The Essential Guide to Load Balancing Strategies and Techniques

Visualizing Load Balancer Algorithms. Examples and Best Practices when using Load Balancers.

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Jun 01, 2025

Hello guys, In today’s era of high-availability systems and instant digital experiences, performance is no longer optional—it’s expected. Whether you're building a SaaS platform, a real-time gaming service, or a global e-commerce site, users demand fast, uninterrupted access.

But how do you scale your systems to meet demand, maintain reliability, and avoid single points of failure?

That’s where load balancing steps in.

Load balancing isn’t just about splitting traffic evenly. It’s a sophisticated discipline that sits at the core of every resilient, distributed system—balancing workloads, improving fault tolerance, and enabling horizontal scalability.

Behind the scenes of the world’s most reliable applications lies a smart balancing act of algorithms, routing techniques, and infrastructure choices.

In the past episodes of System Design basics we have talked about essential System design concepts and software architecture components like Rate Limiter, Database Scaling, API Gateway vs Load Balancer, Horizontal vs Vertical Scaling, Caching strategies, load balancing algorithms, Database transactions and ACID properties and Single Point Failure, and in this article we will talk about .

In this guide, we’ll break down the key load balancing strategies and techniques that power real-world systems—from round-robin and least connections to consistent hashing and geo-distributed balancing.

Whether you’re a backend engineer, SRE, or architect, this guide will arm you with the knowledge to build systems that scale gracefully and stay available—no matter the load.

By the way, if you are preparing for System design interviews and want to learn System Design in a limited time then you can also checkout sites like Codemia.io, ByteByteGo, Design Guru, Exponent, Educative and Udemy which have many great System design courses, great for any developer.

Similarly, while answering System design questions you can also follow a System design templates from DesignGurus.io to articulate your answer better in a limited time.

For this article, I have teamed up with Hayk, a System design expert, and we'll dive into the fundamental concepts of essential Load balancer algorithms.

Let’s dive into the architecture behind the world’s most responsive systems.

What are Load Balancers?

Load balancers distribute incoming network traffic across multiple servers to ensure no single server bears too much load.

By spreading the requests efficiently, they increase the capacity and reliability of applications.

Here are some common strategies and algorithms used in load balancing:

1. Round Robin

Round Robin is the simplest form of load balancing, where each server in the pool gets a request in a sequential, rotating order. When the last server is reached, it loops back to the first.

This works well for servers with similar specifications and when the load is uniformly distributable.

2. Least Connections

Least Connections algorithm directs traffic to the server with the fewest active connections. This is particularly useful when there are sessions of variable lengths and demands.

It is ideal for longer tasks or when the server load is not evenly distributed.

3. Least Response Time

This responsiveness-focused algorithm chooses the server with the lowest response time and with the fewest active connections.

Effective when the goal is to provide the fastest response to requests.

4. IP Hash

IP Hash determines which server receives the request based on the hash of the client’s IP address. This ensures a client consistently connects to the same server.

Useful for session persistence in applications where it’s important that a client consistently connects to the same server.

5. Weighted Algorithms

There are also variants of the above methods that can be weighted. For example, in Weighted Round Robin or Weighted Least Connections, servers are assigned weights typically based on their capacity or performance metrics.

Weighted algorithms are effective when servers in the pool have different capabilities (e.g., CPU, RAM).

6. Geographical Algorithms

These are location-based algorithms that direct requests to the server geographically closest to the user or based on specific regional requirements.

Useful for global services where latency reduction and local regulatory compliance are priorities.

7. Consistent Hashing

Consistent hashing uses a hash function to distribute data across various nodes.

Imagine a hash space that forms a circle where the end wraps around to the beginning, often referred to as a “hash ring”. Both the nodes (servers) and the data (like keys of stored values) are hashed onto this ring.

This also ensures that the same client consistently connects to the same server.

Health Checks

An essential feature of load balancers is continuous health checking of servers to ensure traffic is only directed to servers that are online and responsive. If a server fails, the load balancer will stop sending traffic to it until it is back online.

Load Balancer Examples

Load balancers come in various forms, including hardware appliances, software solutions, and cloud-based services. Here are some examples:

Hardware Load Balancers

F5 BIG-IP: A widely used hardware load balancer known for its high performance and extensive feature set, offering local traffic management, global server load balancing, and application security.
Citrix ADC: Formerly known as NetScaler, it provides load balancing, content switching, and application acceleration.

Software Load Balancers

HAProxy: A popular open-source software load balancer and proxy server for TCP and HTTP-based applications. It’s known for its efficiency, reliability, and low memory footprint.
NGINX: Often used as a web server, NGINX also functions as a load balancer and reverse proxy for HTTP and other network protocols.

Cloud-Based Load Balancers

AWS Elastic Load Balancing (ELB): Offers several types of load balancers as part of the AWS cloud services, including the Application Load Balancer, Network Load Balancer, and Classic Load Balancer.
Microsoft Azure Load Balancer: Provides high availability and network performance to applications running in Azure. It supports inbound and outbound scenarios.
Google Cloud Load Balancing: A fully distributed, software-defined, managed service for all your traffic. It offers various types, including HTTP(S), TCP/SSL, and UDP load balancing.

Virtual Load Balancers

VMware NSX Advanced Load Balancer (Avi Networks): Offers a software-defined application delivery controller that can be deployed on-premises or in the cloud.

What happens when the load balancer goes down?

The load balancer is basically a single point of failure, and in case it goes down, all of the servers become unavailable for the clients.

To avoid or minimize the impact of a load balancer failure, several strategies are typically employed:

Redundancy

Implementing redundant load balancing by using more than one load balancer, often in pairs, is a common approach. If one fails, the other takes over, a method known as failover.

Health Checks and Monitoring

Continuous monitoring and health checks of the load balancer itself can ensure that any issues are detected early and can be addressed before causing significant disruption.

Auto-scaling and Self-Healing Systems

Some modern infrastructures are designed to automatically detect the failure of a load balancer and replace it with a new instance without manual intervention.

DNS Failover

In some configurations, DNS failover can reroute traffic away from an IP address that’s no longer accepting connections (like a failed load balancer) to a preconfigured standby IP.

That’s all about the essential load balancer algorithms. Load balancing isn’t just an infrastructure concern—it’s a core architectural decision that directly impacts the scalability, performance, and resilience of your systems.

From the simplicity of round-robin to the sophistication of consistent hashing and dynamic, application-aware routing, the right load balancing strategy can mean the difference between a sluggish, failure-prone application and one that performs smoothly under pressure.

And, if you like this article, then don’t forget to subscribe Hayk’s substack, he is one of my favorite author here and you can also learn a lot from him