding, intelligent alerting, and actionable insights. Its intuitive dashboard provides a centralized view of system health, pipeline performance, and infrastructure usage, ensuring operational efficiency at every stage of the development lifecycle.

Key Features

1. Real-Time Monitoring:

• Continuously tracks logs, metrics, and events from DevOps tools.
• Monitors pipeline performance, resource utilization, and application health.

2. Predictive Analytics:

• Utilizes AI models to forecast potential system failures and bottlenecks.
• Predicts resource utilization trends (CPU, memory, disk) for better planning.

3. Anomaly Detection:

• Identifies deviations in pipeline execution, infrastructure health, and application performance.
• Uses machine learning models to detect unexpected patterns in logs and metrics.

4. Automated Resolution Suggestions:

• Recommends fixes for common issues based on historical data and best practices.
• Builds a knowledge base of resolutions, improving over time.

5. Smart Alerting:

• Sends alerts via email, Slack, Microsoft Teams, or custom webhooks.
• Configurable severity levels and dynamic thresholds based on historical performance.

6. Seamless Integration:

• Works with Kubernetes for cluster health and pod performance monitoring.
• Monitors Docker containers, images, and logs.
• Tracks Jenkins pipeline statuses and logs.
• Retrieves metrics from Azure DevOps pipelines and builds.

7. Centralized Dashboard:

• User-friendly interface with real-time metrics, anomaly heatmaps, and predictive insights.
• Customizable widgets for different teams and use cases.

8. Scalability and Extensibility:

• Built for distributed systems with support for high-traffic environments.
• Provides APIs and SDKs for extending functionality or integrating with additional tools.

Technologies and Libraries

Frontend (Dashboard):

• React: For building the user interface.
• D3.js or Chart.js: For interactive data visualizations.
• Material-UI or TailwindCSS: For styling and responsive design.
• WebSockets: For real-time updates on the dashboard.

Backend:

• Node.js: Optional for specific integrations like webhooks or real-time event processing.

Instructions to Run the Project

Clone the Repository

• Clone the project repository to your local machine using the following command:

git clone https://github.com/fayazkhan121/DevOps-AI-Sentinel.git

Navigate to the Project Directory

Move into the project directory:

cd DevOps-AI-Sentinel

Install Dependencies

Install all the required dependencies:

npm install

Run the Development Server

Start the development server:

npm run dev

Access the Project

• Open your web browser and navigate to the URL displayed in the terminal (e.g

http://localhost:5173/

Prerequisites

• Ensure the following are installed and set up on your machine:

Node.js: Download and install from Node.js official website.

npm: Comes with Node.js. Verify installation using npm -v.

Use Case

• A DevOps team integrates DevOps AI Sentinel into their Jenkins and Kubernetes-based pipeline. The tool identifies an anomaly in resource utilization during the deployment phase and predicts a potential node failure due to high memory consumption. The team receives a Slack alert with detailed metrics and a recommended resolution (e.g., increasing memory limits for pods). Using the tool’s dashboard, they visualize the anomaly, apply the fix, and prevent downtime.