Scalability, Elasticity, And Efficiency In Cloud Computing


This lets the organization increase or decreases its workload size using the existing cloud infrastructure , without negatively impacting performance. scalability vs elasticity 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.

Over-provisioning refers to a scenario where you buy more capacity than you need. It works to monitor the load on the CPU, memory, bandwidth of the server, etc. When it reaches a certain threshold, we can automatically add new servers to the pool to help meet demand. When demand drops again, we may have another lower limit below which we automatically shut down the server.

Cloud Elasticity Vs Scalability: Main Differences To Know About

ELASTICITY - ability of the hardware layer below to increase or shrink the amount of the physical resources offered by that hardware layer to the software layer above. The increase / decrease is triggered by business rules defined in advance (usually related to application's demands). The increase / decrease happens on the fly without physical service interruption. Advanced chatbots with Natural language processing that leverage model training and optimization, which demand increasing capacity. The system starts on a particular scale, and its resources and needs require room for gradual improvement as it is being used. The database expands, and the operating inventory becomes much more intricate.

If you’re considering adding cloud computing services to your existing architecture, you need to assess your scalability and elasticity needs. This means that the ability to scale a system, which is the ability to increase or decrease resources, is required before a system can be elastic. Elasticity is the system’s ability to take advantage of that scaling ability appropriately and rapidly to demand. However, if you are running a system that is scalable but not elastic, then you are, by definition, not running a cloud. A solution that has been perfected in a year can become obsolete after some years, making it tough for organizations to adapt to the changing needs of customers. With cloud computing, they can now transform their workload to meet today’s needs, without sticking to hardware and resources that were important.

Elasticity Vs Scalability In Cloud Computing: The Final Word

Elasticity is the ability to automatically or dynamically increase or decrease the resources as needed. Elastic resources match the current needs and resources are added or removed automatically to meet future demands when it is needed. In resume, Scalability gives you the ability to increase or decrease your resources, and elasticity lets those operations happen automatically Software system according to configured rules. When you have true cloud elasticity, you can avoid underprovisioning and overprovisioning. Moreover, the efficiency you're able to achieve in everyday cloud operations helps stabilize costs. Cloud elasticity enables software as a service vendors to offer flexible cloud pricing plans, creating further convenience for your enterprise.

If you are willing to charge a higher price and not be locked in, you get flexibility. Using predefined, tested, and approved images, every new virtual server will be the same as others , which gives you repetitive results. It also reduced the manual labor on the systems significantly, and it is a well-known fact that manual actions on systems cause around 70 to 80 percent of all errors. There are also huge benefits to using a virtual server; this saves costs after the virtual server is de-provisioned.

Elasticity Cloud Computing

The pay-as-you-expansion model will let you add new infrastructure components to prepare them for growth. Netflix engineers have repeatedly stated that they take advantage of the Elastic Cloud services by AWS to serve multiple such server requests within a short period and with zero downtime. This will put a lot of load on your server during the campaign's duration compared to most times of the year. Perhaps your customers renew auto policies at roughly the same time every year. There is no downtime and products and services remain available.

Demand scenarios may follow certain patterns expected to test the scalability of the system in specific ways. A demand scenario is characterized by a summary measure of the demand level, which may be the peak level or the average or total demand level. We used different software configurations, hardware settings, and workload generator in this set of experiments to measure the scalability of the two scenarios for both cloud-based software services that have been hosted in EC2. We changed the instance type and the workload generator in order to see the changes in scalability performance when using different and larger experimental settings.

Vertical Scaling

With most modern public clouds, you can use a managed service, such as MongoDB Atlas, to make it easily scale applications both horizontally and vertically. Alright, we know that a cloud solution comes with many advantages amongst which elasticity and scalability seem to be the best. Cloud elasticity helps your business use resources only when it needs them. Instead of having multiple servers running and consuming money, your system upgrades or downgrades taking into account each business’ traffic and needs.

cloud elasticity vs cloud scalability

Elasticity provides the necessary resources required for the current workload but also scales up or down to handle peak utilization periods as well as off-peak loads. Building on our Halloween store example, demand would abruptly end at the end of the month. That is where elasticity comes in — you could ramp down server configurations to meet the lower levels during other periods. Cloud elasticity adapts to fluctuating workloads by provisioning and de-provisioning computing resources. A call center requires a scalable application infrastructure as new employees join the organization and customer requests increase incrementally. As a result, organizations need to add new server features to ensure consistent growth and quality performance. Before you learn the difference, it’s important to know why you should care about them.

What Is The Difference Between Elasticity And Scalability?

As demand on your resources decreases, you want to be able to quickly and efficiently downscale your system so you don’t continue to pay for resources you don’t need. When it comes to elasticity, a cloud solution can bring more resources.

  • The average response times of OrangeHRM for both scenarios and four demand workload levels are shown in Fig.
  • The converse would be scaling down or scaling in when shrinking resources.
  • Cloud environments (AWS, Azure, Google Cloud, etc.) offer elasticity and some of their core services are also scalable out of the box.
  • In the cloud, Scalable and Elastic cloud are two key components of a system, but the choice of each depends on whether your business workload is predictable or not.
  • Cloud elasticity is the cloud’s ability to expand or compress resources based on shifts in workloads and demand.

Expanding the range of quality measurements provides a multiple factor view of quality scalability to support the trade-off options in the context of QoS offerings in the case of service scaling. Both options raise interesting questions and opportunities for further investigation of the technical match between a software system and the cloud platforms on which it may run. It’s been ten years afterNIST clarified the difference between Elasticity vs. Scalability. But cloud elasticity and cloud scalability are still considered equal. But the definition of scalability and elasticity in cloud computing is not complete without understanding the clear connection between both these terms.

Scalability Analysis Comparisons Of Cloud

Adapting to workload changes by dynamic variation in the use of resources. Increasing resources by scaling up/out or decreasing resources by scaling down/in. Strategic resource allocation operation to meet expected long-term demands.

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To scale horizontally , you add more resources like servers to your system to spread out the workload across machines, which in turn increases performance and storage capacity. Horizontal scaling is especially important for businesses with high availability services requiring minimal downtime.

What Does Cloud Elasticity Mean?

A cloud solution may be a home run on things like reliability, security and performance, but if it lacks adaptability, decision makers may want to turn elsewhere. Find out how IronWorker and IronMQ can help you achieve cloud elasticity, reliable performance, and competitive pricing.

cloud elasticity vs cloud scalability

The resources allocated to support this are typically pre-determined capacity with a limited amount of headroom built in to handle maximum demand. Scalability also has the ability with additional infrastructure resources, and sometimes without a limit. As we mentioned above the comparison were based on CPU utilization and throughput without providing any metric or measure. Similarly, Hwang et al. introduces a set of experiments involving five benchmarks, three clouds, and set of different workload generators.