Cloud scalability in cloud computing refers to the ability to increase or decrease IT resources as needed to meet changing demand. Scalability is one of the hallmarks of the cloud and the primary driver of its exploding popularity with businesses.
Data storage capacity, processing power and networking can all be scaled using existing cloud computing infrastructure. Better yet, scaling can be done quickly and easily, typically with little to no disruption or down time. Third-party cloud providers have all the infrastructure already in place; in the past, when scaling with on-premises physical infrastructure, the process could take weeks or months and require tremendous expense.
Cloud providers can offer both elastic and scalable solutions. While these two terms sound identical, cloud scalability and elasticity are not the same.
Elasticity refers to a system’s ability to grow or shrink dynamically in response to changing workload demands, like a sudden spike in web traffic. An elastic system automatically adapts to match resources with demand as closely as possible, in real time. A business that experiences variable and unpredictable workloads might seek an elastic solution in the public cloud.
A system’s scalability, as described above, refers to its ability to increase workload with existing hardware resources. A scalable solution enables stable, longer-term growth in a pre-planned manner, while an elastic solution addresses more immediate, variable shifts in demand. Elasticity and scalability in cloud computing are both important features for a system, but the priority of one over the other depends in part on whether your business has predictable or highly variable workloads.
A scalable cloud architecture is made possible through virtualization. Unlike physical machines whose resources and performance are relatively set, virtual machines virtual machines (VMs) are highly flexible and can be easily scaled up or down. They can be moved to a different server or hosted on multiple servers at once; workloads and applications can be shifted to larger VMs as needed.
Third-party cloud providers also have all the vast hardware and software resources already in place to allow for rapid scaling that an individual business could not achieve cost-effectively on its own.
The major cloud scalability benefits are driving cloud adoption for businesses large and small:
- Convenience: Often with just a few clicks, IT administrators can easily add more VMs that are available without delay—and customized to the exact needs of an organization. That saves precious time for IT staff. Instead of spending hours and days setting up physical hardware, teams can focus on other tasks.
- Flexibility and speed: As business needs change and grow—including unexpected spikes in demand—cloud scalability allows IT to respond quickly. Today, even smaller businesses have access to high-powered resources that used to be cost prohibitive. No longer are companies tied down by obsolete equipment—they can update systems and increase power and storage with ease.
- Cost savings: Thanks to cloud scalability, businesses can avoid the upfront costs of purchasing expensive equipment that could become outdated in a few years. Through cloud providers, they pay for only what they use and minimize waste.
- Disaster recovery: With scalable cloud computing, you can reduce disaster recovery costs by eliminating the need for building and maintaining secondary data centers.
Successful businesses employ scalable business models that allow them to grow quickly and meet changing demands. It’s no different with their IT. Cloud scalability advantages help businesses stay nimble and competitive.
Scalability is one of the driving reasons to migrate to the cloud. Whether traffic or workload demands increase suddenly or grow gradually over time, a scalable cloud solution enables organizations to respond appropriately and cost-effectively to increase storage and performance.
There are two basic types of scalability in cloud computing: vertical and horizontal scaling.
With vertical scaling, also known as “scaling up” or “scaling down,” you add or subtract power to an existing cloud server upgrading memory (RAM), storage or processing power (CPU). Usually 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.
To scale horizontally (scaling in or out), 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.
Changing business requirements or surging demand often require changes to your scalable cloud solution. But how much storage, memory and processing power do you really need? Will you scale up or out?
To determine a right-sized solution, ongoing performance testing is essential. IT administrators must continually measure factors such as response time, number of requests, CPU load and memory usage. Scalability testing also measures an application’s performance and ability to scale up or down depending on user requests.
Automation can also help optimize cloud scalability. You can determine thresholds for usage that trigger automatic scaling so that there’s no effect on performance. You may also consider a third-party configuration management service or tool to help manage your scaling needs, goals and implementation.