In Cloud Computing, What Is The Difference Between Scalability And Elasticity

Vertical scale, e.g., Scale-Up – can handle an increasing workload by adding resources to the existing infrastructure. Thanks to the pay-per-use pricing model of modern cloud platforms, cloud elasticity is a cost-effective solution for businesses with a dynamic workload like streaming services or e-commerce marketplaces. Turbonomic allows you to effectively manage and optimize both cloud scalability and elasticity.

difference between Elasticity and scalability

Similarly, if a master database shuts down a replica database replaces it on the spot as the new master. This way, no individual server or database can cause your website to shutdown or experience any downtime. ZDNet reported that managers need to weigh adaptability heavily when deciding and negotiating for a cloud solution. Internal and external conditions change so rapidly today that a company may need to add or decommission cloud capacity on short notice.

Example Of Cloud Elasticity

The solution to running a WordPress website is to consistently handle any amounts of traffic, small or large. People often mix elasticity and scalability with one another or consider them as one and the same. Because these two terms describe similar occurrences, they are often used interchangeably. But they aren’t interchangeable, and as such, shouldn’t be considered synonymous with each other. What they are is intertwined — because an elastic cloud must simultaneously be scalable up and out.

difference between Elasticity and scalability

Increases in data sources, user requests and concurrency, and complexity of analytics demand cloud elasticity, and also require a data analytics platform that’s just as capable of flexibility. Before blindly scaling out cloud resources, which increases cost, you can use Teradata Vantage for dynamic workload management to ensure critical requests get critical resources to meet demand. Leveraging effortless cloud elasticity alongside Vantage’s effective workload management will give you the best of both and provide an efficient, cost-effective solution.

Cloud Computing: Elasticity Vs Scalability

In the digital world, elastic scaling works by dynamically deploying extra virtual machines or by shutting down inactive ones. The purpose of Elasticity is to match the resources allocated with actual amount of resources needed at any given point in time. Scalability handles the changing needs of an application within the confines of the infrastructure via statically adding or removing resources to meet applications demands if needed. In most cases, this is handled by adding resources to existing instances—called scaling up or vertical scaling—and/or adding more copies of existing instances—called scaling out or horizontal scaling. In addition, scalability can be more granular and targeted in nature than elasticity when it comes to sizing. This means that your data center provider can dynamically increase or decrease the resources they provide to you based on your requirements at any given time.

  • There are plenty that appears similar yet contain contrasting definitions.
  • If your existing architecture can quickly and automatically provision new web servers to handle this load, your design is elastic.
  • This guide covers everything you need to know about the key differences between scalability and elasticity.
  • Join us at the leading event on applied AI for enterprise business and technology decision makers in-person July 19 and virtually from July 20-28.
  • Organizations always need to be able to handle an increased workload.
  • As can you no doubt tell from the above definitions, there are various factors that separate the two terms.

Along with event-driven architecture, these architectures cost more in terms of cloud resources than monolithic architectures at low levels of usage. However, with increasing loads, multitenant implementations, and in cases where there are traffic bursts, they are more economical. The MTTS is also very efficient and can be measured in seconds due to fine-grained services. Tech-enabled startups, including in healthcare, often go with this traditional, unified model for software design because of the speed-to-market advantage. But it is not an optimal solution for businesses requiring scalability and elasticity.

What Are The 5 Main Types Of Clouds Computing?

How to Create a Multi-cloud StrategyLearn how to create a robust multi-cloud strategy that increases efficiency, saves costs, and helps adopt new technologies in your organization. This guide covers everything you need to know about the key differences between scalability and elasticity. Scalability and elasticity are the most misunderstood concepts in cloud computing. In this type of scalability, we increase the power of existing resources in the working environment in an upward direction.

Elasticity provides the functionality to automatically increase or decrease resources to adapt dynamically based on the workload’s demands. Even though it could save some on overall infrastructure costs, elasticity isn’t useful for everyone. Services that do not exhibit sudden changes in workload demand may not fully benefit from the full functionality that elasticity provides. Cloud elasticity does its job by providing the necessary amount of resources as is required by the corresponding task at hand. This means that your resources will both shrink or increase depending on the traffic your website’s getting.

difference between Elasticity and scalability

This allows sites to handle any unexpected surges in traffic at any given time, with no effects on performance. According to TechTarget, scalability is the ability on the part of software or hardware to continue to function at a high level of performance as workflow volume increases. In addition to functioning well, the scaled up application should be able to take full advantage of the resources that its new environment offers. For example, if an application is scaled from a smaller operating system to a larger one should be able to handle a larger workload and offer better performance as the resources become available. Some of the real time examples for your system to be Elasticity ready are retail services sales like Christmas, Black Friday, Cyber Monday, or Valentine’s day. As cloud elasticity allows resources to be built out dynamically, this is a common feature of pay-per-use or pay-as-you-go services.

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It basically helps you understand how well your architecture can adapt to the workload in real time. It is a mixture of both Horizontal and Vertical scalability where the resources are added both vertically and horizontally. Well, you get diagonal scaling, which allows you to experience the most efficient infrastructure scaling. When you combine vertical and horizontal, you simply grow within your existing server until you hit the capacity. Then, you can clone that server as necessary and continue the process, allowing you to deal with a lot of requests and traffic concurrently. Cloud scalability in cloud computing refers to increasing or decreasing IT resources as needed to meet changing demand.

There are an expected number of desktops based on employee population. To ensure the ability to support the maximum number of users and meet SLAs, the amount of services purchased must be enough to handle all users logged in at once as a maximum use case. In short, the amount of resources allocated are there to handle the heaviest predicted load without a degradation in performance. To determine the correct size solution, continuous performance testing is essential. IT administrators must continuously measure response times, number of requests, CPU load, and memory usage. Scalability testing also measures the performance of an application and its ability to scale up or down based on user requests.

In other words, it is the ability of a system to remain responsive during significantly high instantaneous spikes in user load. If the system is not adaptable but is scalable, it does not comply with the definition of Cloud. To help you think about the differences between these two, let’s try two images. First, visualize an elastic band stretching out or back into its original size.

Scalable cloud architecture is made possible through virtualization. Unlike physical machines whose resources and performance are relatively set, virtual machines virtual machines are highly flexible and can be easily scaled up or down. They can be moved to a different server or hosted on multiple servers at once; workloads and applications can be shifted to larger VMs as needed. Data storage capacity, processing power, and networking can all be increased by using existing cloud computing infrastructure. Scaling can be done quickly and easily, usually without any disruption or downtime.


Horizontal scaling is the ability to scale out to handle the load of added users. Additional servers, software, and other resources may need to be added to an existing network. To implement effectively, it is important to remember that this will require anticipation of future needs. Some cloud services are considered adaptable solutions where both scalability and elasticity are offered. They allow IT departments to expand or contract their resources and services based on their needs while also offer pay-as-you-grow to scale for performance and resource needs to meet SLAs. Incorporation of both of these capabilities is an important consideration for IT managers whose infrastructures are constantly changing.


It can be a more affordable option for startups as the business is not paying for more IT infrastructure than it needs to begin. Or, in another scenario, elasticity can prove valuable to an organization that has spikes in demand such as an e-retailer handling seasonal sales or Black Friday shoppers. Before you learn the difference, it’s important to know why you should care about them. If you’re considering adding cloud computing services to your existing architecture, you need to assess your scalability and elasticity needs.

Cloud elasticity is one of the most important features of cloud computing, and a major selling point for organizations to migrate from their on-premises infrastructure. But what is cloud elasticity exactly, and what are the benefits of cloud elasticity? Below, we’ll discuss everything you need to know about elasticity in cloud computing.

The new space allowed it to accommodate 33 more people and install a temporary kitchen. Learn how we’ve helped happy customers like SeatGeek, Drift, Remitly, and more. Office portal – for the accounting department and support staff to collect payments and address queries. If you are unsure which scaling technique better suits your company, you may need to consider a third-party cloud engineering automation platform to help manage your scaling needs, goals and implementation. Here’s how you can migrate your existing WordPress website to 10Web very easily 👍.

According to the definition of cloud computing, as stated by NIST in 2011, elasticity is considered a fundamental characteristic of cloud computing. But not all cloud platform services support the scaling in and out involved in cloud elasticity. Three excellent examples of cloud elasticity at work include e-commerce, insurance, and streaming services. That is how cloud elasticity is different from cloud scalability, in a nutshell.

It is a common feature in pay-per-use or pay-as-you-grow services, meaning IT managers aren’t paying for more resources than they are consuming. While scalability helps handle long-term growth, elasticity ensures flawless service availability at present. It also helps prevent system overloading or runaway cloud costs due to over-provisioning. The answer is scalability and elasticity — two essential aspects of cloud computing that greatly benefit businesses.

The pay-as-you-expand model would also let you add new infrastructure components to prepare for growth. Existing customers would also revisit old wishlists, abandoned carts, or try to redeem accumulated points. This would put a lot more load on your servers during the campaign’s duration than at most times of the year. Over-provisioning leads to cloud spend wastage, while under-provisioning can lead to server outages as available servers are overworked.

CIOs, cloud engineers, and IT managers should consider when deciding to add cloud services to their infrastructure. Cost, security, performance, availability, and reliability are some common key areas to consider. Another criterion that has been added to the list recently is cloud scalability vs elasticity scalability and cloud elasticity. Storage resource demand is, for the most part, a lumpy, non-linear process with imperfect predictability — there are always ebbs and flows. Some applications may require peak resources at the end of a quarter or during the early morning hours.

In another way, growing or shrinking the resources dynamically when needed is known as Elasticity. Cloud reliability is a measure of the probability that the cloud delivers the services it is designed for. This implies that the service is available, and performs in the way intended.

Scalability is one of the driving reasons for migrating to the cloud. Horizontal scaling refers to adding more servers to your network, rather than simply adding resources like with vertical scaling. This method tends to take more time and is more complex, but it allows you to connect servers together, handle traffic efficiently and execute concurrent workloads. Cloud scalability in cloud computing refers to the ability to increase or decrease IT resources as needed to meet changing demand. Scalability is one of the hallmarks of the cloud and the primary driver of its exploding popularity with businesses. In order to achieve scalability, a system must be able to handle larger loads by either increasing hardware capacity or adding additional nodes .

Teradata Vantage: Intelligence Powered By The Cloud

In AWS, the process of getting the resources dynamically when you actually require them and then release the resources when you are done and do not need them is known as elasticity. Storage scalability is commonly measured in terms of capacity and performance. Capacity scalability is how much capacity the storage system can address, manage and support with acceptable performance. There are several storage systems that can address a lot of capacity as long as acceptable performance isn’t a requirement. There are others that can address, support and manage even more capacity while maintaining acceptable performance regardless of the scale. Performance scalability is the storage system’s ability to scale performance with or without capacity in the form of IOPS and/or throughput.

Cloud Elasticity To The Rescue

Cloud elasticity enables software as a service vendors to offer flexible cloud pricing plans, creating further convenience for your enterprise. Scalability in the cloud refers to adding or subtracting resources as needed to meet workload demand, while being bound by capacity limits within the provisioned servers hosting the cloud. Elasticity, on the other hand, is useful for discussing shorter term resource needs, such as sudden bursts of traffic that could threaten to overwhelm an e-commerce site.