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Part-1 Scalable Architectures Series

Active-Active deployment architecture, also known as load balancing or horizontal scaling, involves deploying multiple instances of an application or service, with each instance actively handling requests. This approach provides high availability, scalability, and fault tolerance. However, accomplishing an Active-Active deployment architecture poses several challenges:

Biggest Challenges

1. Session Management: In an Active-Active setup, each instance may not have access to the same session data, leading to inconsistencies and errors.
2. Data Consistency: Ensuring data consistency across multiple instances can be challenging, particularly in scenarios where data is updated frequently.
3. Load Balancing: Efficiently distributing incoming traffic across multiple instances is crucial to prevent overload and ensure optimal performance.
4. Instance Synchronization: Keeping all instances up-to-date and synchronized can be complex, especially when dealing with rolling updates or deployments.
5. Monitoring and Logging: Collecting and analyzing logs from multiple instances can be challenging, making it difficult to identify and troubleshoot issues.

Architectural Changes Needed at the Application Level

1. Stateless Architecture: Design the application to be stateless, using external storage solutions like databases or caching layers to store session data.
2. Distributed Session Management: Implement a distributed session management system, such as using a centralized session store or a distributed caching layer.
3. Event-Driven Architecture: Adopt an event-driven architecture, where instances communicate with each other through events, ensuring data consistency and synchronization.
4. API-Based Communication: Use APIs for communication between instances, ensuring a standardized and scalable way of exchanging data.
5. Service Discovery: Implement a service discovery mechanism, allowing instances to register and deregister themselves, and enabling the load balancer to direct traffic accordingly.
6. Configurable and Dynamic Configuration: Design the application to be highly configurable, with dynamic configuration options, to facilitate easy updates and changes.
7. Robust Error Handling and Retry Mechanisms: Implement robust error handling and retry mechanisms to handle instance failures and network issues.
8. Monitoring and Logging: Integrate monitoring and logging tools that can collect and analyze data from multiple instances, providing insights into application performance and issues.

Let us take an example – what needs to be done to make the application active active when it has the following tech stack. Front end – ReactJS, Webserver – tomcat, Database – Mongo DB, Messaging – Kafka and IBM MQ.

To make the application Active-Active, we’ll need to ensure that all components are scalable, fault-tolerant, and can handle requests simultaneously. Here’s a step-by-step guide for each component in your tech stack:

Frontend (ReactJS)

1. Use a Load Balancer: Place a load balancer in front of your ReactJS application to distribute incoming traffic across multiple instances.
2. Implement Session Management: Use a centralized session management solution, such as Redis or Memcached, to store session data. This ensures that user sessions are preserved across multiple instances.
3. Use a CDN: Serve static assets, such as images and CSS files, through a Content Delivery Network (CDN) to reduce the load on your application instances.

Web Server (Tomcat)

1. Configure Clustering: Set up Tomcat clustering to allow multiple instances to share session data and work together seamlessly.
2. Use a Load Balancer: Place a load balancer in front of your Tomcat instances to distribute incoming traffic.
3. Implement Session Replication: Configure Tomcat to replicate session data across multiple instances, ensuring that user sessions are preserved in case of instance failure.

Database (MongoDB)

1. Configure Replication: Set up MongoDB replication to create multiple copies of your data across different instances.
2. Use a Replica Set: Create a replica set, which allows MongoDB to automatically failover to a secondary instance in case of primary instance failure.
3. Implement Sharding: If your dataset is large, consider implementing sharding to distribute data across multiple instances.

Messaging (Kafka and IBM MQ)

1. Configure Kafka Clustering: Set up Kafka clustering to allow multiple brokers to work together and provide fault tolerance.
2. Use Kafka’s Replication Feature: Configure Kafka to replicate messages across multiple brokers, ensuring that messages are preserved in case of broker failure.
3. Implement IBM MQ Clustering: Set up IBM MQ clustering to allow multiple queue managers to work together and provide fault tolerance.

Additional Steps

1. Implement Health Checks: Configure health checks for each component to ensure that instances are functioning correctly and to detect any issues.
2. Use Monitoring and Logging Tools: Implement monitoring and logging tools to track the performance and health of each component.
3. Implement Automated Failover: Configure automated failover for each component to ensure that the system can recover quickly in case of instance failure.

By following these steps, you can make your application Active-Active, ensuring that it is highly available, scalable, and fault-tolerant.