Skip to main content

Scalability and Performance

Redundancy and failover strategies​

  • Implement multiple load balancers in an active-active or active-passive configuration to ensure high availability.

Active-Active​

All load balancers are active and share the traffic load. If one fails, the others continue to handle requests.

Active-Passive​

One load balancer is active, while the other(s) are on standby. If the active load balancer fails, a passive one takes over.

Synchronization and State Sharing​

In active-active and active-passive configurations, it's crucial to ensure that session data and state information are synchronized across load balancers.

  • Centralized configuration management: Using a centralized configuration store (e.g., etcd, Consul, or ZooKeeper) to manage load balancer settings and ensure consistency across instances.
  • State sharing and replication: Implementing mechanisms to share session state and other relevant data between load balancers, such as using distributed caches (e.g., Redis, Memcached) or , or built-in state-sharing mechanisms provided by the load balancer software or hardware.

Horizontal and vertical scaling​

  • Horizontal scaling (scaling out): Adding more servers to distribute the load.
  • Vertical scaling (scaling up): Increasing the resources (CPU, RAM, etc.) of existing servers to handle more load.

Challenges of Load Balancing

While load balancing offers numerous benefits, it also comes with its own set of challenges that need to be addressed to ensure optimal performance and reliability.

Single Point of Failure​

If the load balancer itself fails and there is no redundancy in place.

Remedy: Implement high availability and failover mechanisms, such as redundant load balancer instances, to ensure continuity even if one instance fails.

Session Persistence​

Some applications require that a user's session is consistently directed to the same backend server.

Remedy: Use session persistence (sticky sessions) techniques or advances techniques, such as cookies or IP hashing, to ensure that a user's requests are consistently directed to the same backend server.

Health Check And Monitoring​

Regular health checks are essential to ensure that backend servers are operational and can handle requests. Remedy: Implement robust health check mechanisms and monitoring tools to detect and respond to server failures promptly.

Latency​

Load balancing can introduce additional latency due to the extra hop in the request path. Remedy: Optimize load balancer performance maybe choose geographically distributed servers to minimize latency.

Scalability Limitations​

As traffic grows, the load balancer itself may become a bottleneck if it cannot handle the increased load. Remedy: Plan for horizontal or vertical scaling of the load balancer to accommodate growing traffic demands.