Load Balancing vs Client-Side Load Balancing

Developers should learn and use load balancing when building scalable, high-availability systems, such as web applications, APIs, or microservices that experience variable or high traffic loads meets developers should learn and use client-side load balancing when building distributed systems, especially microservices, to enhance fault tolerance and reduce latency by avoiding an extra hop to a central load balancer. Here's our take.

Load Balancing

Nice Pick

Developers should learn and use load balancing when building scalable, high-availability systems, such as web applications, APIs, or microservices that experience variable or high traffic loads

Pros

• It is essential for distributing incoming requests across multiple servers to prevent downtime, reduce latency, and ensure fault tolerance, particularly in cloud environments or during traffic spikes
• Related to: high-availability, horizontal-scaling

Cons

• Specific tradeoffs depend on your use case

Client-Side Load Balancing

Developers should learn and use client-side load balancing when building distributed systems, especially microservices, to enhance fault tolerance and reduce latency by avoiding an extra hop to a central load balancer

Pros

• It is particularly useful in cloud-native environments with dynamic service discovery (e
• Related to: microservices, service-discovery

Cons

• Specific tradeoffs depend on your use case

The Verdict

Use Load Balancing if: You want it is essential for distributing incoming requests across multiple servers to prevent downtime, reduce latency, and ensure fault tolerance, particularly in cloud environments or during traffic spikes and can live with specific tradeoffs depend on your use case.

Use Client-Side Load Balancing if: You prioritize it is particularly useful in cloud-native environments with dynamic service discovery (e over what Load Balancing offers.

The Bottom Line

Load Balancing wins

Developers should learn and use load balancing when building scalable, high-availability systems, such as web applications, APIs, or microservices that experience variable or high traffic loads