Beginner’s Guide to Horizontal vs Vertical Scaling

When a system is first built, it’s designed to handle a certain amount of traffic.

But as more users come in, that initial capacity starts to run out. Pages load more slowly, requests pile up, and at some point, the system can’t keep up. (Especially if traffic spikes).

So to avoid performance issues or downtime, businesses need a way to expand their capacity called ‘scaling’. However, the real challenge isn’t just to decide on wanting to scale — it’s choosing how to scale.

There are two main approaches:

• Vertical scaling (scaling up): Upgrading a single machine to make it more powerful
• Horizontal scaling (scaling out): Adding more machines to share the workload

Each method has advantages and trade-offs, so how do you know which one is right for you?

The good news is that in this guide, we’ll break down what horizontal and vertical scaling are, how they work, and when to use each one — as well as how this connects with cloud scaling and why it might be the best option for your projects.

So let’s dive in…

Vertical scaling (scaling up)

Imagine you run a coffee shop with one espresso machine. At first, it works fine, but as more customers walk in, the line gets longer, and you need to serve drinks faster.

So what can you do?

Well, one option is to upgrade your machine. A high-end model can steam milk faster, pull multiple shots at once, and handle a bigger workload.

That’s vertical scaling. Instead of adding more servers to handle your app or website traffic, you can upgrade the one you already have by increasing its CPU, RAM, or storage. (Kind of like how you might upgrade your PC to perform better).

Vertical scaling is a popular choice for businesses running databases, monolithic applications, or workloads that need a single high-performance machine.

• It’s simple. You don’t need to rework your system or distribute traffic across multiple servers
• Easier maintenance. Since everything runs on one machine, there’s less complexity
• Great for databases. Some workloads, especially databases, perform better on a single powerful machine

That being said, there are downsides to each scaling option.

With vertical scaling the issues are:

• There’s a hardware limit. You can only upgrade a machine so much before hitting a ceiling
• Upgrades can cause downtime. Adding more resources often means shutting down the server temporarily
• It gets expensive. High-end hardware is costly, and at a certain point, adding multiple servers is more cost-effective
• Single point of failure. If your single upgraded server crashes, everything goes down, as there’s no redundancy

TL;DR

Vertical scaling is great for short-term boosts, but when demand keeps growing, it may not be enough. That’s where horizontal scaling comes in.

Horizontal scaling (scaling out)

Let’s go back to the coffee shop example.

Imagine that we upgraded our espresso machine, and that helped for a while but now the line is out the door again. (Perhaps everyone was loving how fast the service was and now created even more demand!)

The problem of course is that no matter how powerful or fast the new machine is, it can only serve so many customers at once.

This leads us to the next logical solution:

• Add more of those new high end machines
• Hire more baristas
• Spread out the workload
• And sell more coffee!

That’s horizontal scaling. You add more servers to share the load. This way, rather than relying on a single powerful machine, you build a network of (often smaller) machines that work together.

Tech giants like Google, Amazon, and Netflix rely on horizontal scaling because it’s the only way to handle millions of users. Instead of one giant server doing all the work, they distribute traffic across a fleet of machines.

• No hard limits. You can keep adding servers as demand grows
• Better uptime. If one server goes down, others keep running, reducing the risk of outages
• Cost efficiency. Many small servers are often cheaper than one high-end machine

Like I said before though, no method is perfect and each has its challenges.

With horizontal scaling, the issues are:

• More complexity. You need a system to distribute traffic, like a load balancer, and manage multiple machines
• Not all apps scale well. Certain workloads such as databases (especially relational databases) work better with vertical scaling unless designed for distribution
• Data consistency can be tricky. If users switch between different machines, keeping their data synchronized requires extra work

TL;DR

Most businesses start with vertical scaling because it’s simple, but once they hit a limit, they move to horizontal scaling to grow without restrictions.

That being said, managing multiple machines in horizontal scaling takes effort. But what if you could avoid that complexity? That’s where cloud scaling comes in

Scaling in the cloud: Renting servers instead of owning them

So far, we’ve covered vertical scaling (making one machine more powerful) and horizontal scaling (adding more machines). But what if you didn’t have to manage servers at all?

That’s where cloud platforms like AWS, Azure, and Google Cloud come in. In simple terms, instead of buying your own machines, you rent them as needed.

Why do this? Well, the benefits stack up pretty fast…

For example

If we go back to our coffee shop example from before:

• On a slow morning, you only have a couple of baristas on duty
• When the morning rush hits, extra baristas show up instantly to help serve customers
• When things quiet down, they go home, and you stop paying them

Handy right?

Now imagine if we took that a step further, and your coffee shop could automatically bring in the perfect number of baristas at any moment without you having to call them in. They just appeared as traffic increased. No call up needed or asking people to come in on days off.

Better still, what if they could also bring in enough coffee machines as needed and then remove them when not needed?

That’s what happens with cloud scaling, often referred to as auto-scaling. When traffic spikes, the cloud spins up and adds more servers instantly. When demand drops, it scales back down, so you don’t pay for resources you aren’t using.

With the cloud, businesses can:

• Scale on demand . No need to guess how many servers they’ll need. The cloud adjusts automatically
• Avoid expensive upfront costs. Instead of spending thousands on hardware, they pay only for what they use
• Skip maintenance. No worrying about server failures, cooling, or upgrades—the cloud provider handles all of it

Pretty good right?

So which method should you use to scale?

Well, it depends.

• For companies starting from scratch, cloud scaling is the obvious choice because you never have to think about vertical vs. horizontal scaling in the traditional sense. Not only that but it’s usually cheaper to get started
• If your system is small or monolithic and already up and running, then vertical scaling is the simplest first step
• If you expect long-term growth or spikes in demand, horizontal scaling is better
• If you don’t want to manage servers, cloud scaling is often the best option

However, not every company started in the cloud. Some of them are still following more traditional methods of scaling vertically and horizontally, but more and more of them are moving to the cloud.

Hence the growing demand for Cloud Engineers and Architects, as well as the booming cloud industry growth.

Final takeaway: Scaling is all about trade-offs

There’s no one-size-fits-all approach. Vertical scaling is simple but limited. Horizontal scaling offers more flexibility but adds complexity. Cloud scaling makes both approaches easier but comes with its own challenges if you’re adding this in after you already started.

The key is understanding what works for your specific needs so you can scale efficiently, avoid bottlenecks, and ensure your system keeps up with demand.

P.S.

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