Vertical Scalability's Development

Written by
Mariel Lettier

Any app or system can handle a set number of simultaneous requests or a set quantity of network traffic. Yet, if exceeded, your server could crash, or your service quality could suffer. So, what can you do to avoid this? You can scale your system! This concept refers to how systems or applications grow or shrink to adapt to changes and demand. On growth, there are two options: vertical and horizontal scaling.

Before, we covered everything you need to know about horizontal scalability. Now, it's vertical scalability's turn! We'll explain how it works, its pros and cons, and how it compares to horizontal scalability. Are you ready to plunge in?

What is Vertical Scalability?

Vertical scaling—or scaling up—adds resources to an existing node, computer, or server. Here, the load spreads between the CPU and RAM resources of the system. Replacing your server with a more powerful one is also considered vertical scaling. Here, the main goal is to improve performance. In this scenario, you can scale up memory, speed, storage, or other capabilities.

Vertical Scalability in the Cloud

When it comes to cloud computing, the same concept of vertical scalability applies. The scaling of networking, processing, and memory happens in-cloud servers instead of on-premises. Some providers offering vertical scalability options include AWS and Azure. Besides manual and scheduled, cloud scaling has added benefit of automatic scaling.

Pros of Vertical Scalability


Using an existing server is more affordable than buying a new one. It also means there might be no need to add backup and software to more machines. Not to mention, it saves extra costs related to space, cooling, and power.


Maintenance is both more manageable and less expensive. The administrator can easily manage and maintain the scaled-up app or system.


With single servers, there's no need for communication and synchronization with other machines. This approach simplifies the process and leads to faster responses.


As only one machine or server receives requests, data will remain consistent.

Cons of Vertical Scalability


Scaling up means your only server will be down for the time it takes to upgrade it. Thus, unless you have a backup, your app or software will be unavailable for some time.


One server or node means a single point of failure. This choice increases the risk of data loss in the case of software or hardware malfunction.


There are limitations to how much you can upgrade as you have only one machine. Your server has a set threshold for RAM, processing power, and storage.

Vertical Scaling Best Practices

There are some things to notice if you decide vertical scaling is the right choice for you:


Make sure you are aware of your capacity requirements before scaling up. It helps to avoid extra costs if you overshoot or outages if you underestimate your needs.


This aspect applies particularly to scaling up in the cloud. Cloud computing allows you to operate across the globe. Thus, you must keep up to date with the relevant jurisdiction. For example, some countries and industries require local data storage and processing.


You should always test your system to guarantee it can meet demand.


Vertical scaling doesn't mean you should stop collecting data on performance and trends. It would be best if you documented the effects of your scaling.


This point is also specific to cloud scaling. As mentioned, you should know how to carry out manual and schedule-based scaling. Yet, automated scaling is best for cloud platforms.

Vertical Scaling vs. Horizontal Scaling

Now that we know vertical scalability, it's time to meet its counterpart. Horizontal scalability—or scaling out— entails adding more nodes to a system so you can cope with new demands. Here, several resources share the workload.

Examples of vertical scalability are Amazon RDS and MySQL. Meanwhile, horizontal scaling tools enclose MongoDB, Cassandra, and Google Cloud Spanner. So, what else sets these two scaling methods apart? In the table below, we'll look at their main differences.

Both vertical and horizontal scaling have their pros and cons. Which one you choose will depend on your resources and your needs. Below, we'll share when it's best to choose one.

When to use Vertical Scalability?

● When you're on a tight budget.
● When you require unique data consistency.
● When a single machine can meet your scaling requirements.
● When you want to keep things simple.

When to use Horizontal Scalability?

● When you want to increase performance.
● When the servers receive multiple requests.
● When you want to simplify the upgrading process.
● When you have a more generous budget.
● When you wish for built-in redundancy.

Bonus: Combining Vertical and Horizontal Scaling

Although often seen as opposites, vertical and horizontal scalability can work together! In fact, this is what big companies do. When they scale out, they also scale up by choosing more powerful machines than their existing one/s. As a result, you get the best of both worlds. On the one hand, you get the resilience and limitless scalability of horizontal scaling. Also, you beneficiate from vertical scaling's speed and consistency.


At some point, all tech businesses will face the scalability issue. In this context, vertical scalability is excellent if you are on a tight budget and want to save some trouble. We hope this article gave you all the needed info to decide if vertical scaling is the right choice for you!

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