Load Balancing Strategies and Techniques You Must Know to Improve Network Efficiency

7. Source IP Hash

Source IP hash is a load-balancing technique that uses the hash of the client’s IP address and the server’s weights to select a server. This technique ensures that all requests from the same client are always directed to the same server, taking into account the capacity of the server.

How it works:

1. The load balancer receives a request from the client.
2. The load balancer calculates the hash of the client’s IP address and the server’s weight.
3. The load balancer selects servers based on the hash value and weight of the server.
4. The load balancer sends a request to the selected server.
5. The server processes the request and sends the response to the client.

Excess:

• Ensures that all requests from the same client are always directed to the same server.
• Improve connection performance and stability.
• Distribute workloads evenly between servers by considering server capacity.

Deficiency:

• If the selected server fails, all requests from the same client will fail.
• The complexity is higher than the IP hash technique.

Application Example:

• A web application with many users who often log in and log out.
• A web application that uses cookies to store session data.
• Web applications with servers that have different capacities.

8. URL Hash

URL hashing is a load-balancing technique that uses the hash of a URL request to select a server. This technique ensures that all requests for the same URL are always directed to the same server, which can improve caching performance and stability.

How it works:

1. The load balancer receives a request from the client.
2. The load balancer calculates the hash of the request URL.
3. The load balancer selects the server based on the hash value.
4. The load balancer sends a request to the selected server.
5. The server processes the request and sends the response to the client.

Excess:

• Ensure that all requests for the same URL are always directed to the same server.
• Improve caching performance and stability.
• Easy to implement.

Deficiency:

• If the selected server fails, all requests for the same URL will fail.
• It does not consider the current server workload or server response time.

Application Example:

• Web applications with a lot of static content, such as images, videos, and JavaScript files.
• A web application that uses caching to speed up page load times.
• Web application with integrated CDN (Content Delivery Network).

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:

1. GSLB receives requests from clients.
2. GSLB determines the geographic location of the client.
3. GSLB selects the server closest to the client’s geographic location based on various factors, such as latency, bandwidth, and server workload.
4. GSLB sends a request to the selected server.
5. 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:

1. The load balancer receives a request from the client.
2. The load balancer chooses one of two available servers at random.
3. The load balancer sends a request to the selected server.
4. 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.