Vikas Bhonsle, CEO at Crayon Software Experts India
The year 2022 will see a big boom in Multicloud adoption across verticals. Tech research and consulting services firm International Data Corporation (IDC) had already declared 2021 to be the year of Multicloud, with the vast majority of enterprises deploying combinations of on-premises, off-premises, public, and private clouds as their default environments. They also claim that by 2022, over 90% of enterprises worldwide will be relying on a mix of on-premises/dedicated private clouds, multiple public clouds, and legacy platforms to meet their infrastructure needs.
Where most industries failed to comply with the rapidly changing scenarios led by the pandemic, cloud computing supported the global economy by ensuring continuity for remote workforces and allowing supply chains to adapt. Cloud solutions have made it possible to seamlessly ‘work from anywhere.’ Imagine, if there were no cloud storage or cloud-based services, there would have been no meetings over Teams or Zoom, or for that matter, there would be no tools for even mailing, messaging, or conferencing remotely.
Multicloud enables companies to transfer their workload on multiple clouds with respective applications and data criticality. It enables the management of multiple cloud services such as IaaS, PaaS, and SaaS and provides flexibility.
The hike in Multicloud adoption is also influenced by some other technology trends. In 2022, Artificial Intelligence (AI) will be a critical enabler in cloud computing technology adoption. Organisations will therefore look for a strong AI engineering strategy to ensure that their projects will not fail. AI engineering is an emergent discipline focused on developing tools, systems, and processes to enable the application of AI in real-world contexts. It also plays a vital role in keeping data centers up and running.
We also see that public cloud companies are transitioning to location-agnostic distributed cloud services, where they maintain, operate, and develop the services but physically provide them at the point where it is needed. This process eliminates latency issues and satisfies privacy regulations such as the GDPR which requires data storage in specific geographic locations. A few types of distributed cloud include on-premises, Internet of Things (IoT) edge cloud, metro-area community cloud, 5G mobile edge cloud, and global network edge cloud.
By the end of 2022, industrial firms will be largely using edge computing, data analysis and solution development at the data generation site. It will make businesses more efficient by reducing latency, cost, and security risks. In fact, the global roll-out of 5G technology is supercharging this development, leading to a massive demand for cloud-to-edge applications.