MSME’s transitioned from Cloud scalability to elasticity 

Biswas Nair, Founder & CEO, Inspirria Cloudtech 

The key trends 
There are lot of predictions from analyst to technology vendors on the key trends in technology especially computing power, quantum computing, smarter devices, AI, Machine learning and datafication to name a few. We still have a long way to go with leveraging the digitalization strategy especially with Cloud technology being the key propeller to achieve business strategy success. 

Cloud to scale the customers’ business 
Scalability is the inherent capacity of a system to cater to growing demand by adding more or bigger computing resources. This term “scalability”  was coined to describe the ideal state of the architecture that is growth-friendly for successful startups or MSME in India. A scalable cloud architecture is made possible through virtualization. Unlike physical machines whose resources and performances are relatively set, 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; workload 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 latest technology adoption trends in MSMEs 
Post pandemic the MSME’s have transitioned from Cloud scalability to elasticity. Elasticity refers to the ability of a system to drastically change computing capacity to match an ever fluctuating workload. Systems are configured so that clients are only charged for consumed instances, regardless of sudden bursts in demand. In an elastic system, you pay for what you consume. This is pretty relevant in a start-up environment wherein a new launched mobile/web application needs to react to their system usage with increased user surge or in the traditional set up retail business who have to be elastic with seasonal buying behavior patterns.