Container Infrastructure Monitoring System
Developed a centralized dashboard for managing and monitoring Docker-based container infrastructure within campus network. Features real-time log monitoring, system resource tracking (CPU, RAM, disk, network), and domain-based access management through reverse proxy configuration.
Technologies Used
Project Overview
This project aims to manage and monitor container-based infrastructure centrally through a dashboard. The system is designed to simplify administrators in managing multiple Docker-based services, monitoring system performance, and performing application troubleshooting efficiently within the campus network environment.
System Architecture
Docker: Containerization platform for running applications in isolated, consistent, and portable environments across different servers.
Portainer: Main dashboard for managing container lifecycle, images, volumes, and Docker networks on local and remote servers.
Dozzle: Displaying container logs in real-time through web interface without using command line.
cAdvisor: Detailed container performance monitoring including resource usage and network traffic for system load analysis.
Nginx Proxy Manager: Reverse proxy for domain and subdomain routing plus HTTP/HTTPS access and SSL certificate management.
Bind9: Internal DNS server for managing domain and subdomain resolution within campus network environment.
Key Features
Centralized Container Management: Managing multiple containers (web services, monitoring services, and other supporting services) from a single centralized dashboard.
System Resource Monitoring: Monitoring CPU, RAM, disk, and network usage for early bottleneck detection.
Real-Time Log Monitoring: Displaying application logs in real-time to simplify debugging and error identification without direct server access.
Domain & Access Management: Configuring internal service access through domains or subdomains for more structured and user-friendly services.
Project Outcome
✓ Centralized control of all services, faster performance detection, efficient troubleshooting