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What is a load balancer: A comprehensive guide

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The importance of load balancers in today’s fast-changing IT infrastructures can’t be overstated. As traffic grows and applications scale, keeping systems stable, responsive, and available becomes a real challenge. That’s where load balancers prove their worth.

If you're planning to add a load balancer to your environment or just want to read about them, this guide has you covered. It explains what load balancers are, how they work, the different types, the algorithms they use, and much more.

What is a load balancer and how does it work?

A load balancer is a system that distributes incoming network traffic across multiple servers. Its main job is to ensure that no single server gets overloaded, which helps keep user applications fast and available.

You can think of a load balancer as the traffic controller for your servers. It sits in front of your server pool and directs requests in a way that keeps everything running smoothly. If one server is too busy or goes offline, the load balancer sends traffic to the others that are still healthy.

With that said, here’s a more technical explanation of load balancers:

  • They operate at different layers of the OSI (Open Systems Interconnection) model.
  • Some work at Layer 4 (Transport Layer) and use information like IP address and TCP/UDP ports to decide where to send traffic.
  • Others operate at Layer 7 (Application Layer) and make routing decisions based on data in the request itself, like HTTP headers, cookies, or URLs.

The way a load balancer handles traffic also depends on its configuration, the type of load balancer being used, and the algorithm it follows. The next sections go into these elements.

Why bother with a load balancer?

Here are some reasons why modern IT infrastructures need load balancers:

  • A load balancer spreads incoming requests across multiple servers, which ensures that no single machine gets overwhelmed. This helps maintain consistent performance even during traffic spikes.
  • If one server crashes, goes offline, or fails a health check, the load balancer automatically routes traffic to the remaining healthy servers. This keeps the application available to users even during partial outages or hardware failures.
  • You can update one server at a time while others continue to serve traffic. The load balancer directs traffic away from servers that are being updated to enable zero-downtime deployments.
  • Some load balancers use latency-based routing or geo-awareness to choose the fastest backend for each request. This improves response time for users.
  • Since users only interact with the load balancer, your actual servers stay hidden from the public internet. This reduces your attack surface and helps enforce consistent security policies.

Types of load balancers

Next, let’s take a closer look at the two main types of load balancers: Layer 4 load balancers and Layer 7 load balancers.

Layer 4 load balancer

Layer 4 load balancers make decisions using low-level information like IP addresses or TCP/UDP ports, rather than the actual content of the traffic. This makes them faster and more efficient for handling large volumes of simple requests.

Typical use cases:

  • Distributing traffic across backend servers in a fast, low-latency environment
  • Load balancing non-HTTP services like SMTP, FTP, or database connections
  • Environments where speed and throughput are more important than content-based routing
  • Internal services that don’t require deep inspection of the requests

Layer 7 load balancer

Layer 7 load balancers operate at the application level and can inspect request content before making routing decisions. They can look at URLs, headers, cookies, or other HTTP data to decide where to send the traffic. This allows for more advanced routing logic and better control over how traffic is handled.

Typical use cases:

  • Directing requests to different backend services based on API routes
  • Serving different versions of a site or app from the same domain
  • Applying A/B testing or canary deployments
  • Handling SSL termination and HTTPS redirection
  • Enforcing application-level policies like authentication or rate limiting

Load balancing algorithms

As touched upon above, load balancers use different algorithms to decide how to distribute incoming traffic across backend servers. In this section, let’s go over some of the most widely used algorithms.

Round robin

Round Robin sends each new request to the next server in line, looping back to the start once it reaches the end. It’s simple and doesn’t take server load into account.

How it works:
 If there are 3 servers, say A, B, and C, the first request goes to A, the second to B, the third to C, and the fourth back to A. The cycle keeps on repeating in the same manner.

Typical use cases:

  • Environments where all servers have similar capacity
  • Simple, stateless applications
  • Internal services with low variation in load per request

Weighted round robin

This is a variation of Round Robin in which each server is assigned a weight based on its capacity. Higher-weighted servers receive more requests.

How it works:
If Server A has a weight of 2 and Server B has a weight of 1, Server A will get two requests for every one that goes to Server B.

Typical use cases:

  • Mixed server environments with varying hardware specs
  • Situations where some servers can handle more load than others

Least connections

This algorithm sends new traffic to the server with the fewest active connections. It’s useful when different requests get processed at different speeds.

How it works:
The load balancer keeps a count of how many active connections each server has and sends new requests to the one with the smallest number.

Typical use cases:

  • Applications with long-lived connections (e.g., streaming or chat)
  • APIs where request processing time varies a lot
  • Load balancing across containers or VMs with dynamic capacity

Weighted least connections

Just like Least Connections, but it also considers server weights. A heavier server is allowed to have more active connections than a lighter one.

How it works:
Combines server load (connections) and assigned weight to find the best target.

Typical use cases:

  • Environments with different-sized servers and variable workloads
  • Balancing across cloud instances with different resource limits

IP hash

This algorithm uses the client’s IP address to determine which server will handle the request. It ensures that the same client always goes to the same server (unless the pool changes).

How it works:
 A hash function is applied to the client IP, and the result maps to one of the backend servers.

Typical use cases:

  • Applications that need session stickiness
  • Caching systems where request locality improves performance
  • Legacy apps that rely on server-side session state

Random

As the name suggests, this algorithm picks a backend server at random for each request. It’s simple and distributes traffic evenly over time, though not always in the short term.

How it works:
No tracking, no weights; each request is sent to a randomly chosen server.

Typical use cases:

  • Lightweight or testing environments
  • When simplicity is preferred over precision
  • Systems where traffic patterns are unpredictable

Advanced load balancer features

Modern load balancers do more than just distribute traffic. They offer a range of advanced features that can improve performance, security, and visibility across your systems. The following section discusses some of these features.

SSL termination

When SSL termination is configured, the load balancer handles the SSL/TLS encryption and decryption instead of passing encrypted traffic to the backend servers. This offloads the heavy cryptographic work and simplifies certificate management.

Typical steps to implement:

  • Install an SSL certificate on the load balancer
  • Configure the load balancer to listen on port 443 (HTTPS)
  • Set up backend servers to accept unencrypted HTTP traffic
  • Optionally redirect all HTTP traffic to HTTPS
  • Test to ensure proper encryption and decryption flow

Content caching

With caching enabled, the load balancer can store copies of frequently requested content (like images, scripts, or static HTML) and serve them directly. This reduces load on backend servers and speeds up response times.

Typical steps to implement:

  • Enable caching on the load balancer (based on URL paths or MIME types)
  • Define cache rules and expiration times
  • Set headers properly on backend responses to support caching
  • Monitor cache hit/miss rates
  • Fine-tune caching policies based on usage patterns

Logging and analytics

Many load balancers offer detailed logs and analytics on traffic patterns, server health, error rates, and more. This helps with troubleshooting, performance tuning, and auditing.

Typical steps to implement:

  • Enable logging in the load balancer settings
  • Choose log format (e.g., common log format, JSON)
  • Set up log storage or integrate with log management platforms (e.g., Site24x7’s log management tool)
  • Use dashboards or reports to visualize traffic data
  • Set alerts for unusual patterns or failures

Health checks

Health checks let the load balancer monitor backend servers to make sure they are responding correctly. If a server fails a check, it’s removed from rotation until it recovers.

Typical steps to implement:

  • Define health check paths or ports (e.g., /health, port 80)
  • Set frequency and timeout for checks
  • Choose thresholds for marking a server as unhealthy
  • Enable alerts or logging for health check failures
  • Confirm that servers return proper status codes on the health check endpoint

Rate limiting

Rate limiting controls how many requests a client can make in a given time. It’s useful for preventing abuse, managing API usage, and protecting against denial-of-service attacks.

Typical steps to implement:

  • Define request limits per IP or token
  • Set time window for the limit (e.g., 100 requests per minute)
  • Configure response codes for exceeded limits (usually 429 Too Many Requests)
  • Add exceptions for trusted clients if needed
  • Monitor rate limit logs for unusual activity

Session persistence (sticky sessions)

This feature ensures that a client is consistently routed to the same backend server for the duration of a session. This can be important for apps that store session data.

Typical steps to implement:

  • Choose a session persistence method (IP hash, cookies, etc.)
  • Enable persistence on the load balancer
  • Set timeout or session duration rules
  • Make sure backend servers are aware of session design (or use shared storage)
  • Test for consistent session behavior

Load balancing best practices

Finally, here are some best practices to follow when designing and managing a load-balanced environment:

  • Set up regular health checks that monitor both connectivity and application responses. When a server fails, the load balancer should stop sending traffic to it until it recovers. This ensures that users never hit broken endpoints.
  • If your application needs to route traffic based on things like URL paths, API versions, or user sessions, Layer 7 is the better option. It gives you more flexibility and control over how traffic is handled.
  • Let the load balancer handle encryption and decryption to reduce CPU load on backend servers. It also simplifies certificate management since you only need to manage it in one place.
  • Set connection timeouts and retry limits carefully. Without this, a single slow server can tie up resources and degrade overall performance.
  • Collect logs from your load balancer to monitor traffic volume, status codes, latency, and error rates. These insights help with capacity planning, debugging, and security audits.
  • If you have a mix of small and large servers, assign weights so that traffic is distributed according to their processing power and available resources.
  • Sticky sessions tie users to specific servers, which can cause uneven traffic and limit failover. Only use them if your app depends on local session storage.
  • Use auto-scaling to add or remove backend servers based on traffic. When paired with a load balancer, this allows your system to grow or shrink based on real-time needs without downtime.
  • Load balancers are exposed to the public internet in many setups. Make sure the software or firmware is up to date to protect against known vulnerabilities.
  • Simulate server crashes, DNS issues, or traffic spikes to confirm that the load balancer responds the way you expect.
  • Don’t overlook the health and performance of the load balancer itself. Use monitoring tools like Site24x7 that offer ready-to-use plugins for popular load balancers, including NGINX, HAProxy, AWS ELB, and others. These plugins help you track CPU usage, connection counts, error rates, response times, and several other key metrics.
  • Use multiple load balancers in active-passive or active-active mode to eliminate single points of failure. If one load balancer goes down, the other can take over without affecting availability.
  • Separate internal and external traffic across different load balancers. This helps isolate issues, improves security, and ensures that internal system communication doesn’t get affected by external spikes.
  • Define clear traffic routing rules and keep the configuration organized and version-controlled. This reduces errors during updates and makes rollbacks easier if needed.

Conclusion

Load balancers are an integral part of modern IT infrastructures. Whether you are looking to boost performance, enable HTTPS, reduce downtime, or handle sudden spikes in traffic, a well-configured load balancer can make a big difference.

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