Horizontal vs. Vertical Cloud Scaling: Key Differences and Similarities
Vertical scaling upgrades existing infrastructure while horizontal scaling deploys new infrastructure.
Scalability is defined as the ability to enhance or diminish the throughput capacity of cloud systems to fulfill fluctuating demand for bandwidth. This article lists down the key similarities and differences between horizontal and vertical cloud scalability in detail.
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What Is Horizontal and Vertical Scalability?
Scalability is the ability to enhance or diminish the throughput capacity of cloud systems to fulfill fluctuating demand for bandwidth.
Horizontal vs. VerticalScaling
In the post-pandemic corporate world of 2021, numerous businesses have adopted cloud systems in some capacity or the other. Scalability helps these businesses keep their online services available for clients in a cost-effective manner, regardless of fluctuations in demand.
Scalability is a critical component of the cloud in the post-pandemic corporate landscape. Demand for online services can fluctuate widely based on several (sometimes uncontrollable) factors. The inability to meet this varying demand even for a few minutes could lead to customers taking their business to a competitor. With cloud adoption among businesses at an all-time high, cloud scalability plays an important role in today’s world.
Cloud scaling takes place in two primary ways: horizontal and vertical. Both scaling methodologies enhance system capacity in terms of processing power, data storage, and networking capabilities. However, while vertical scaling takes place using existing infrastructure, horizontal scaling relies on the deployment of new infrastructure.
Cloud scalability works primarily by infusing virtualization capabilities in the cloud architecture. Virtual machines (VMs) are backed by physical infrastructure with relatively crystallized specifications and performance capabilities. The flexibility offered by VMs allows them to be scaled up or down with ease, i.e., by moving existing workloads to larger or smaller VMs whenever required. The workloads and applications processed and stored on these VMs can be transferred to different servers or even to several servers simultaneously, which is an example of scaling out.
Using the cloud services of third-party vendors allows businesses to leverage the vast software and hardware resources already deployed by these providers for their scaling needs. The swift scaling provided by third-party cloud services may not be possible for individual businesses to achieve by themselves cost-effectively.
Enterprises leverage scalable cloud models to cater to changing customer demands and enhance profitability. Cloud scalability allows companies to work in a swift, efficient, and competitive manner. In fact, scalability is one of the key advantages of migrating business processes to the cloud.
Demand for cloud bandwidth can spike suddenly, increase gradually, or even decrease with time. Regardless of the situation, cloud scalability allows enterprises to respond appropriately by increasing or decreasing performance and storage capabilities instantly and cost-effectively.
Let’s find out a little more about these scaling methodologies:
Horizontal scaling
Also called ‘scaling out’, horizontal cloud scaling improves the cloud throughput by adding new computing infrastructure. At a basic level, scaling out can mean adding new computing nodes or machines to enhance the data processing and storage capabilities.
Horizontal scaling is primarily useful for organizations that need high availability and near-zero downtime for their online services. Compared to vertical scaling, horizontal scaling is quicker and easier to accomplish. Generally, it takes place with minimal downtime or other disruptions.
Vertical scaling
Vertical cloud scaling enhances the technical specifications of existing infrastructure by adding or replacing CPU, HDD, or other components. Decommissioning existing systems and replacing them with higher capability infrastructure would also qualify as vertical scaling or ‘scaling up’. The old infrastructure is either discarded for scrap, resold, or repurposed for less intensive business processes. Compared to horizontal scaling, vertical scaling can take longer and may entail a period of downtime. However, scaling up is usually cheaper than scaling out.
Using the services of a third-party cloud vendor simplifies vertical scaling for businesses. This is because ensuring sufficient cloud computing resources for fulfilling scalability needs becomes the service provider’s duty. For the end user, scaling up can then be as simple as modifying the instance size on a web interface.
See More: Private vs. Public Cloud: 10 Key Comparisons
Similarities Between Horizontal and Vertical Cloud Scaling
Whether cloud services are scaled horizontally or vertically, both scaling methodologies have many similarities. Here are some key similarities between horizontal and vertical cloud scaling.
Horizontal and Vertical Cloud Scaling Similarities
1. Enhance processing and storage
Cloud computing has many business applications in 2021. However, processing and storage are still two of the most common uses of the cloud for companies. Cloud scaling helps businesses process and store critical data and applications at the required scale.
By enhancing their cloud processing and storage capabilities, businesses can securely host applications and store sensitive client data. Ensuring that these business needs are met is essential for any organization. However, flexibility in processing and storage is especially useful for organizations that are just starting up.
A startup might begin its journey with just a few terabytes of information to process and store. However, even one particularly successful business day could lead to this data multiplying very quickly. With cloud scalability, such businesses will be able to manage these increased workloads with ease.
Whether you choose to scale up or out, it makes onboarding new clients and catering to new customers a breeze. Processing and storing data becomes an always-on operation, and customers will not have to face downtime or slow response times.
2. Improve business capabilities
Cloud scalability has revolutionized the idea of business infrastructure. The idea of ‘fixed capacity’ systems is slowly becoming a thing of the past. Even smaller companies are able to access powerful cloud resources to enhance their workflows and other business capabilities at the scale they need.
The demand for powerful cloud-based software for business development and data analysis is steadily increasing in the post-pandemic corporate world. Companies can scale their systems to enhance their business capabilities. Scaling up (or out) allows businesses to leverage the cloud for developing products and services to achieve the desired business results at the required scale.
Implementing the correct scaling protocols means that accessing the right infrastructure at the right time is rarely a problem. Companies no longer need to worry about a client being ‘too big’ for them. Instead, they can ramp up their cloud computing resources whenever they need improved business capabilities. Also, when business capabilities are lying unused, they can be scaled down (or in) to minimize costs.
3. Increase flexibility
Flexibility is a core benefit of cloud scalability. Many businesses across industries have moved online in the aftermath of COVID-19. This has made dynamism a regular part of day-to-day business operations. Flexible infrastructure is needed to rise to this challenge and achieve long-term success.
Scalable cloud infrastructure enables businesses to reshape their systems to accommodate changing workloads. In fact, some companies are adopting scalable cloud architecture and applications from the get-go. This enables them to easily transform private cloud networks into hybrid cloud or multi-cloud environments to address relevant business problems.
Cloud scalability, regardless of type, offers immense flexibility to companies. It allows them to address operational challenges and regulatory and legal requirements as they scale their cloud infrastructure to meet existing and foreseeable business needs.
4. Reduce response time
Cloud scalability helps minimize the time taken by businesses to respond to customers. Automated scaling processes mean that customers don’t even need to wait for the company to scale its systems manually. This helps ensure that no customers have to wait for an unreasonably long period of time to get a response. Simply set the parameters, and your cloud platforms will expand or contract automatically as per the demand for bandwidth.
5. Encourage innovation
Both types of scalable cloud solutions help manage the throughput of different business assets effectively. This removes the need for IT personnel to constantly monitor and respond to bandwidth issues. The tech team can spend more time creating and improving innovative solutions to transform important business processes.
6. Maximize cost-effectiveness and profitability
Finally comes the core similarity between both horizontal and vertical scaling, which is maximum cost-effectiveness and profitability. Cloud computing helps companies of all sizes reduce their costs related to infrastructure. This is because they can expand or contract bandwidth based on existing business needs.
Further, scalability minimizes the risks normally associated with the rapid expansion of business operations. For instance, having three back-to-back amazing quarters followed by a slow one doesn’t automatically lead to profits being gutted due to fixed cloud infrastructure costs. Instead, companies can enhance or limit the scale of operations (and associated costs) based on time of the day, yearly trends, demand forecasts, and even manually.
Scalable cloud infrastructure of both types also minimizes the need for constant supervision by IT personnel. Whenever demand crosses a certain threshold, the system automatically scales to accommodate it. Additionally, ‘lifting and shifting’ on-premise applications to the cloud can help make business operations even more economical. All this helps minimize cloud costs and maximize profits.
See More: Virtual vs. Private Cloud: 10 Key Comparisons
Differences Between Horizontal and Vertical Cloud Scaling
While the two types of cloud scaling environments have many similarities, they have numerous distinctions as well. Below are the key differences between horizontal and vertical cloud scaling.
| Performance Model | |
|---|---|
| Horizontal Scaling | Vertical Scaling |
| Horizontal scaling harnesses the power of multiple physical machines. This ‘distributed programming’ allocates processing and storage tasks across physical machines connected by a single network. | Vertical scaling leverages concurrent programming on a single physical machine. This machine may have multiple cores. The data processing and storage capacity of the machine can be optimized through in-process messaging and multi-threading. |
| Key Features and Examples | |
|---|---|
| Horizontal Scaling | Vertical Scaling |
| Horizontal scalability features robust load balancing, distributed file systems, and clustering. This allows traffic to be regulated more effectively at higher demand levels. Fault tolerance mechanisms are also more prominent in horizontal scaling environments.
Prime examples of horizontal scaling include MongoDB and Cassandra. |
Vertical scalability is prominent for its ease of implementation and maintenance by existing in the form of a single system. Scaling up comes with minimal risk of application incompatibility. This form of scaling is more apt for smaller organizations with lower data throughput requirements.
Prominent examples of vertical scaling include Amazon RDS and MySQL. |
| Geographical Distribution | |
|---|---|
| Horizontal Scaling | Vertical Scaling |
| Scaling out is ideal for enhancing the geographical reach of an application. Horizontal scaling minimizes geo-latency, helps ensure regulatory compliance, and enhances business continuity. | Scaling up is ideal for applications requiring a limited geographical presence. Vertical scaling is best suited for companies that cater to clients within a specific region. |
| Execution | |
|---|---|
| Horizontal Scaling | Vertical Scaling |
| The horizontal scaling process involves breaking sequential blocks of logic into tinier pieces. This allows data to be executed concurrently across machines. | There is no need for repeated changes in the logic process involved in vertical scaling. The same code is deployed for execution on a machine with more advanced specifications. |
| Data Transmission | |
|---|---|
| Horizontal Scaling | Vertical Scaling |
| Horizontal scaling transmits data between machines using network communication, also known as ‘calls’. These calls can be slow and are likely to fail, especially in un-optimized scaling environments.
Data processing in non-optimal horizontal scaling environments often translates to different machines processing different requests. This can lead to outdated data being transmitted to the client. However, this issue can be addressed through the implementation of stateless scalability. Distributed computing environments without a shared address space could lead to complications in data sharing. This method can also increase costs, as data needs to be copied before being shared or updated. Finally, horizontal scaling calls for a load balancing component. This is required to distribute traffic among the numerous machines involved. |
Vertical scaling operates on the principle of inter-process communication. This scalability method is much faster and more straightforward.
As scaling up involves a single machine for processing all requests, the issue of ‘data inconsistency’ does not exist. Even multi-threaded environments usually feature a shared address space. This enables data sharing to be done through the passing of references. Finally, the entire load of data is processed by a single machine. This removes the need for a load balancer. |
| Cost | |
|---|---|
| Horizontal Scaling | Vertical Scaling |
| The absolute cost of horizontal scaling is often exponentially higher than that of vertical scaling. This is because scaling out involves multiple physical machines, often spread across numerous data centers in different geographies.
However, horizontal scaling can help corporations that have an appropriate use case to enhance their profitability manifold. |
Vertical scaling is usually a low-cost alternative to horizontal scaling. This is because a single machine is more economical to operate, maintain, and manage.
As the capacity of single machines increases through the introduction of cutting-edge components, the profitability associated with vertical scaling is better than ever before. |
| Downtime | |
|---|---|
| Horizontal Scaling | Vertical Scaling |
| Downtime is rare in an environment bolstered by horizontal scaling. This is because multiple machines exist to process requests at the same time. In case some machines stop functioning, others will take up their workload. | An environment that relies on vertical scaling is more susceptible to downtime. This is because all workloads are processed on a single machine. No matter how robust the capacity of this machine, any problems in its operations might introduce the risk of downtime. |
| Flexibility | |
|---|---|
| Horizontal Scaling | Vertical Scaling |
| Horizontal scaling is extremely flexible, as there is no upper limit on how many machines can be deployed for processing workloads. This makes it possible to choose an optimal configuration from both a performance and cost perspective.
Flexibility is also apparent in the cost of operations–when you need to ‘scale in’, you can simply shut down the machines that are not required at the given moment. |
Vertical scaling is not possible beyond the upper capacity of a single machine. Additionally, enhancing the specifications of the machine often involves downtime.
Vertical scaling also falls behind in terms of cost flexibility—the cost of day-to-day operations is essentially fixed based on the hardware being used. |
| Upgrades | |
|---|---|
| Horizontal Scaling | Vertical Scaling |
| Upgrading the capabilities of the existing scaling system does not require the network to be taken down. 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. |
Choosing between horizontal and vertical cloud scaling
Both horizontal and vertical cloud scalability have their advantages and disadvantages. So, how do you choose the right cloud scaling methodology for your organization?
The first factor to consider is the architecture of your application. Start by identifying your business goals and the technical requirements for fulfilling them. Then, consult with all stakeholders to understand which business areas would gain value through cloud scaling.
Next, involve technical experts from within the organization (and, if required, from outside as well). Leverage this expertise to make critical decisions based on architecture, business processes, and stakeholders. Factors that can help you gain a better understanding of the cloud scaling needs of your organization include the performance requirements of your application and its technical characteristics, such as the system throughput, availability, and response time needed for peak performance.
Consider developing prototypes to understand what each cloud scaling model would look like in practice. Once the prototype is up and running, test its productivity, reliability, fault tolerance, and cost-effectiveness. Ensure that the findings are in sync with your short-, medium-, and long-term cloud scaling goals.
Regardless of the methodology you choose, it should answer the above questions. However, every organization has a different use case, and these questions are just a way to get started. Work with stakeholders from across departments to come up with more questions pertaining to your organization in particular. Then, take the effort to answer those questions as accurately and exhaustively as possible. It may seem like a lot of work in the short term, but cloud scaling is a long-term commitment. A solution that meets your organization’s needs today will not necessarily do so five to ten years down the line.
Once your requirements are crystallized, work with technology experts to understand whether your application will actually operate with the chosen model and architecture. In case neither really seems to be a perfect fit, consider that most leading tech enterprises use a combination of both methodologies to fulfill their scalability requirements.
This hybrid approach can help you combine the reliability and speed of vertical scaling with the infinite scalability and robust business continuity offered by horizontal scaling. Remember, you’ll always have to compromise on a few factors regardless of the methodology you pick.
See More: Cloud vs. On-premise Comparison: Key Differences and Similarities
Takeaway
Whether you opt for horizontal or vertical cloud scaling, remember that deploying new hardware or components randomly is never the best way forward. Adding more machines or nodes without first studying the technical needs of your application carefully might lead to bottlenecks, inconsistencies, and a generally sub-optimal environment.
If you’re unsure, see whether increasing the capacity or modifying the specifications of existing machines addresses your business requirements. In that case, go for vertical scaling, especially if you’re just starting out. Once you are confident that your users (and, therefore, data throughput) are about to increase exponentially, it may be the right time to opt for a horizontal or hybrid scaling model.
Finally, remember that third-party vendors can provide cutting-edge cloud scalability solutions as well. Depending on your business needs, you can combine your existing infrastructure with their services or completely outsource your requirements. Spend the resources saved by outsourcing to focus on your core competencies.
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