How Load Balancers Distribute Traffic

Imagine launching a new feature and suddenly your app gets flooded with users-maybe a YouTube shoutout, a Product Hunt launch, or a festive sale rush.

If all those requests hit a single server, things fall apart fast:

• Slow responses
• Crashed servers
• Angry users refreshing the page

This is where load balancers quietly save the day.

In this post, we’ll break down:

• What a load balancer actually does
• How it distributes traffic
• The most common algorithms it uses
• What happens when servers fail
• Why every scalable system depends on it

No buzzwords. No fluff. Just how it really works.

What Is a Load Balancer?

A load balancer sits between users and your backend servers.

Instead of users directly talking to your app servers, they talk to the load balancer. The load balancer then decides:

“Which server should handle this request?”

Think of it like a traffic police officer at a busy junction-directing vehicles so no single road gets jammed.

Simple flow:

1User → Load Balancer → Backend Server

From the outside, users see one application.
Behind the scenes, traffic is being carefully distributed.

Why Load Balancers Exist

Without a load balancer:

• One server becomes a single point of failure
• Scaling means manual DNS changes
• Downtime is almost guaranteed

With a load balancer:

• Traffic is evenly spread
• Servers can be added or removed safely
• Failures are handled automatically

This is why load balancers are foundational infrastructure, not an “advanced optimization”.

How Traffic Reaches the Load Balancer

Here’s what actually happens when a user opens your app:

1. The user enters your domain (e.g., app.example.com)
2. DNS points the domain to the load balancer’s IP
3. Every request now hits the load balancer first
4. The load balancer forwards the request to a backend server
5. The response flows back through the load balancer to the user

From the user’s perspective-nothing looks different.
Behind the scenes-everything is controlled.

Common Traffic Distribution Strategies

1. Round Robin

Requests are sent sequentially:

1Server A → Server B → Server C → repeat

Pros

• Simple and predictable
• Works well when servers are identical

Cons

• Ignores real-time server load

Best for: small systems with evenly sized servers

2. Least Connections

The load balancer asks:

“Which server is handling the fewest active requests?”

Pros

• Adapts to uneven traffic
• Prevents overloaded servers

Best for: APIs and long-running requests

3. Weighted Distribution

Not all servers are equal.

Example:

• Server A (weight 3)
• Server B (weight 1)

Server A receives 3× more traffic.

Pros

• Ideal for mixed instance sizes
• Useful during gradual scaling

4. IP Hashing (Sticky Sessions)

Requests from the same user IP always go to the same server.

Pros

• Maintains session consistency

Cons

• Can create uneven load

Best for: legacy apps relying on in-memory sessions

Health Checks: The Secret Sauce

Load balancers don’t blindly forward traffic.

They constantly ask each server:

“Are you alive?”

This is done using health checks:

• Ping a specific endpoint (e.g., /health)
• Expect a valid response
• Mark the server unhealthy if it fails

If a server goes down:

• Traffic is rerouted automatically
• Users never notice
• No manual intervention needed

This is how high-availability systems survive real-world failures.

What Happens When a Server Crashes?

Let’s say Server B suddenly dies:

1. Health check fails
2. Load balancer removes Server B from rotation
3. Traffic continues to Server A and C
4. When Server B recovers → it’s added back automatically

This is fault tolerance-one of the biggest advantages of load balancing.

Layer 4 vs Layer 7 Load Balancing

Layer 4 (Transport Layer)

• Operates on IP and port
• Extremely fast
• No awareness of request content

Example: TCP traffic routing

Layer 7 (Application Layer)

• Understands HTTP, headers, paths
• Can route based on:
• • URLs
  • Cookies
  • Headers

Example:

1/api    → API servers
2/admin → Admin servers

Most modern web applications rely on Layer 7 load balancing.

Load Balancers and Scaling

Load balancers enable:

• Horizontal scaling (adding more servers)
• Zero-downtime deployments
• Rolling updates

You can:

• Add servers during peak traffic (sales, festivals, launches)
• Remove servers during low usage
• Deploy new versions gradually

All without users noticing anything.

A Real-World Setup

A typical production architecture looks like this:

1Users
2  ↓
3Load Balancer
4  ↓
5Multiple App Servers
6  ↓
7Database

When traffic grows:

• Add more app servers
• Load balancer distributes requests
• App keeps running smoothly

This is how products scale from 10 users to 10 million.

Why Developers Should Care

Even if you’re not a DevOps engineer:

• Load balancers affect performance
• They influence session handling
• They impact error rates
• They decide uptime

Understanding them helps you:

• Debug production issues faster
• Design scalable systems
• Make better architectural decisions

Final Thoughts

Load balancers are invisible when they work-and disastrous when missing.

They don’t:

• Magically make your app fast
• Fix inefficient code

But they protect your system from collapsing under pressure.

If your app has more than one server or plans to a load balancer isn’t optional. It’s essential.