Elasticity Vs Scalability In Cloud Computing

Scalability means having strategies for keeping performance good, even when load increases. Maintainability is in essence about making life better for the engineering and operations teams who need to work with the system. One of the great benefits of cloud computing from Alibaba Cloud is flexibility when it comes to payments. Whether you need a server instance for an hour, a month, a year, or forever, there’s a billing option to suit. Calls to the grid are asynchronous, and event processors can scale independently. With database scaling, there is a background data writer that reads and updates the database.

  • Elasticity, after all, refers to the ability to grow or shrink infrastructure resources dynamically.
  • Cloud elasticity – this term refers to how efficiently your cloud services are able to add or remove resources on-demand.
  • It supports web applications written in Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker on familiar servers such as Apache, Nginx, Passenger, and IIS.
  • Today, the office is no longer just a physical place – it’s a collection of people who need to work together from wherever they are.
  • However, we note that alternative, utility-oriented (i.e. economic cost/benefit focused) approaches are also used in the literature for the conceptualization and measurement of these performance aspects of cloud-based services .
  • It increases redundancy and ensures that you are not dependent on one machine.

The average number of OrangeHRM instances for both scenarios and for the four demand workload levels are shown in Fig. The average numbers of MediaWiki instances for both scenarios and for the four workload levels are shown in Fig.8a and b. The average response times of OrangeHRM for both scenarios and four demand workload levels are shown in Fig. The average response times of MediaWiki for both scenarios and for the four workload levels are shown in Fig.

Consistent Performance

It is not quite practical to use where persistent resource infrastructure is required to handle the heavy workload. Through vertical scaling , you can increase or decrease the capacity of existing services/instances by upgrading the memory , storage, or processing power . Usually, this means that the expansion has an upper limit based on the capacity of the server or machine being expanded. Horizontal scaling results in more computers networked together and that will cause increased management complexity.

scalability and elasticity in cloud computing

This is important in order to support effective measurement and testing the scalability of cloud-based software systems. In terms of comparisons, we note that compared the performance and scalability of two applications (RUBBoS and/or Cloudstone) on three public clouds , and three private clouds that have been built using the three mainstream hypervisors . 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. Only three benchmarks were considered for scalability measurements, the comparison was based on the scaling scenarios, and what the effect on performance and scalability.

Evolve IP partners with IT professionals to bring together their essential productivity and communication tools into a single, secure cloud-based solution, fine-tuned for the hybrid workforce and delivered as a service. By integrating these disconnected systems from vendors like Microsoft, Cisco, and VMware, and filling in the gaps, we are improving the experience for both employees and customers, while centralizing technology management. So no matter how locations, tools, and partners shift over time, you have a solution that makes the future of work better for everyone. For application scaling, adding more instances of the application with load-balancing ends up scaling out the other two portals as well as the patient portal, even though the business doesn’t need that.

Elasticity Vs Scalability In Cloud Computing: The Final Word

We re-ran a number of tests to make sure that the variations in results are not caused by configuration differences. In order to measure the values of I and tr the system must perform the delivery of the service over a period of time, such that short-term variations corresponding to system elasticity do not influence the measurements. The same demand pattern should be executed multiple times to get reliable averages. Some interesting scalability behavior has been noted through the analysis, such as big variations in average response time for similar experimental settings hosted in different clouds. A case of over provision state has been accrued when using higher capacity hardware configurations in the EC2 cloud. Here we use the quality scalability metric defined by considering the system average response time.

Scalability is the ability of a system to remain responsive as the number of users and traffic gradually increases over time. Most B2B and B2C applications that gain usage will require this to ensure reliability, high performance and uptime. Scalability handles the scaling of resources according to the system’s workload 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.

In this paper, we demonstrate the use of two technical scalability metrics for cloud-based software services for the comparison of software services running on the same and also on different cloud platforms. The underlying principles of the metrics are conceptually very simple and they address both the volume and quality scaling performance and are defined using the differences between the real and ideal scaling carves. We used two demand scenarios, two cloud-based open source software services and two public cloud platforms . Our experimental results and analysis show that the metrics allow clear assessments of the impact of demand scenarios on the systems, and quantify explicitly the technical scalability performance of the cloud-based software services.

scalability and elasticity in cloud computing

Thanks to elasticity, Netflix can spin up multiple clusters dynamically to address different kinds of workloads. Сloud elasticity is a system’s ability to manage available resources according to the current workload requirements dynamically. EFS or Elastic File System is a shared storage volume that can be mounted https://globalcloudteam.com/ via NFS to an operating system, enabling multiple instances to see the same disk volume. With EFS Storage you only pay for what you consume, but an EFS volume is virtually infinitely scalable. Performance – sometimes it’s better to leave the application as is and upgrade the hardware to meet demand .

S3 has almost unlimited scalability, and you only pay for the content stored in it. The size of a single object can be up to 5TB, and there is no limit to the number of objects that can be stored in the bucket. A maintenance window with downtime is required – unless you have a backup server that can handle operations and requests, you will need some considerable downtime to upgrade your machine. Less complicated maintenance – the maintenance is easier and less complex because of the number of instances you will need to manage. No changes have to be made to the application code and no additional servers need to be added; you just make the server you have more powerful or downsize again.

Potentially, different components, technologies or technical solutions may fit different degree with the cloud platform’s provisions. The technical scalability metrics that we used here combined with instrumentation could allow the identification of best matches that can improve the system scalability. In the term of average response time, we note that there are big differences in the average of response times for the second scenario as it gradually from 2.035 s for demand size 100 to 9.24 s for demand size 800. While it graduates from 1.02 s for demand size 100 to 3.06 s for demand size 800, for the second scenario- Step-wise increase and decrease. In this study, we perform three kinds of comparisons, one between the same cloud-based software hosted on two different cloud platforms . The second comparison is between two different cloud-based software services hosted on the same cloud platform .

The quality scalability metrics show at the MediaWiki has higher performance than the OrangeHRM in this respect in the first scenario and the performances are relatively close in this sense in the case of the second scenario. One possible factor behind the different volume scalability performance is that we ran the MediaWiki on t2.medium virtual machines, while the OrangeHRM was run on t2.micro virtual machines. Interestingly this difference in the virtual machines made no major difference to the quality scaling of the two software systems. In principle, the difference in the volume scalability performance may point to the possibility that technical solutions in the MediaWiki system support more the volume scaling of the system than the corresponding solutions in the OrangeHRM. A deeper insight and investigation into the components of these systems responsible for the performance difference could deliver potentially significant improvements to the system with the weaker scalability performance metrics. We note two cases of over-provisioning of MediaWiki software instances for both 200 and 400 demand size, when we used new set of auto-scaling policies – see Fig.

What Is Reliability In Cloud Computing?

We calculated the scalability metrics ηI and ηt for the two demand scenarios for the cloud-based application for both cloud platforms. The calculated metrics for EC2 show that in terms of volume scalability the two scenarios are similar, the scaling being slightly better in the context of the step-wise increase and decrease of demand scenario. In contrast, Azure shows better volume scaling in the first scenario with around 0.65, while in the second scenario the volume scaling performance for the Azure is slightly less than the corresponding performance for the EC2. The scalability metrics address both volume and quality scaling of cloud-based software services and provide a practical measure of these features of such systems.

Horizontal scaling,also known as scaling out, is the process of adding more hardware to a system. Doing the opposite, that is removing hardware, is referred to as scaling in. Adopting iterative ways of working and codification across traditional infrastructure, networking, and security teams. For instance, outdated technology environments are expensive to upgrade while some rigid infrastructures aren’t built to enable robust analytics. In the computer world, “flexible” may refer to hardware, software, or a combination of the two. It describes a device or program that can be used for multiple purposes, rather than a single function.

scalability and elasticity in cloud computing

Reliability and availability – horizontal scaling can provide you with a more reliable system. It increases redundancy and ensures that you are not dependent on one machine. Finally, you might want to look into some of the newer database systems that were architected with scalability and elasticity in mind. A scalable system can be changed to adapt to changing workloads without impacting its accessibility, thereby assuring continuing availability even as modifications are made.

Horizontal Scaling In Aws

On the other hand, depending on your requirements, vertical scaling can be less costly if you’ve already invested in the hardware; it typically costs less to reconfigure existing hardware than to procure and configure new hardware. Of course, vertical scaling can lead to over-provisioning which can be quite costly. Replacing difference between scalability and elasticity or adding resources to a system typically results in performance improvement, but realizing such gains often requires reconfiguration and downtime. Furthermore, there are usually limitations to the amount of additional resources that can be applied to a single system, as well as to the software that uses the system.

Weigh Up How Application Architectures Affect Scalability And Elasticity

In other words, a scalable system can be adjusted without requiring any downtime. Scalability is the property of a system to handle a growing amount of work by adding resources to the system. In computing, scalability is a characteristic of computers, networks, algorithms, networking protocols, programs and applications. Hybrid cloud is a cloud computing environment that uses a mix of on-premises, private cloud and third-party, public cloud services with orchestration between the two platforms. The Elasticity refers to the ability of a cloud to automatically expand or compressed the infrastructural resources on a sudden-up and down in the requirement so that the workload can be managed efficiently. The services have become very flexible and can be altered according to the business needs of a company.

The results show that the metrics can be used effectively to compare the scalability of software on cloud environments and consequently to support deployment decisions with technical arguments. 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. The purpose of this kind of comparison is to see the effects on the scalability performance using the same cloud platform while using different types of instances and workload generators.

It can also result in latency between nodes and complicate programming efforts if not properly managed by either the database system or the application. That said, depending on your database system’s hardware requirements, you can often buy several commodity boxes for the price of a single, expensive, and often custom-built server that vertical scaling requires. 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. Select a technology, sourcing, and migration model that aligns with economic and risk constraints – when making decisions about cloud architecture, companies need to tread lightly.

What Are The Five Essential Characteristics Of Cloud Computing?

From a database perspective, elasticity infers a flexible data model and clustering capabilities. The greater the number of changes that can be tolerated, and the ease with which clustering can be managed, the more elastic the DBMS. Train team members to act as software engineers who can bounce between multiple technology stacks to deliver integrative cloud solutions. In order to reap the benefits of cloud computing, your business must always have an internet connection.

A system, business or software that is described as scalable has an advantage because it is more adaptable to the changing needs or demands of its users or clients. 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.

Unfortunately, choosing the wrong technology and making incorrect sourcing decisions shine the spotlight on compliance concerns, execution success, cybersecurity, and vendor risk. Virtualization is the creation of virtual servers, infrastructures, devices and computing resources. Virtualization changes the hardware-software relations and is one of the foundational elements of cloud computing technology that helps utilize the capabilities of cloud computing to the full. Cloud scalability is all about adding or reducing IT resources to meet changes in demand.

The launch template defines the minimum and the maximum number of EC2 instances in the group, as well as the indicators that trigger the launch of new instances. These triggers can be based on instance health checks, CPU load, incoming or outgoing network traffic, or the number of load balancer requests per target. Horizontal scaling increases high availability because as long as you are spreading your infrastructure across multiple areas, if one machine fails, you can just use one of the other ones. Cloud scalability refers to the ability to increase or decrease IT resources as needed to meet changing needs. Scalability is one of the main advantages of the cloud and the main driving force for its popularity in businesses.

Diagonal scaling – combining vertical scaling with horizontal scaling allows for growth within the existing server until it reaches capacity. Then, that server can be cloned, which allows the business to deal with a lot of requests and traffic at the same time. Horizontal scaling – this occurs when ‘building out’ a system with additional components, like adding more memory to a server by linking it with other servers. With horizontal scaling, additional hardware resources, which can decrease redundancy, can be added to the linked servers with minimal impact. Cloud elasticity – this term refers to how efficiently your cloud services are able to add or remove resources on-demand. Companies need to consider how elastic their cloud services are because they need to ensure that your clients and employees can automatically and seamlessly access the resources they need.

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. In the cloud, you will usually use both of these methods, but horizontal scaling is usually considered a long-term solution, while vertical scaling is usually considered a short-term solution. The reason for this distinction is that you can usually add as many servers to the infrastructure as you need, but sometimes hardware upgrades are just not possible anymore. Cloud security, also known as cloud computing security, consists of a set of policies, controls, procedures and technologies that work together to protect cloud-based systems, data and infrastructure. From authenticating access to filtering traffic, cloud security can be configured to the exact needs of the business. The purpose of Elasticity is to match the resources allocated with actual amount of resources needed at any given point in time.

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