What is Elasticity in Cloud Computing?

Prerequisite

An important prerequisite to elastic computing is understanding the concept of cloud computing first. You can read about Introduction to Cloud Computing from this article on Scaler Topics.

What is Elasticity in Cloud Computing?

Elastic computing is a subset of cloud computing that involves dynamically increasing/decreasing the capacity of the cloud servers according to the requirement. The ability of a cloud to expand or decrease its capacity for CPU, memory, and storage resources in response to shifting organizational needs is known as cloud elasticity.

Cloud Elasticity can be automatic, requiring no capacity planning ahead of time, or it can be a manual process, alerting the company when resources are running low and allowing it to choose to increase or decrease capacity as needed. The elasticity process should proceed quickly, almost instantly. Delays in scaling down could result in your servers remaining idle, which would incur unnecessary cloud costs, while delays in scaling up could result in overcrowding and outages. The cloud provider's monitoring tools allow for dynamic resource allocation adjustments without affecting the currently running cloud-based operations. The term cloud elasticity is frequently used to describe horizontal scaling architecture and is typically used to describe resources offered by public cloud providers that are charged on a pay-as-you-go basis. This method more closely aligns real-time cloud spending with the actual use of cloud services.

As per how well a cloud service provider can conform to varieties in workload via independently giving or de-provisioning assets to best fulfill the need, a cloud supplier is considered to have pretty much or less elasticity. As a result, there is no longer a need for IT administration workers to keep an eye on resource usage to evaluate whether more CPU, memory, or storage resources are required or whether any extra capacity may be turned off. Thanks to cloud elasticity, businesses, and IT teams can respond to any unforeseen spikes in demand, eliminating the need to keep backup equipment on hand. When a demand arises for a service that an organization typically provides on-premises, it can cloudburst to meet that need, switching back to on-premises operations only when the demand has subsided. As a result, cloud elasticity reduces infrastructure, human resources, and total IT expenditures.

Example :

Think about an E-commerce services provider whose volume of transactions rises during holidays like Diwali and Christmas. Therefore, the resources (CPU, memory, servers) must be increased for this particular period to cater to the increased demands. We can use cloud-elasticity services rather than cloud scalability to manage this kind of problem. The deployed resources can be withdrawn when the season has ended, i.e., the demand has been rescinded.

How Does Cloud Elasticity Differ from Cloud Scalability?

Thanks to cloud elasticity, you can match the allocated resources with the necessary resources at any given time. With cloud scalability, you might alter the resources that are now set up to oblige changing application requests. You can accomplish this by adding or eliminating resources to existing cases - in an upward direction increasing or down — or by adding or eliminating resources from existing examples — evenly scaling out or in. At the point when you don't need the resources, you may statically support a more modest environment by downsizing the framework.

Difference Between Cloud Elasticity and Scalability:

Why is Cloud Elasticity Important?

Businesses would be compelled to pay for mainly underutilized capacity and manage it through component failures, network updates, operating system level updates, patching, etc., if Cloud Elasticity didn't exist. In many respects, the elastic nature of cloud computing distinguishes it from more established computing paradigms like client-server, grid computing, and legacy infrastructure. Companies can prevent either under or over-provisioning with the help of cloud elasticity. Under-provisioning might make it hard to satisfy demand, leading to unacceptable latency, irritated users, and ultimately lost sales as customers abandon time-consuming online transactions in favor of more responsive companies. A lack of cloud elasticity in this strategy could lead to lost revenue and detrimental repercussions on the bottom line. Organizations that overprovision spend more than necessary to satisfy their requests, wasting money that may be utilized elsewhere. Lack of elasticity could cause VM wastage even for businesses that are already using the public cloud, costing thousands of dollars annually.

How Does Cloud Elasticity Work?

Because of the elasticity of the cloud, businesses may quickly scale capacity up or down, manually or automatically. Cloud elasticity, for instance, can be used to cloudburst from on-premises infrastructure into the public cloud to meet a sudden or seasonal demand. An application's ability to increase or decrease its resource usage is called an application's cloud elasticity.

Instances of cloud elasticity can be started manually, often within minutes, or automatically depending on workload trends. Before using Cloud Elasticity, organizations had to either have extra stand-by capacity on hand or purchase, configure and deploy more capacity, a process that may take weeks or months. If and when demand decreases, capacity can be eliminated in a couple of minutes. Businesses avoid having to purchase or retire on-premises infrastructure this way because they only pay for the resources that are being used at any given time.

Typical Use Cases for Cloud Elasticity

With every day that goes by, elastic computing becomes more and more well-known, and several e-commerce, mobile, and web development firms worldwide are starting to employ it. Nowadays, organizations concentrate on enhancing their digital initiatives by staying one step ahead of the competition and pursuing ongoing scalability and agility. Now that we've grasped the idea of elastic computing let's look at a few illustrations.

1. E-commerce applications :
   One of the best examples to demonstrate the use case of cloud elasticity is the case of E-commerce websites like Amazon, Flipkart, Myntra, Lenskart, etc. Assume that Lenskart holds a special sale in honor of any holiday, such as Diwali, Christmas, Halloween, etc. People worldwide eagerly anticipate these days to take advantage of special discounts, promotions, and offers before returning to their abandoned carts to complete their wish lists. While shopping, adding items to carts, making purchases, paying for them, reading reviews, and other activities, customers may be doing numerous things at once. This results in increased traffic and stress on Lenskart's servers. With elastic computing, you might scale up the resources in your applications to handle peak festival seasons' high customer demand. The extra capacity and resources can be relinquished after the sale and only maintain what the organization genuinely needs to run the business.

2. Streaming Services :
   Streaming Services like Netflix and Amazon Prime also use the concept of Elastic computing. This can be understood as follows. For example, a highly awaited series is scheduled to be released on a particular date and time. So, when it is released, these streaming platforms will experience heavy traffic on their app/website, which was very much anticipated in advance. Elasticity comes in handy in this situation. Millions of viewers can stream their favorite programs simultaneously thanks to the addition of more resources, which can handle both unexpected and anticipated traffic surges at any given point. So these streaming platforms can hire additional resources to cater to these highly increased demands during peak hours. Once the demand goes down gradually, they can free up the previously acquired resources, thereby avoiding any extra cost.

3. Ticket Booking Platforms :
   As was the case with streaming services, whenever a new movie featuring a big star is released, the cinema hall's ticket booking portal faces high traffic as many people would try to buy the tickets for the first show of the first day. A similar case might be with the railway/air travel tickets booking portal during the time of vacations. In both these cases, using elastic computing can solve the problem and prevent any possible outrage or downtime. Hiring an additional pool of resources within a matter of minutes and releasing them immediately once the demand is over allows these companies to handle high traffic with the minimum cost incurred.

4. Temporary projects :
   Elastic computing supports a company's digital transformation strategy. Following the commencement of the COVID-19 pandemic, the bulk of the workforce started working from home. Thanks to elastic computing, virtual desktop infrastructure may now be deployed in the cloud for remote employees or contract-based temporary workers and freelancers. Its use may also be advantageous for unplanned jobs with short deadlines, such as media rendering, data processing, and data analytics.

Key Components of Elastic Computing

Large businesses worldwide can employ elastic computing, a flexible powerhouse, to propel their operations forward. The requirement to purchase additional IT hardware resources is removed with elasticity. Instead, it lets you add as few or as few resources as you need to handle unforeseen increases in demand. Google Cloud Platform (GCP), Microsoft Azure, Amazon Web Services (AWS), Digital Ocean, Alibaba Cloud Platform, and Heroku are among the most well-known and dependable cloud service providers aiding businesses in this way. This takes us to the key elements of elastic computing that are shared by the majority of the aforementioned cloud service providers.

1. Operating system support :
   It is preferred by businesses to have many alternatives available to them for the choice of the operating system that can be used. Different business needs may pick a different OS. For example, one business might choose Microsoft Windows Servers for their operations, whereas another might opt for Linux or Oracle Enterprise-based OS. Thus, cloud service providers should be able to support a variety of operating systems.

2. Instances and Images :
   An Instance or an elastic cloud computing instance refers to a virtual server/computing environment that contains a package of an OS, CPU (i.e., computing power), RAM, storage (hardware), and flexible network configurations. There can be multiple types of these instances, each with unique requirements. Operating systems like Linux and Microsoft Windows servers are given images that contain initialized data for the programs and preinstalled software they need.

3. Storage options :
   Elastic block storage, in short, EBS, is the extra storage that the cloud service provider provides to handle the workload demands and needs of an organization. The benefit of EBS is the high performance and the reduced latency that it brings onboard.

4. Snapshot :
   A snapshot is like a picture we take to back up data. A snapshot can be used to back up and restore a complete drive. Snapshots help capture the exact point-in-time status of a hard disc and also help in the creation of custom images. In catastrophic situations where you run the danger of losing essential data, snapshots are an excellent tool, making recovery data backup vital.

5. Networks and Regions :
   In terms of packets per second (PPS), upgraded networks perform noticeably better. There are also, if any, fewer latency issues and network jitters. Traditional networks built on shared infrastructure networks and virtual private clouds (VPCs) built on independent private cloud networks are two commonly used networks. Thanks to elastic cloud computing service providers, users can deploy instances across several locations and availability zones. Consequently, the failure of one of your applications won't affect the others. Availability zones are discrete locations that offer other zones in the same region low-cost, low-latency network connectivity. "Regions" refers to a variety of geographical regions or countries made up of one or more availability zones.

Best Practices for Elastic Computing

Businesses may build high-performing, scalable, reliable, and failure-resistant applications using the benefits of elastic cloud computing. To get the most out of elastic computing and ensure that the requirements of your intended workload are met, have a look at this list of these best practices.

1. Security :
   One of the main issues with elastic computing is security. The largest companies worldwide are also unprotected from security lapses and significant online attacks. The growing internet exposure of cloud-based systems makes them an accessible target for hackers and attackers as well. Associations should thus rigorously stick to security best practices while overseeing access controls and accreditation of the executive's approaches and cycles. It is important to provide high security at each tier. Some good methods include creating, distributing, and rotating security keys frequently. Organizations should revoke access rights to protect their credentials. Additionally, regular operating system and application maintenance should be planned ahead of time. It is important to get the upgrading and patching work of the operating system and network in use done timely to avoid any possible security threats.

2. Resource Management and Storage Space :
   The key value of elastic computing rests in the cloud service provider's capacity to offer enterprises additional resources to manage their workload flexibly. You should likewise expect your exact asset needs and present a solicitation for them ahead of time. Resource management is consequently pivotal in this present circumstance. To monitor and determine the status of the additional resources you requested, you can use instance metadata and custom resource tags. You can accommodate and store as much data as you want with elastic cloud computing, which offers endless storage capacity. In this instance, use elastic block storage space (EBS) for the operating system instead of your data. You can also save your temporary data on the instance storage. It's essential to have a cluster with a replication factor that gives fault tolerance if you use the instance store to store your database. It would help if you hibernate or cease using your instance because another crucial thing to remember is that the data stored in the instance storage will automatically trash itself after the process has been halted.

3. Backup, recovery, and disaster management :
   Setting up a methodology for information reinforcement and recuperation is significant for various reasons. Numerous cloud service providers provide a variety of adaptable and reliable backup and recovery solutions. Regular EBS backups utilizing snapshots and image generation are also essential. This makes it possible to record the current configuration and use it as a model for subsequent occurrences. Deploying application data across various availability zones and meticulously replicating data are other steps you should take. Being caught off guard is much worse than being ready for failure. Start by assuming that everything will fail, then design solutions in reverse response. Doing this will make it possible to continue using the program even if certain instances fail, are deleted, or are replaced. Your applications' top priority should be using fault-tolerance services. By deploying a replica of failing servers that can be quickly activated with continuous monitoring, fault tolerance is leveraged. This makes it possible to redeploy identical copies of a production server promptly. Embracing a strategy like this enables servers to be designed for failure, resulting in uniform servers that are simple to copy without spending a lot of money.

What are the Benefits of Cloud Elasticity?

The benefits of cloud elasticity include :

1. Pay-as-you-go pricing :
   By tightly connecting IT spending to actual demand in real-time, cloud elasticity enables organizations to only pay for the resources that are being actually used at any time. Since elasticity automatically distributes or reallocates resources based on current demand, it enables businesses to right-size their infrastructure despite potential spending fluctuations.

2. High Availability :
   Cloud elasticity empowers high accessibility and issue tolerance since VMs or containers can be cloned assuming they seem, to be failing, guaranteeing that business services are continuous and clients don't encounter downtime. Clients are given a steady and unsurprising experience notwithstanding resources being naturally provisioned or de-provisioned without disturbing operations.

3. Agility :
   Cloud Elasticity forestalls the need to anticipate unforeseen interest spikes by eliminating the need to purchase, design, and put in a new framework when request changes. This permits associations to fulfill any startling need, whether it results from an occasional spike, a notice on Twitter, or a choice by Times Magazine.

4. Speed/Time-to-market :
   Instead of waiting weeks or months for capacity to become available through a traditional procurement process, organizations can access it in a matter of minutes.

5. Efficiency :
   Like with other automation, the ability to automatically modify cloud resources as necessary frees up IT professionals to concentrate on tasks that are more advantageous to the organization rather than provisioning.

What are the Challenges of Cloud Elasticity?

Only enterprises that regularly or suddenly see a rise or fall in demand for IT services can benefit from cloud elasticity. The advantages of cloud elasticity are likely not advantageous to businesses with known, continuous demand. Some of the possible difficulties with cloud elasticity include the following :

1. Vendor Lock-In :
   Although the Cloud Elasticity solution is offered by all of the top public cloud providers, organizations are limited to working with a single vendor for their cloud requirements due to their varied architectures.

2. Time to provision :
   Even while cloud VMs can be started whenever they are needed, there may still be a delay of up to several minutes before they are usable. Depending on the demands of a particular application or service, this may or may not be sufficient time. It might affect performance when a sudden spike happens, such as when a sign-on storm occurs at the start of a business day.

3. Availability of Resources :
   Existing cloud or on-premises deployments must be modified to take advantage of cloud elasticity. Suppose an organization doesn't outsource its IT administration. In that case, it will need to hire technical staff, such as architects, developers, and administrators, to ensure that a Cloud Elasticity plan is set up to suit the organization's requirements. As the newly acquired talent becomes familiar with the new environments, languages, automation tools, and processes that must be used, this may also cause a learning curve delay.

4. Security Impact :
   Cloud services that scale elastically may have an impact on present security procedures and require revision. Elastic systems' transience may hamper an event reaction.