Distributed Monitoring System

About the Project

Distributed Monitoring System is a comprehensive solution for real-time monitoring of distributed systems and applications. Built with modern technologies and microservices architecture, it provides powerful monitoring capabilities, alerting, and metrics visualization.

Key Features

Real-time Monitoring: Track system metrics, application performance, and infrastructure health in real-time;
Alert Management: Configure custom alert rules with multiple notification channels (email, Slack, webhooks);
Metrics Collection: Collect and store metrics from multiple sources with high throughput;
Dashboard Visualization: Interactive dashboards with charts and graphs for metrics analysis;
Distributed Architecture: Scalable microservices architecture with message queuing;
API Integration: RESTful APIs for easy integration with existing systems;
Data Persistence: Efficient storage with PostgreSQL and Redis caching;
Docker Support: Fully containerized with Docker Compose for easy deployment.

Technical Architecture

The system is built using a microservices architecture with the following components:

API Gateway (Ocelot): Routing, rate limiting, and load balancing;
Identity Provider (Keycloak 23): OAuth 2.0 / OIDC authentication and authorization;
Metrics Collector: Background service collecting metrics from monitored targets;
Alert Engine: Evaluates alert rules and triggers notifications;
Message Broker (RabbitMQ 3.12): Asynchronous communication between services;
Database (PostgreSQL 16): Persistent storage with Entity Framework Core 10.0;
Cache Layer (Redis 7): High-performance distributed caching;
ELK Stack: Elasticsearch 8.11, Logstash 8.11, and Kibana 8.11 for log management and visualization;

Technologies Used

Core Technologies

.NET 10.0: Runtime framework
C# 12: Programming language
ASP.NET Core 10.0: Web API framework
Entity Framework Core 10.0: ORM for database access

Infrastructure Components

PostgreSQL 16: Primary data store (Port 5432)
RabbitMQ 3.12: Message broker for async communication (Ports 5672, 15672)
Redis 7: Distributed caching (Port 6379)
Ocelot: API Gateway for routing and rate limiting (Port 5000)
Keycloak 23: Identity provider with OAuth 2.0 / OIDC (Port 8080)
Elasticsearch 8.11: Log storage and search (Port 9200)
Kibana 8.11: Visualization dashboards (Port 5601)
Logstash 8.11: Log processing pipeline (Port 5000)

Development Tools

Docker & Docker Compose: Containerization and orchestration
Serilog: Structured logging
FluentValidation: Input validation
Swagger/OpenAPI: API documentation
xUnit: Unit testing framework

Design Patterns and Best Practices

Clean Architecture: Separation of concerns with clear layer boundaries;
CQRS Pattern: Command Query Responsibility Segregation using MediatR;
Repository Pattern: Abstraction layer for data access;
Dependency Injection: Built-in .NET DI container for loose coupling;
SOLID Principles: Following object-oriented design principles;
Unit Testing: Comprehensive test coverage with xUnit;
API Versioning: Support for multiple API versions;
Error Handling: Global exception handling with custom middleware.

Monitoring Capabilities

The system can monitor various types of metrics:

System Metrics: CPU usage, memory consumption, disk I/O;
Application Metrics: Request rates, response times, error rates;
Infrastructure Metrics: Network traffic, database connections, queue depth;
Custom Metrics: User-defined metrics via API;
Health Checks: Endpoint availability and response validation.

Alert System

Flexible alerting system with multiple features:

Threshold-based alerts (greater than, less than, equals)
Time-window aggregations (average, sum, count)
Multiple notification channels (email, Slack, webhooks)
Alert severity levels (info, warning, critical)
Alert suppression and deduplication
Alert history and audit trail

API Endpoints

RESTful API with comprehensive endpoints:

Metrics API: POST /api/metrics, GET /api/metrics
Targets API: CRUD operations for monitored targets
Alerts API: Configure and manage alert rules
Dashboard API: Retrieve aggregated metrics for visualization
Health API: System health checks and status

Deployment

The system is fully containerized and can be deployed using Docker Compose:

Single command deployment: docker-compose up -d
Automatic service discovery and networking
Volume persistence for databases
Environment-based configuration
Health checks for all services
Easy scaling with Docker Swarm or Kubernetes

Security Features

OAuth 2.0 / OIDC: Authentication and authorization via Keycloak 23
JWT-based authentication: Secure token-based authentication
Role-based access control (RBAC): Fine-grained permissions management
API rate limiting: Protection against abuse via Ocelot Gateway
CORS configuration: Secure cross-origin resource sharing
Secure password hashing: Industry-standard encryption algorithms
SQL injection prevention: Parameterized queries with Entity Framework Core

Performance Optimization

Redis caching for frequently accessed data
Database indexing for query optimization
Asynchronous processing with message queues
Connection pooling for database connections
Batch processing for metrics ingestion
Lazy loading and pagination for large datasets

Future Enhancements

Machine learning for anomaly detection
Predictive alerting based on historical trends
Multi-tenancy support
Advanced data retention policies
Integration with popular monitoring tools (Prometheus, Grafana)
Mobile application for on-the-go monitoring
Custom plugin system for extensibility

Use Cases

Microservices Monitoring: Track health and performance of distributed services
Infrastructure Monitoring: Monitor servers, databases, and network devices
Application Performance: Track application metrics and user experience
DevOps Automation: Integrate with CI/CD pipelines for deployment monitoring
SLA Compliance: Ensure service level agreements are met

Learning Outcomes

This project demonstrates proficiency in:

Microservices architecture design and implementation
Real-time data processing and streaming
Message-driven architecture with RabbitMQ
Clean Architecture and SOLID principles
Docker containerization and orchestration
RESTful API design and implementation
Database design and optimization
Asynchronous programming in C#
Testing strategies for distributed systems