What is cloud elasticity?

Why is cloud elasticity important?

Organizations often experience unexpected increases in the use of their cloud-based applications. At peak periods, they need their cloud systems to run continuously without interruption. Those with insufficient cloud elasticity risk losing customers and can suffer reputational damage.

At times like these, elastic cloud services are essential to support both the high levels of online traffic and transactions, as well as the drop in demand when the event ends. In the absence of cloud elasticity, organizations might suffer service outages and computer failures, which increase the threat of viruses and other vulnerabilities. Companies might also have to resort to fixes, such as operating system upgrades and patches, which can be costly.

Cloud elasticity vs. cloud scalability

Cloud elasticity and cloud scalability are common cloud computing concepts that have some similarities, but there are fundamental differences in how they operate in a cloud environment.

Cloud elasticity involves the ability to automatically or manually add or shrink cloud resources quickly to meet sudden changes in demand and prevent disruptions in service. The flexibility and agility of elastic cloud services give organizations the ability to adapt to short-term variations in workloads. Companies with cloud operations that experience unpredictable shifts in demand often turn to the elastic cloud services available in a public cloud.

In contrast, cloud scalability involves increasing and decreasing resources to meet workload demands over time and supports a deliberate approach to long-term planning. A company that is building a music streaming service, for example, would find cloud scalability important for accommodating fast growth in subscribers without having to worry about constraints.

How does cloud elasticity work?

With elasticity, organizations can quickly and nimbly scale up or down -- either automatically or manually -- the resources needed to support cloud-based applications. During this process, the cloud provider resizes its cloud by provisioning or deprovisioning resources such as RAM, storage capacity and CPU processing capability to match changes in an organization's overall demand profile.

Horizontal scaling, which involves increasing the number of machines in an organization's IT infrastructure to accommodate new demand, is often used to achieve cloud elasticity. So, too, is the public cloud, which provides pay-as-you-go billing. Both options are critical to business expansion and cost containment.

As more customers visit a website -- or new employees require access to the organization's internal cloud applications -- and the demand for resources grows, autoscaling of resources starts to occur. There are three main types:

1. Dynamic scaling, the most common configuration, uses various metrics to automatically adjust the amount of compute power in response to triggering events.
2. Predictive scaling refers to the predetermined increase of server capacity based on expected periods of high traffic at a public website, for example, during holiday travel; major sporting events, like the Super Bowl or World Cup final; or Black Friday.
3. Scheduled scaling refers to the deployment of server resources to manage routine high-traffic periods, such as peak business hours.

All three can be scaled down when the demand for resources declines.

Benefits of cloud elasticity

Cloud elasticity enables organizations to equip their IT environment with a fail-safe amount of cloud capacity that ensures online systems stay up and running to whatever capacity customers and employees need during peak periods of cloud application use.

Organizations must be able to manage bursts of activity on their cloud systems without knowing exactly how many additional resources they'll need, but once the surge is over, they can reset their resource use to normal levels and avoid wasteful expenses.

Cloud elasticity is both financially and operationally advantageous to organizations. Using elastic cloud services avoids overprovisioning (using too many resources), which comes with unnecessary expenses, as well as underprovisioning (using too few resources), which can result in users being unable to access the service. An optimally performing cloud elasticity model avoids overprovisioning and underprovisioning, resulting in cost efficiency in cloud environments. In essence, organizations only pay for the resources they use.

Challenges of cloud elasticity

Cloud elasticity presents several challenges. For a start, because elasticity in cloud computing requires managing many different resources in an organization's IT infrastructure, cloud elasticity entails a learning curve and experience to understand how to manage services in an efficient and cost-effective way.

Organizations that run their cloud environment on premises rather than outsourcing their cloud infrastructure have to find technical expertise, such as developers, architects and administrators, to manage the increase and decrease in demand for cloud resources when they implement a cloud elasticity strategy.

In addition, cloud services that are subjected to frequent increases and decreases in demand are more likely to be exposed to cybersecurity threats, which requires them to be carefully reevaluated according to security criteria.

Another challenge is preventing a sudden surge in demand from negatively impacting performance if additional resources can't be allocated in time.

Cloud elasticity examples

Businesses with e-commerce websites that offer sales starting from Black Friday until early January when the holiday season comes to an end experience huge surges in online visits and transactions.

Airlines that experience higher volumes of ticket sales during holidays such as Christmas see a surge in online visits and ticket purchases.

Online ticket distribution companies that sell concert tickets for high-demand events, such as Taylor Swift's The Eras Tour or Beyoncé's Renaissance World Tour, typically experience a rapid rise in demand and a need for elastic cloud services to handle ticket sales, often over an extended period.

Companies also need elasticity when adding cloud capacity for software testing and development projects and removing the resources once the project ends.

Elastic cloud services are also useful for short-term projects, such as batch processing, data analytics and media rendering.

If a disaster occurs at an organization's production site, the organization often implements a business continuity and disaster recovery plan that calls for using the public cloud and elastic computing to support a replica of the production site, which then requires constant replication and saving of data to ensure that is it always accessible in the cloud.

Organizations might also need to expand their data sources when, for example, they create new business units or combine data and IT infrastructure in a corporate merger or acquisition. The process can result in a high volume of information being assigned to data warehouses and data lakes. By using elastic cloud services, organizations can prevent the data management challenges of an expansion from interfering with daily operations.