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Real-Time WebSocket Platform (Go)

Enterprise Real-Time Communication Platform

GitHub Repository: SamvetaOrg/sanjay

Tech Stack

  • Backend: Go (Golang)
  • Real-time: WebSockets
  • Caching & Pub/Sub: Redis
  • Database: MongoDB
  • Communication: gRPC
  • Load Balancing: NGINX
  • Containerization: Docker

Project Overview

Built a horizontally scalable WebSocket service in Go designed to handle massive concurrent connections and high message throughput. The platform supports enterprise real-time communication needs with fault tolerance, distributed architecture, and resilience under load.

Key Technical Achievements

Concurrency & Scale

  • 50k+ Concurrent Connections: Engineered to handle over 50,000 simultaneous WebSocket connections per instance
  • High Message Throughput: Optimized message processing pipeline for thousands of messages per second
  • Goroutine Management: Efficient goroutine pooling and lifecycle management to prevent resource exhaustion
  • Memory Optimization: Careful memory management to handle large-scale concurrent operations

Distributed Architecture

  • Redis Pub/Sub: Implemented distributed communication layer enabling message broadcasting across multiple server instances
  • Horizontal Scalability: Designed stateless architecture allowing seamless addition of new instances
  • Session Persistence: Redis-backed session storage for connection state management across instances
  • Multi-instance Coordination: Synchronized message delivery across distributed WebSocket servers

Reliability & Fault Tolerance

  • Fault-tolerant Message Handling: Implemented retry mechanisms and dead letter queues for failed messages
  • Circuit Breaker Pattern: Protected downstream services from cascading failures
  • Offline Message Queues: Stored messages for offline users with guaranteed delivery on reconnection
  • Graceful Degradation: System continues operating with reduced functionality during partial failures

Performance & Resilience

  • Rate Limiting: Token bucket and sliding window algorithms to prevent abuse and ensure fair usage
  • Connection Management: Automatic reconnection handling with exponential backoff
  • Health Monitoring: Real-time health checks and automatic instance recovery
  • Load Shedding: Intelligent request dropping during overload conditions

Production Deployment

  • NGINX Load Balancer: Configured NGINX for WebSocket-aware load balancing with sticky sessions
  • Multi-instance Architecture: Deployed multiple instances behind load balancer for high availability
  • Capacity Planning: Architected for 100k+ concurrent connections with room for growth
  • Docker Containerization: Containerized services for consistent deployment and easy scaling

Technical Highlights

WebSocket Implementation

  • Connection Lifecycle: Proper handling of connection establishment, maintenance, and cleanup
  • Ping/Pong Mechanism: Heartbeat implementation to detect and close dead connections
  • Binary & Text Messages: Support for both message types with efficient serialization
  • Compression: WebSocket compression for reduced bandwidth usage

Go-Specific Optimizations

  • Goroutine Pools: Worker pool pattern to limit goroutine creation
  • Channel Buffering: Optimized channel buffer sizes for message passing
  • Context Propagation: Proper context usage for cancellation and timeouts
  • Zero-copy Operations: Minimized memory allocations in hot paths

Redis Integration

  • Pub/Sub Channels: Topic-based message routing across instances
  • Connection Pooling: Efficient Redis connection management
  • Pipelining: Batched Redis operations for improved throughput
  • Cluster Support: Ready for Redis cluster deployment

Monitoring & Observability

  • Metrics Collection: Real-time metrics on connections, messages, and errors
  • Distributed Tracing: Request tracing across microservices
  • Structured Logging: JSON-formatted logs for easy parsing and analysis
  • Alerting: Automated alerts for critical issues

Performance Metrics

  • 50,000+ concurrent connections per instance with stable performance
  • High message throughput with sub-millisecond latency
  • 99.9% uptime with fault-tolerant architecture
  • Capacity for 100k+ connections with horizontal scaling

Scalability Features

  • Stateless Design: No server-side state allows easy horizontal scaling
  • Load Balancing: NGINX with WebSocket support and sticky sessions
  • Auto-scaling Ready: Metrics-based auto-scaling integration
  • Database Sharding: MongoDB sharding support for data scalability

Resilience Patterns

  • Circuit Breaker: Prevents cascading failures to downstream services
  • Retry Logic: Exponential backoff with jitter for failed operations
  • Bulkhead Pattern: Resource isolation to prevent total system failure
  • Timeout Management: Proper timeout handling at all levels

This project showcases expertise in building high-performance, distributed real-time systems using Go, with a focus on concurrency, scalability, and reliability at enterprise scale.