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Cloud Scalability Vs Cloud Elasticity

A shipping company may need to increase resources during a holiday season, then reduce them after the holiday. Say we have a system of 5 computers that does 5 work units, if we need one more work unit to be done we we’ll have to use one more computer. Also, if a new computer is purchased and the extra work unit is not needed any more, the system get stuck with a redundant resource. Not all AWS services support elasticity, and even those that do often need to be configured in a certain way. Elasticity is the ability for your resources to scale in response to stated criteria, often CloudWatch rules. Scalability is largely manual, planned, and predictive, while elasticity is automatic, prompt, and reactive to expected conditions and preconfigured rules.

  • Scalability and Elasticity both refer to meeting traffic demand but in two different situations.
  • Over time as the business grows so will the database and the resource demands of the database application.
  • Various seasonal events and other engagement triggers (like when HBO’s Chernobyl spiked an interest in nuclear-related products) cause spikes in customer activity.
  • But a scalable system can use increased compute capacity and handle more load without impacting the overall performance of the system.
  • Say we have a system of 5 computers that does 5 work units, if we need one more work unit to be done we we’ll have to use one more computer.
  • It’s more flexible and cost-effective as it helps add or remove resources as per existing workload requirements.

These resources required to support this are usually pre-planned capacity with a certain amount of headroom built in to handle peak demand. Scalability also encompasses the ability to expand with additional infrastructure resources, in some cases without a hard limit. Scalability can either be vertical (scale-up with in a system) or horizontal (scale-out multiple systems in most cases but not always linearly). Therefore, applications have the room to scale up or scale out to prevent a lack of resources from hindering performance. There are cases where the IT manager knows he/she will no longer need resources and will scale down the infrastructure statically to support a new smaller environment.

What Is The Difference Between Scalability And Elasticity?

Do not fall into the sales confusion of services where cloud elasticity and scalability are presented as the same service by public cloud providers. They allow IT departments to expand or contract their resources and services based on their needs while also offering pay-as-you-grow to scale for performance and resource needs to meet SLAs. Microsoft already has pre-provisioned resources we can allocate; we begin paying for those resources as we use them. Opposite to this, if your business is selling software or a small company with predefined growth throughout the year, you should not worry about elastic cloud computing. Having a predictable workload where capacity planning and performance are stable and have the ability to predict the constant workload or a growth cloud scalability may be the better cost saving choice.

Scalability vs Elasticity

In other words, scale up performance without having to worry about not meeting SLAs in a steady pay-as-you-grow solution. Sometimes, the terms cloud scalability and cloud elasticity are used interchangeably. They shouldn’t be, as they have different meanings, although they are related. Elastic workloads are a major pattern which benefits from cloud computing.

Elasticity Vs Scalability Vs Agility Vs High Availability Vs Fault Tolerance Vs Disaster Recovery

Both of them are related to handling the system’s workload and resources. Advanced chatbots with Natural language processing that leverage model training and optimization, which Scalability vs Elasticity demand increasing capacity. Scalability includes the ability to increase workload size within existing infrastructure (hardware, software, etc.) without impacting performance.

Scalability enables stable growth of the system, while elasticity tackles immediate resource demands. In the past, a system’s scalability relied on the company’s hardware, and thus, was severely limited in resources. With the adoption of cloud computing, scalability has become much more available and more effective. Unlike elasticity, which is more of makeshift resource allocation – cloud scalability is a part of infrastructure design. It comes in handy when the system is expected to experience sudden spikes of user activity and, as a result, a drastic increase in workload demand. Elasticity is the ability to grow or shrink infrastructure resources dynamically as needed to adapt to workload changes in an autonomic manner, maximizing the use of resources.

Both of them are adaptable solutions for organizations, but they have specific differences. While elasticity works in those work environments with dynamic working conditions, elasticity does not need any such criteria to work upon. In simpler terms, not owing to Cloud services, elasticity happens to shrink and extend itself depending on the surroundings’ condition.

Cloud scalability includes the ability to increase workload size within existing infrastructure (hardware, software, etc.) without impacting performance. The resources required to support scalability are usually pre-planned capacity with a certain amount of headroom built in to handle peak demand. Scalability also encompasses the ability to expand with additional infrastructure resources—in some cases, without a hard limit.

Cloud Concepts

This type of scalability is best-suited when you experience increased workloads and add resources to the existing infrastructure to improve server performance. If you’re looking for a short-term solution to your immediate needs, vertical scaling may be your calling. For example, there is a small database application supported on a server for a small business. Over time as the business grows so will the database and the resource demands of the database application.

Scalability vs Elasticity

If our workload does benefit from seasonality and variable demand, then let’s build it out in a way that it can benefit from cloud computing. As the workload resource demands increase, we can go a step further and add rules that automatically add instances. As workload resource demands decrease; again, we could have rules that start to scale in those instances when it is safe to do so without giving the user a performance impact. Horizontal scaling works a little differently and, generally speaking, provides a more reliable way to add resources to our application.

For example, if you had one user logon every hour to your site, then you’d really only need one server to handle this. However, if all of a sudden, 50,000 users all logged on at once, can your architecture quickly provision new web servers on the fly to handle this load? System scalability is the system’s infrastructure to scale for handling growing workload requirements while retaining a consistent performance adequately.

Like the clothing, the business would take a sudden hike in the holiday or Christmas season. For the companies at that time, it is crucial to increase resource availability, which would last for a lesser period. The resources need to get back to the original after the season is over. The main aim of cloud elasticity is to ensure that the resources are sufficient at every given point in time.

The additional infrastructure to handle the increased volume is only used in a pay-as-you-grow model and then “shrinks” back to a lower capacity for the rest of the year. A use case where cloud elasticity is necessary would be in retail during increased seasonal activity. For example, during the holiday season (e.g., Black Friday spikes and special sales) there can be a sudden increased demand on the system. This also allows for additional sudden and unanticipated sales activities throughout the year, if needed, without impacting performance or availability. It can also provide big cost savings to retail companies looking to optimize their IT spend, if packaged well by the service provider.

Difference Between Elasticity And Scalability In Cloud Computing

This is used by companies that need high availability and little or no downtime with applications. Now, lets say that the same system uses, instead of it’s own computers, a cloud service that is suited for it’s needs. Ideally, when the workload is up one work unit the cloud will provide the system with another “computing unit”, when workload goes back down the cloud will gracefully stop providing that computing unit. Scalability is the ability of the system to accommodate larger loads just by adding resources either making hardware stronger or adding additional nodes . Cloud elasticity and scalability optimize the infrastructure and ensure that the organizations keep up to the compliance levels.

Scalability vs Elasticity

Two additional criteria that have become increasingly important are cloud scalability and cloud elasticity. For example, say there is a small database application supported on a server for a small business. Over time, as the https://globalcloudteam.com/ business grows, so will the database and the resource demands of the database application. In other words, you can scale up performance without having to worry about not meeting SLAs in a steady pay-as-you-grow solution.

Where Elasticity And Scalability Cross Paths

Both are essentially the same, except that they occur in different situations. Nevertheless, this article does not describe how to improve scalability, because scalability is a systemic issue and there is no one specific solution that can solve it all at once. The reason for the first point is simple, because the system usage is not fixed, so the use of resources will vary with the system usage. But in general, it can still be maintained in a stable state and there will be no significant ups and downs. Companies increasingly are seeing the Cloud as a digital transformation engine as well as a technology that enhances business progression.

You can scale up a platform or architecture to increase the performance of an individual server. As mentioned earlier, cloud elasticity refers to scaling up the computing capacity as needed. It basically helps you understand how well your architecture can adapt to the workload in real time. Scalability is used to fulfill the static needs while elasticity is used to fulfill the dynamic need of the organization.

Usually, this means that hardware costs increase linearly with demand. But the definition of scalability and elasticity in cloud computing is not complete without understanding the clear connection between both these terms. Vertical scale, e.g., Scale-Up – can handle an increasing workload by adding resources to the existing infrastructure. 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.

Say we have a system of 5 computers that does 5 work units, if we need one more work unit to be done we we’ll have to use one more computer. Turbonomic allows you to effectively manage and optimize both cloud scalability and elasticity. In cloud computing, the term cloud scalability refers to the capacity to improve or reduce IT resources, depending on the requirement changing demand. In other words, we can say that scalability is employed to satisfy the static growth in the workload. 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.

Elasticity is the ability of a system to increase its compute, storage, netowrking, etc. capacity based on specified criteria such as the total load on the system. Scalability refers to the ability for your resources to increase or decrease in size or quantity. Modern business operations live on consistent performance and instant service availability. Elasticity and scalability features operate resources in a way that keeps the system’s performance smooth, both for operators and customers. Scalability is an essential factor for a business whose demand for more resources is increasing slowly and predictably. Various seasonal events and other engagement triggers (like when HBO’s Chernobyl spiked an interest in nuclear-related products) cause spikes in customer activity.

Thanks to elasticity, Netflix can spin up multiple clusters dynamically to address different kinds of workloads. But some systems (e.g. legacy software) are not distributed and maybe they can only use 1 CPU core. So even though you can increase the compute capacity available to you on demand, the system cannot use this extra capacity in any shape or form. But a scalable system can use increased compute capacity and handle more load without impacting the overall performance of the system.

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