Scalability and Elasticity differences



Scalability: “Increasing” the capacity to meet the “increasing” workload.

Elasticity: “Increasing or reducing” the capacity to meet the “increasing or reducing” workload.

Scalability: In a scaling environment, the available resources may exceed to meet the “future demands”.

Elasticity: In the elastic environment, the available resources match the “current demands” as closely as possible.

Scalability: Scalability adapts only to the “workload increase” by “provisioning” the resources in an “incremental” manner.

Elasticity: Elasticity adapts to both the “workload increase” as well as “workload decrease” by “provisioning and deprovisioning” resources in an “autonomic” manner.

Scalability: Increasing workload is served with increasing the power of a single computer resource or with increasing the power by a group of computer resources.

Elasticity: Varying workload is served with dynamic variations in the use of computer resources.

Scalability: Scalability enables a corporate to meet expected demands for services with “long-term, strategic needs”.

Elasticity: Elasticity enables a corporate to meet unexpected changes in the demand for services with “short-term, tactical needs”.

Scalability is the ability of the system to accommodate larger loads just by adding resources either making hardware stronger (scale up) or adding additional nodes (scale out).

Elasticity is the ability to fit the resources needed to cope with loads dynamically usually in relation to scale out. So that when the load increases you scale by adding more resources and when demand wanes you shrink back and remove unneeded resources. Elasticity is mostly important in Cloud environments where you pay-per-use and don’t want to pay for resources you do not currently need on the one hand, and want to meet rising demand when needed on the other hand.

Think of Scalability as the ability to increase/decrease the workload sizes within an existing infrastructure.

Think of Elasticity as it relates to cloud as the ability to grow or shrink infrastructural resources dynamically as needed to adapt to the current workload changes.

Scalability often is discussed at the application layer, highlighting capability of a system, network or process to handle a growing amount of work, or its potential to be enlarged in order to accommodate that growth.

While scalability can rely on elasticity, it can also be achieved with over provisioning.

Elasticity in cloud infrastructure involves enabling the hypervisor to create virtual machines or containers with the resources to meet the real-time demand.

Scalability includes the ability to increase workload size within existing infrastructure (hardware, software, etc.) without impacting performance. These resources required to support this are usually pre-planned capacity with a certain amount of headroom built in to handle peak 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.

Scalability: You can increase or decrease the resources and services used based on the demand or workload at any given time. Cloud computing supports both vertical and horizontal scaling depending on your needs.

Vertical scaling, also known as “scaling up”, is the process of adding resources to increase the power of an existing server. Some examples of vertical scaling are: adding more CPUs, or adding more memory. Horizontal scaling, also known as “scaling out”, is the process of adding more servers that function together as one unit. For example, you have more than one server processing incoming requests.

Scaling can be done manually or automatically based on specific triggers such as CPU utilization or the number of requests and resources that can be allocated or de-allocated in minutes.

Elasticity:  As your workload changes due to a spike or drop in demand, a cloud computing system can compensate by automatically adding or removing resources.

For example, imagine your website is featured in a news article, leading to a spike in traffic overnight. Since the cloud is elastic, it automatically allocates more computing resources to handle the increased traffic. When the traffic begins to normalize, the cloud automatically de-allocates the additional resources to minimize cost.

Another example is if you are running an application used by employees, you can have the cloud automatically add resources for the peak operating hours during which most people access the application, and remove the resources at the usual end of the day.

Scale refers to adding network bandwidth, memory, storage, or compute power to achieve better performance.

Scaling up, or vertical scaling means to increase the memory, storage, or compute power on an existing virtual machine. For example, you can add additional memory to a web or database server to make it run faster.

Scaling out, or horizontal scaling means to add extra virtual machines to power your application. For example, you might create many virtual machines configured in exactly the same way and use a load balancer to distribute work across them.

In cloud terms, the only difference between scalability and elasticity is, when you are on-premises you can scale up and out, but you cant scale in. Meaning, you cant just remove the hardware you bought earlier. With cloud, you can add or remove hardware from your VM as per work load. Dynamic scalability is elasticity. Elasticity is going up or coming down.

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