How IRCTC Handles Millions of Requests During Peak Time

# How IRCTC Handles Millions of Requests During Peak Time

The Indian Railway Catering and Tourism Corporation (IRCTC) is known for handling millions of requests daily, especially during peak times such as Tatkal ticket booking hours. This blog will delve into the technical aspects and architecture that enable IRCTC to manage such high traffic efficiently.

1. Overview of IRCTC

IRCTC is the official online ticketing and catering service provider for the Indian Railways. With millions of users accessing the site simultaneously, especially during peak hours, IRCTC needs a robust and scalable architecture to handle the load.

2. Architecture Overview

2.1. High-Level Architecture

Components:

1. **Load Balancers**: Distribute incoming traffic evenly across multiple servers.

2. **Web Servers**: Handle HTTP requests from users.

3. **Application Servers**: Execute the business logic of the application.

4. **Database Servers**: Store and retrieve data as required.

5. **Caching Servers**: Temporarily store frequently accessed data to reduce database load.

6. **CDN (Content Delivery Network)**: Distribute static content (images, CSS, JS files) closer to users to improve load times.

3. Handling Peak Traffic

3.1. Load Balancing

IRCTC uses load balancers to distribute incoming traffic across multiple servers. This ensures no single server is overwhelmed and can efficiently manage the load.

• **Types of Load Balancers**:

  • **Hardware Load Balancers**: Physical devices that distribute traffic.

  • **Software Load Balancers**: Software solutions like NGINX or HAProxy.

3.2. Horizontal Scaling

To handle peak traffic, IRCTC employs horizontal scaling, which involves adding more servers to distribute the load.

• **Auto-Scaling**: Automatically adds or removes servers based on current traffic.

3.3. Database Optimization

IRCTC uses several strategies to optimize database performance:

• **Sharding**: Splits the database into smaller, more manageable pieces.

• **Replication**: Creates multiple copies of the database to distribute the load.

• **Indexing**: Improves query performance by indexing frequently accessed data.

3.4. Caching

To reduce the load on the database, IRCTC uses caching mechanisms:

• **In-Memory Caches**: Use Redis or Memcached to store frequently accessed data in memory.

• **CDN**: Caches static content closer to users, reducing the load on the main servers.

3.5. Microservices Architecture

IRCTC uses a microservices architecture to break down the application into smaller, independent services. Each service handles a specific function, such as user authentication, ticket booking, or payment processing.

• **Benefits**:

  • Improved scalability

  • Easier to manage and deploy

  • Independent development and deployment cycles

4. Real-Time Monitoring and Alerts

IRCTC employs real-time monitoring and alerting systems to track performance and detect issues.

• **Tools**:

  • **Prometheus**: For monitoring and alerting.

  • **Grafana**: For visualizing metrics.

  • **ELK Stack (Elasticsearch, Logstash, Kibana)**: For log management and analysis.

5. Security Measures

Handling millions of requests also means ensuring the security of user data. IRCTC implements various security measures:

• **SSL/TLS Encryption**: Ensures data is encrypted during transmission.

• **WAF (Web Application Firewall)**: Protects against common web exploits.

• **DDoS Protection**: Mitigates Distributed Denial of Service attacks.

6. Conclusion

IRCTC’s ability to handle millions of requests during peak times is a result of its robust and scalable architecture, efficient load balancing, optimized database management, effective caching, microservices architecture, real-time monitoring, and stringent security measures. By continuously evolving and adopting new technologies, IRCTC ensures a seamless and reliable experience for its users.