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In the initial days of internet revolution, every industry was struggling very hard to meet the growing business demands.
With a very limited and complex infrastructure, organizations found it very difficult to finish the mission-critical tasks, while every single task consumed lot of time and efforts.
Capital expenditure and maintenance costs added to the severity of the challenge and needless to say about the unexpected failures that often lead to entire process shutdown.
Fast forward to today! As the internet usage increased and technology adoption widened, Cloud computing emerged as a game changer offering a one-stop solution to many challenges of the past and paved way for the future.
But the current day cloud scenario is far beyond expectation and the ‘ability to scale’ or ‘scalability’ is deciding the success for most organizations, irrespective of size and industry.
While there are many advantages, Scalability makes the most common advantage that makes Cloud attractive.
The need for scalability in a cloud environment emerges as a result of a sudden rise in business demands for diverse requirements.
Scalability in cloud computing is the ability to scale compute, devices, storage and networks up and down to meet the workload demands required to keep up the business productivity and performance.
This naturally requires high resource utilization and continuous resource availability.
Scaling of applications in a cloud environment typically takes two different strategies:
• Vertical Scaling
Cloud Vertical Scaling involves addition of CPU, I/O resources and memory to the existing server or replacement of the existing one with the most powerful one. Here, apps scale up and down, which might require alteration of resource capacity like moving an application to a large Virtual Machine (VM) size. As part of this process, systems might often be unavailable while undergoing redeployment. Thus, automating vertical scaling is not that usual.
• Horizontal Scaling
Cloud Horizontal Scaling involves provisioning of additional servers, splitting of workloads between servers, and adding more instances instead of moving to a larger instance. Here, apps scale in and out, which means resource instances are eliminated or added as per the requirement. But the application progress is either uninterrupted or unimpacted by the provisioning of new resources. As the provisioning is done, the solution gets added to the new resources. Whereas, in case of a demand drop, the unused or additional resources are shut and de-allocated.
Majority of the today’s cloud-based systems use automatic horizontal scaling process, as it removes additional costs and supports effective resource utilization.
In line with the above strategies, scaling in cloud environment is done in three different ways: Manual, Scheduled and Automatic or Autoscaling.
• Manual Scaling
Here, engineers manually manage scaling in and out or up and down. Though cloud scaling can happen at a push of a button, manual scaling is human-dependent and can pose challenges in handling on-demand fluctuations, which can mean extra costs and time.
• Scheduled Scaling
Little advantageous compared to manual scaling, scheduled scaling helps make the provisioning tailored to your actual usage avoiding the manual work required to act upon changing demands everyday.
• Automatic or Autoscaling
This type of scaling doesn’t demand you to either act manually or schedule in advance. Compute, networks, devices and storage scale automatically to the changing demands in line with the set of predefined instructions. Thus, autoscaling keeps your application up and running all the time, ensuring its all-time availability. It also ensures effective resource utilization at times of performance issues or unexpected outages.
Out of the three, autoscaling definitely proves to be a special advantage considering the current day’s competitive business scenario.
At the next level of scalability, autoscaling method presented a special advantage by enabling dynamic allocation of resources to the changing performance requirements.
Autoscaling typically has two advantages:
Autoscaling takes the elasticity advantage presented by the cloud-hosted applications to release the management overhead.
The autoscaling strategy monitors systems at the infrastructure, application and service levels, which derives metrics like CPU utilization, system response times, memory utilization, among others.
In line with the user demand, the autoscaling strategy provides room for additional session VMs within the existing infrastructure.
Some of the autoscaling best practices include:
While the above scaling methods and autoscaling best practices make scaling easier and effective, infrastructure scaling is very crucial to meet the full scaling advantage.
Infrastructure Scaling in Cloud merely requires focus on storage assessment, load assessment, metrics analysis, re-designing of in-house infrastructure matching different business needs, followed by load tests to match the production requirements.
Scaling in a cloud environment is definitely an effective means to cloud cost management by way of effective resource utilization and to enhanced cloud productivity by way of resource availability and provisioning. Moreover, autoscaling presents a better business advantage by allowing you to just ‘pay for what you use’, which is the core idea of cloud technology behind saving cost and time.
But it all purely depends on how you leverage the Cloud Scaling strategy and its best practices to meet the desired Return on Investment (RoI)!
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