9. Global Server Load Balancing (GSLB)
Global Server Load Balancing (GSLB) is a load-balancing technique that distributes workloads between servers located in various geographic locations. This technique aims to improve the performance and availability of web applications for users around the world by minimizing latency and maximizing throughput.
How it works:
- GSLB receives requests from clients.
- GSLB determines the geographic location of the client.
- GSLB selects the server closest to the client’s geographic location based on various factors, such as latency, bandwidth, and server workload.
- GSLB sends a request to the selected server.
- The server processes the request and sends the response to the client.
Excess:
- Improve the performance and availability of web applications for users around the world.
- Minimize latency and maximize throughput.
- Improve user experience by minimizing page load times.
Deficiency:
- The complexity is higher than traditional load-balancing techniques.
- Requires more complex infrastructure and configurations.
- The cost of implementation and operation is higher.
Application Example:
- A multinational company with websites and web applications used by users all over the world.
- Video streaming service provider with an integrated CDN.
- A global e-commerce platform with traffic from various countries.
10. Random with Two Choices
Random with Two Choices is a load-balancing technique that randomly selects a server from two available servers. This technique is simple and easy to implement, but less optimal than other techniques.
How it works:
- The load balancer receives a request from the client.
- The load balancer chooses one of two available servers at random.
- The load balancer sends a request to the selected server.
- The server processes the request and sends the response to the client.
Excess:
- Simple and easy to implement.
- No complex configuration is required.
Deficiency:
- Less optimal than other techniques.
- It does not consider the current server workload or server response time.
- The chances of one of the servers being overloaded are higher.
Application Example:
- Low-traffic, static web applications.
- Simple website with a balanced workload.
- Test or development scenarios.
Case Study of the Application of Load Balancing Techniques
Case Study 1: Large E-Commerce
Background: A large e-commerce company faced challenges in dealing with a surge in traffic during the holiday season. These spikes cause servers to be frequently overloaded, resulting in long response times and poor user experiences.
Solution: The company decided to implement Load Balancing using a combination of Least Connections and Weighted Round Robin.
- Least Connections is used to handle regular daily traffic, ensuring that requests are routed to the server that has the fewest active connections. It helps in distributing the workload evenly during normal periods.
- Weighted Round Robin is used during peak traffic during the holiday season, where servers with higher capacity are given more weight to receive more requests.
Results: By using both of these techniques, companies can handle traffic spikes without any problems, improve response times, and maintain a good user experience. Sales during the holiday season increased significantly due to a stable and responsive website.
Case Study 2: Streaming Service Provider
Background: Video streaming service providers face challenges in providing a consistent user experience due to large variations in transaction size and processing time.
Solution: The company implements Load Balancing using Least Response Time.
- Least Response Time ensures that video requests are routed to the server that has the lowest response time at the time the request is received. This helps in reducing latency and ensuring a smooth viewing experience for users.
Result: By directing requests to the most responsive servers, companies can improve streaming quality and reduce buffering. This increases customer satisfaction and lowers churn rates.