Cloud Elasticity Vs Cloud Scalability

Cloud applications can be of varying types and complexities, with multiple levels of artifacts deployed in layers. Controlling such structures must take into consideration a variety of issues, an approach in this sense being rSYBL. Elastic strategies on Clouds can take advantage of control-theoretic methods (e.g., predictive control has been experimented in Cloud scenarios by showing considerable advantages with respect to reactive methods). Of course, the problem with this approach is that Black Friday occurs just once a year, and there are 364 other days in the year where this level of capacity may not be required.

ComponentsGroups – logical groups containing a collection of EC2 instances with similar characteristics for scaling and management purpose. Internal usage – application team using development and test environments. Complete Controller is not affiliated with or endorsed by Intuit Inc. Complete Controller is solely responsible for the provision of all services on or accessed through this website. You need to go ahead and configure cloud front to allow «upload requests» like POST, PUT, etc.

  • Scaling up, or vertical scaling, is the concept of adding more resources to an instance that already has resources allocated.
  • So scalability is about handling more load by increasing available resources, either vertically or horizontally .
  • Cloud elasticity solves this problem by allowing users to dynamically adapt the number of resources – for example, the number of virtual machines – provisioned at any given time.
  • Both, Scalability and Elasticity refer to the ability of a system to grow and shrink in capacity and resources and to this extent are effectively one and the same.
  • It also ensures extra unanticipated and sudden sales activities throughout the year whenever required without affecting availability or performance.
  • The ability to scale up is not as efficient as reacting swiftly to a downtime or service shutdown.

Users sometimes access websites more often at certain times of the day. The ability to scale up and scale down is related to how your system responds to the changing requirements. Elastically in the context of cloud computing, it is required that the scaling of the system is quick, and it means the variable demands that the system exhibit. To scale vertically , you add or subtract power to an existing virtual server by upgrading memory , storage or processing power . This means that the scaling has an upper limit based on the capacity of the server or machine being scaled; scaling beyond that often requires downtime. Usually, this means that hardware costs increase linearly with demand.

It Helps Provide Smooth Services

However, unfortunately many customers’ views are muddied by some providers who market the more expensive elastic cloud option irrespective of the size and kind of businesses. With the cost of hardware declining, it can make sense to adopt horizontal scaling using low-cost commodity systems for tasks that previously required larger computers. Of course, horizontal scaling can be limited by the capability of software to exploit networked computer resources and other technology constraints. Keep in mind, too, that traditional database servers cannot run on more than a few machines . Elasticity is the ability of a system to manage available resources based on the current workload requirements.

For elasticity, it’s an actor changing their body weight to meet the numerous demands of the film industry. When deploying applications in cloud infrastructures (IaaS/PaaS), requirements of the stakeholder need to be considered in order to ensure proper elasticity behavior. Elasticity is usually enabled by closely integrated system monitoring tools that are able to interact with cloud APIs in real-time to both request new resources, as well as retire unused ones.

The bank chose MarkLogic to build their operational Trade Store for regulatory compliance. The Trade Store has elastic provisioning for 40+ million records and growing. By moving off relational, they achieved flexibility and success in meeting regulatory deadlines. The whitepaper introduces basic MarkLogic terms for those readers who might be new to the product and concepts.

scalability vs elasticity

Things like cost, performance, security and reliability come up often as key points of interest to IT departments. Joining those criteria at the top of the list of importance are the concepts of scalability and elasticity. Healthcare services were heavily under pressure and had to drastically scale during the COVID-19 pandemic, and could have benefitted from cloud-based solutions. 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.

There are three main types of cloud computing services, sometimes called the cloud computing stack because they build on top of one another. Many businesses face a growing network and the need to maintain fast network speeds during expansion. This means they must position computing resources closer to users since server distance is the main limitation of latency. Edge computing allows companies to target high-traffic regions with edge nodes and edge PoPs to improve latency — enhancing user experience and allowing for more advanced applications. Cloud scalability enables businesses to handle a growing workload with two important characteristics.

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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. Cloud elasticity is a well-renowned feature related to horizontal scaling or scale-out solutions that allows system resources to be added or removed dynamically whenever required. Flexibility is more generally featured in pay-as-you-expand or pay-per-use services and is commonly related to public cloud resources.

Furthermore, you need to decide if you need to run your system on the cloud or not. Unfortunately, demand drops and spike quickly until the system support team is competitive enough to additional backup services online. There could have been an outrageous of servers, resulting in the losses of customers. According to the definition of cloud computing, as stated by NIST in 2011, elasticity is considered a fundamental characteristic of cloud computing. A stateless web application layer – these generally have very good elasticity as being stateless makes it very easy to add and remove backend instances of the application.

Weigh Up How Application Architects Affect Scalability And Elasticity

All of these resources that need to support the workload are often pre-planned capacity featuring a headroom’s certain amount built in to tackle peak requirements. In some cases, even without a hard limit, the ability to grow with extra infrastructure resources also comes under scalability. Thus, applications must have enough room to scale out or scale up to prevent performance hindrances due to lack of resourcefulness. There are several cases where a company’s IT manager knows that there is no further need for resources and will subsequently scale down the infrastructure to support a smaller new environment.

One such aspect is the cloud’s elastic and scalable capabilities, that have risen to form one of the most important features of cloud services. To put it simply, these two features are responsible for the way your website handles traffic and its possible surges. In this healthcare application case study, this distributed architecture would mean each module is its own event processor; there’s flexibility to distribute or share data across one or more modules. There’s some flexibility at an application and database level in terms of scale as services are no longer coupled. The hospital’s services are in high demand, and to support the growth, they need to scale the patient registration and appointment scheduling modules. This means they only need to scale the patient portal, not the physician or office portals.

scalability vs elasticity

But not all cloud platform services support the scaling in and out involved in cloud elasticity. An elastic cloud provider provides system monitoring tools that track resource utilization. The goal is always to ensure these two metrics match up to ensure the system performs at its peak and cost-effectively. Netflix engineers have repeatedly said they take advantage of elastic cloud services by AWS to serve such numerous server requests within a short time and with zero downtime.

In this digital age, companies want to increase or decrease IT resources as needed to meet changing demands. The first step is moving from large monolithic systems to distributed architecture to gain a competitive edge – this is what Netflix, Lyft, Uber and Google have done. However, the choice of which architecture is subjective, and decisions must be taken based on the capability of developers, mean load, peak load, budgetary constraints and business-growth goals. It is worth noting, however, that there is an inherent limit to systems that rely on vertical scaling – since there is usually a maximum server size available on all public clouds.

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Scaling out or in refers to expanding/shrinking an existing infrastructure’s resources by adding new/removing existing components. When a cloud provider matches resource allocation to dynamic workloads, such that you can take up more resources or release what you no longer need, the service is referred to as an elastic environment. The process is referred to as rapid elasticity when it happens fast or in real-time. Some companies have highly predictable growth and consistent computing environments, while others have workloads that fluctuate depending on demand and the time of year. Thankfully, cloud computing gives companies more flexibility in how they set up their infrastructure as well as access to more resources than is possible when using on-premise equipment. It’s been ten years after NIST clarify the difference between scalability vs. elasticity.

The scaling out or scaling up concept, also known as horizontal scaling, is a technique of cloning resources to meet the variable requirement. Sometimes elasticity can be related to infrastructure artificially as well as scalability to applications. The definition of NIST refers to capabilities and not application or infrastructure.

Database Trends and Applications delivers news and analysis on big data, data science, analytics and the world of information management. Sarah Weber is a curious and driven digital marketer with a diverse background working on digital teams within technology, medical, agencies, and consumer packaged goods. Sarah Weber graduated from Messiah College with a Bachelor of Science in Marketing. In her free time, Sarah can be found spending time with friends and her dog, hiking in Shenandoah, or sewing up a new pattern. It turns out, one of these features generally attributed to the cloud is, in fact, more “cloudy” than the other. Here’s how you can migrate your existing WordPress website to 10Web very easily 👍.

As another example, you can configure your system to increase the total disk space of your backend cluster by an order of 2 if more than 80% of the total storage currently available to it is used. If for whatever reason, at a later point, data is deleted from the storage and, say, the total used storage goes below 20%, you can decrease the total available disk space to its original value. 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. However, with the sheer number of services and distributed nature, debugging may be more difficult and there may be higher maintenance costs if services are not fully automated. Allows you to match the supply of resources—which cost money—to demand.

It is wise to consider the tradeoffs between horizontal and vertical scaling as you consider each approach. Vertical scaling has been a standard method of scaling for traditional RDBMSs that are architected on a single-server type model. Nevertheless, every piece of hardware has limitations that, when met, cause further vertical scaling to be impossible. For example, if your system only supports 256 GB of memory, when you need more memory you must migrate to a bigger box, which is a costly and risky procedure requiring database and application downtime.


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. System scalability is the system’s infrastructure to scale for handling growing workload requirements while retaining a consistent performance adequately. Many have used these terms interchangeably but there are distinct differences between scalability and elasticity.

Cloud Services Considerations

One of the most significant differences between on-premise and cloud computing is that you don’t need to buy new hardware to expand your cloud-based operations as you would for an on-prem system. When demand dissipates, MarkLogic can scale back down without having to worry about complex sharding. With these features, organizations scalability vs elasticity can handle incredible volumes of data and run large scale web applications—all without breaking the bank. Different components of a service may also exhibit different elasticity and scalability characteristics, with the overall elasticity or scalability of the entire service falling to the lowest out of all the components .

This guide will explain what cloud elasticity is, why and how it differs from scalability, and how elasticity is used. We’ll also cover specific examples and use cases, the benefits and limitations of cloud elasticity, and how elasticity affects your cloud spend. The additional storage would help your bots collect more data in one place. Then, if you use machine learning and big data analytics, the bots would rapidly query the data and find best-fit responses to relevant questions.

Traditionally, when designing a system, engineers and architects would need to plan for and provision sufficient computing capacity in order to handle the maximum possible peaks in demand. For a retailer or bank, for example, this could be the annual Black Friday sales when the number of users visiting a website and making purchases is likely to be at their absolute peak. Mention what is the difference between elasticity and scalability in … For example, if you run a business that doesn’t experience seasonal or occasional spikes in server requests, you may not mind using scalability without elasticity.

Example Of Cloud Scalability

Another use case is special sporting events like the Super Bowl that experience much more traffic than regular-season games. Cloud edge solutions are crucial to managing organizational costs while increasing the computing power available to your applications. When you need to integrate massive volumes of data, it is imperative to have a database that scales quickly, easily, and at low cost. But, it is also important to have elasticity—to be able to scale down based upon fluctuating demand.

Cloud Elasticity Vs Scalability: Main Differences To Know About

At the risk of stating the obvious, there are distinct differences between elasticity and scalability. In the end, the best choice depends on the business need or use case. This will help determine whether an elastic service or scalability service is the ideal one. As can you no doubt tell from the above definitions, there are various factors that separate the two terms.

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