Distributed Monitoring System

Project Overview

A comprehensive monitoring and observability platform designed specifically for microservices architectures. This system provides real-time insights, intelligent alerting, and beautiful visualizations to help teams maintain healthy distributed systems.

Architecture and Design

Metrics Collection

- Custom Agents: Lightweight agents deployed alongside services

- Pull-based Model: Prometheus-compatible metrics collection

- Service Discovery: Automatic discovery of new services and endpoints

Data Processing

- Time Series Database: High-performance storage for metrics data

- Real-time Aggregation: Stream processing for live dashboards

- Data Retention: Intelligent data lifecycle management

Visualization and Alerting

- Custom Dashboards: Drag-and-drop dashboard builder

- Intelligent Alerts: Machine learning-powered anomaly detection

- Multi-channel Notifications: Slack, email, PagerDuty integration

Key Features

Service Map Visualization

Interactive service dependency maps showing real-time health and performance metrics for each service and their interconnections.

Anomaly Detection

Machine learning algorithms that learn normal behavior patterns and automatically detect anomalies without manual threshold configuration.

Distributed Tracing

Complete request tracing across microservices to identify bottlenecks and performance issues in complex distributed systems.

Technical Implementation

Built using Go for high performance and low resource usage, with Redis for caching and InfluxDB for time-series data storage.

Impact and Results

- 90% Faster incident detection and resolution

- Reduced MTTR from hours to minutes

- Proactive Issue Prevention through predictive alerting

- Complete System Visibility across 200+ microservices