Horizontal Vs. Vertical Scaling: Which Is Right For Your App? (2024)

Think About Long-Term Viability

When demand for your application is soaring, you’ll quickly recognize the need to maintain an app’s accessibility, uptime, and capacity in the face of increased load. Do you scale up or scale out?

In other words, is horizontal scaling or vertical scaling the correct strategy for your business?

The difference between these two types of scaling comes from the way that computing resources are added to your infrastructure. With vertical scaling (“scaling up”), you’re adding more compute power to your existing instances/nodes. In horizontal scaling (“scaling out”), you get the additional capacity in a system by adding more instances to your environment, sharing the processing and memory workload across multiple devices.

A useful analogy for understanding this distinction is to think about scaling as if it were upgrading your car. Vertical scaling is like retiring your Toyota and buying a Ferrari when you need more horsepower. With your super-fast car, you can zoom around at high speed with the windows down and look amazing. But, while Ferraris are awesome, they’re not very practical- they’re expensive, and at the end of the day, they can only take you so far before they’re out of gas (not to mention, only two seats!).

Horizontal scaling works similarly in that it gets you that added horsepower, but it doesn’t mean ditching the Toyota for the Ferrari. Instead, it’s like adding another vehicle to a fleet. You can think of horizontal scaling like several vehicles you can drive all at once. Maybe none of these machines is a Ferrari, but no one of them needs to be: across the fleet, you have all the horsepower you need.

Why Scaling Out Is Better Than Up

When you’re choosing between horizontal scaling and vertical scaling, you also have to consider what’s at stake when you scale up versus scale out.

In the Toyota-for-Ferrari trade-in scenario, you’re replacing a slower server with a bigger, faster one.

When you do this, though, you’re throttling yourself while the machine is taken offline for the upgrade. And, what happens down the road when your traffic is on the rise again and you have to repeat the upgrades? There are only a finite number of times you can go about solving your problem by “scaling up” in this manner.

Horizontal scaling is almost always more desirable than vertical scaling because you don’t get caught in a resource deficit. Instead of taking your server offline while you’re scaling up to a better one, horizontal scaling lets you keep your existing pool of computing resources online while adding more to what you already have. When your app is scaled horizontally, you have the benefit of elasticity.

You can do exactly this when your infrastructure is hosted in a Managed Cloud environment. When you scale out to the cloud, you enjoy more options for building and deploying apps.

Amazon Elastic Compute Cloud (EC2), for example, acts as a virtual server with unlimited capacity. You choose the processor, storage capacity, networking options, and operating system you need and adjust your capacity as your computing needs grow.

When you containerize your apps, you can use Amazon Elastic Container Service (ECS) or Amazon Elastic Kubernetes Service (EKS). You can use container orchestration services to deploy, manage, and scale your apps. These services automate node provisioning, patching, and updating so you can focus on other aspects of your application.

AWS Lambda’s serverless functions also provide flexibility as you scale out. These functions enable you to run your code without provisioning or managing servers and automatically scale computing power as needed.

If you develop your applications using GraphQL application programming interfaces (APIs), AWS AppSync connects to Lambda and other data sources. AppSync automatically scales up and down depending on request volumes.

Scaling out to the cloud enables you to combine any and all of these cloud services, and more, with flexibility to meet your changing app configuration and use.

Other benefits of scaling out in a cloud environment include:

  • Instant and continuous availability
  • No limit to hardware capacity
  • Cost can be tied to use
  • You’re not stuck always paying for peak demand
  • Built-in redundancy
  • Easy to size and resize properly to your needs

How To Achieve Effective Horizontal Scaling

There are important best practices to keep in mind to make your service offering compatible with horizontal scaling.

The first is to make your application stateless on the server side as much as possible. Any time your application has to rely on server-side tracking of what it’s doing at a given moment, that user session is inextricably tied to that particular server. If, on the other hand, all session-related specifics are stored browser-side, that session can be passed seamlessly across literally hundreds of servers. The ability to hand a single session (or thousands or millions of single sessions) across servers interchangeably is the very epitome of horizontal scaling.

The second goal to keep square in your sights is to develop your app with a service-oriented architecture. The more your app is comprised of self-contained but interacting logical blocks, the more you’ll be able to scale each of those blocks independently as your use load demands. Be sure to develop your app with independent web, application, caching and database tiers. This is critical for realizing cost savings — because without this microservice architecture, you’re going to have to scale up each component of your app to the demand levels of services tiers getting hit the hardest.

Enjoy the Best of Both Solutions

Scaling up versus scaling out is not necessarily an either/or choice. While you’re splitting your monolithic apps into microservices, you can scale up, too, to handle increased load in the meantime.

Start by splitting out the parts of your app with the highest load. That way, you can scale out those microservices as needed.

When you approach your scaling this way, what’s left of the original app won’t need to scale up as far. You can gradually complete the transition from monolithic app to microservices while still scaling up if demand spikes.

Your Cloud-Friendly, Autoscaling App and DevOps

You’ve worked hard developing your app. Now it’s time to get it on the market and ready to handle staggering growth. A Managed AWS Cloud service and a team of highly skilled cloud architects who can implement DevOps automation is the most effective way to ensure your app scales to success.

Get started on solving your scaling challenges by scheduling a 30-minute SA On-Demand where you can talk to one of our engineers about the steps you need to take to get ready with autoscaling!

FAQ

How does the choice between horizontal and vertical scaling impact an application infrastructure's maintenance and management complexity?

The choice between horizontal and vertical scaling significantly influences the maintenance and management complexity of an application's infrastructure. Horizontal scaling, which involves adding more machines or instances to handle increased load, introduces a higher level of complexity due to the need to manage multiple servers, ensure they are correctly configured, distribute the load effectively, and maintain synchronization across all instances. This complexity makes using advanced orchestration and automation tools necessary to streamline the management process. On the other hand, vertical scaling, which entails upgrading the existing hardware's capabilities, presents a simpler management scenario. It avoids the intricacies associated with networked instances but comes with limitations, such as the physical upgrade limits and the risk of a single point of failure.

Despite its limitations, are there specific scenarios or types of applications for which vertical scaling might still be the preferred approach over horizontal scaling?

There are specific scenarios where vertical scaling is preferred over horizontal scaling. Applications not designed to scale out or have architectural constraints that limit their ability to operate efficiently across multiple machines might benefit more from vertical scaling. Additionally, vertical scaling is often more suitable for workloads requiring significant computational power but not parallelizing well, making them poor candidates for distribution across several smaller instances. For smaller-scale applications or those with predictable, manageable growth, the simplicity and direct path to enhanced performance offered by vertical scaling can outweigh the scalability benefits of horizontal scaling.

Can a hybrid approach combining horizontal and vertical scaling be effective, and if so, under what circ*mstances would this strategy be most beneficial?

A hybrid scaling approach, which combines horizontal and vertical scaling principles, can be highly effective in meeting an application's diverse requirements. This strategy is beneficial under circ*mstances where different components of an application have varying scaling needs. For example, a database layer might require vertical scaling to handle complex queries efficiently, while the application's front-end layer benefits from horizontal scaling to accommodate an increasing number of user requests. By leveraging the strengths of both scaling methods, organizations can balance scalability, performance, and management simplicity, tailoring their infrastructure to the specific needs of their applications. This approach allows for the flexibility to scale out or up as needed, optimizing resource utilization and performance across the board.

Horizontal Vs. Vertical Scaling: Which Is Right For Your App? (2024)

FAQs

Horizontal Vs. Vertical Scaling: Which Is Right For Your App? ›

Reliability and availability – horizontal scaling can provide you with a more reliable system. It increases redundancy and ensures that you are not dependent on one machine. Performance – sometimes it's better to leave the application as is and upgrade the hardware to meet demand (vertically scale).

Which is better, horizontal or vertical scaling? ›

Vertical scaling: Adds more resources to existing server racks, allowing data to be executed on a single node. Easier data management. Horizontal scaling: Involves adding new servers, requires managing numerous queries, but can handle larger databases effectively.

How will your system handle growth, vertical or horizontal scaling? ›

Horizontal scaling keeps the existing pool of computing resources online and adds more to what is already present. For consistent, high-resource demand, vertical scaling may be efficient. It boosts existing capabilities without the need for added infrastructure.

Is using containers for software applications an example of horizontal scaling or vertical scaling? ›

Scalability with Containers: Containers enable both horizontal and vertical scaling. You can create multiple container instances of your application to achieve horizontal scalability, and you can allocate more resources (CPU, memory) to individual containers for vertical scalability.

Which of the following choices is a benefit of horizontal scaling compared to vertical scaling? ›

Horizontal Scaling improves fault tolerance. It spreads work across many nodes. It ensures availability if one node fails. Vertical scaling, however, may have limitations in fault tolerance as the entire system relies on a single machine, potentially impacting system availability in case of hardware failures.

Which scaling method is best? ›

If your data has a normal or Gaussian distribution, standard scaling or z-score/Box-Cox transformations may be better. For data with uniform or linear distributions, min-max scaling or quantile/rank transformations may be the best choice. Ultimately, the best method to use depends on the type of data you have.

What are the disadvantages of vertical scaling? ›

Disadvantages of vertical scaling

Single point of failure – Having all your operations on a single server increases the risk of losing all your data if a hardware or software failure was to occur. Upgrade limitations – There is a limitation to how much you can upgrade a machine.

What is a good example of horizontal scaling? ›

Horizontal scaling is the process of adding a resource to a set or cluster of resources. An example would be adding a virtual machine to a cluster of virtual machine clusters or adding a database to a database cluster.

What are the problems with horizontal scaling? ›

Disadvantages of Horizontal Scaling:

Any bugs in the code will become more complex to debug and understand. The licensing fee is expensive as you will have more nodes that are licensed. The cost of the data center will increase significantly because of the increased space, cooling, and power required.

Is vertical growth better than horizontal growth? ›

By scaling horizontally, you might face additional challenges, unique to the markets you are targeting. This might be product localization issues or industry-specific business aspects. However, a vertical growth strategy is typically more lucrative and can result in better long-term ROI.

What is an example of scaling vertically? ›

Vertical scaling (or "scaling up") refers to adding more hardware to an existing machine so that you run the same workload on better specs. For example, if a server requires more processing power, vertically scaling the device would mean upgrading its CPU.

Is Kubernetes horizontal or vertical scaling? ›

Kubernetes supports manual scaling of workloads. Horizontal scaling can be done using the kubectl CLI. For vertical scaling, you need to patch the resource definition of your workload.

What is the difference between horizontal scaling and vertical scaling in REST API? ›

Horizontal scaling adds more machines to a system, distributing the load. Vertical scaling upgrades a single machine's CPU, RAM, and storage. The choice depends on system architecture and application needs. Demand for an application programming interface (API) is usually not static.

Why is horizontal scaling better than vertical scaling? ›

Therefore, horizontal scaling is ideal for enterprises that require perpetual availability at peak performance levels. Conversely, the capabilities of vertical scaling cannot be enhanced without downtime. This is because all operations take place on a single machine, which often needs to be shut down for upgrades.

When to use vertical scaling? ›

Vertical scaling is best for:
  1. Less important systems and workloads.
  2. Systems and workloads that aren't likely to need additional scale in the future.
  3. Keeping initial costs down (but it may increase future costs).
  4. Systems and workloads that do not require high availability, high performance, or multi-region deployment.
Apr 9, 2023

Why is vertical scaling less common? ›

Vertical scaling is less common in cloud environments due to the downtime that may be required to scale up or down.

Is vertical scaling more expensive than horizontal scaling? ›

Cost Implications

Horizontal scaling is more expensive than vertical scaling because it involves higher upfront hardware costs and requires re-architecting a software system.

Is vertical scaling better than horizontal scaling Facebook ads? ›

For instance, if you have a profitable campaign with a good Return on Ad Spend (ROAS), you might opt for vertical scaling to slowly increase the reach of your campaign. On the other hand, if you're looking to quickly expand your reach, horizontal scaling might be the better option.

Why is horizontal scaling difficult? ›

The complexities of managing transactions across shards illustrate the significant hurdles that SQL databases face when scaling horizontally. This level of complexity requires a careful balance between maintaining the ACID properties and delivering the performance users expect from their database systems.

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