By Dr. Christopher Richard, MD & Chief Cloud Architect, G7 CR Technologies
When it comes to handling a business’s computing needs, companies need to decide on how much processing power they need. Generally, there are three options — the old practice of having an on-premises network of servers, edge computing that combines prepping up of some base load computing on-site and then uploading it on-demand to the cloud, or computing intensive tasks from start to finish on the cloud itself.
While edge computing can solve the challenges pertaining to connecting a device to a network from a remote location, slow data processing and network bandwidth issues, cloud computing helps companies store, process, and work with data on remote servers hosted over the internet. For example, Microsoft Azure, a commercial cloud computing provider, helps companies reduce costs associated with physical IT infrastructure through its digital platforms and collections of services. Consequently, organisations can provide a secure remote work environment to their employees and take advantage of IoT.
Though Artificial Intelligence (AI) and cloud computing have their own challenges and growth paths, the use of AI has gained parlance as it is touted to be the next evolution in cloud computing. AI helps in increasing productivity by assisting in automation of the IT infrastructure and handling of routine exercises. When AI and cloud computing are brought together, it results in an extensive network that can handle a huge amount of data. As a result, machine learning and improvement takes place with each step of data processing.
AI would have been just a niche concept if it hadn’t been boosted by cloud computing. The data on the cloud helps AI learn and remodel itself in any given scenario it is being used in. Now, AI and cloud computing have become mutually inclusive as organisations can use the power of AI-driven cloud computing to become more efficient, formulate fresh strategies, and develop insight-driven models for the betterment of their businesses. AI can help IT teams monitor and manage core workflows. Complex and repetitive tasks can be automated with the help of AI, which can help boost productivity and even perform data analysis without any human intervention.
Over the past decade, cloud platforms were all about storage of data, for example the photographs, contacts, files, etc. from one’s smartphone. But now clouds have evolved into computing as emerging businesses with smaller budgets need flexibility when it comes to their computing needs. Given the proliferation of big data, the ability to crunch it with ease is the cloud’s next biggest trend. Considering the number of startups and the Indian government’s push for self-reliance and becoming job providers, there is a need for cheaper, on-demand options that don’t require employees to implement and run IT solutions.
Cloud computing in India is currently in a “democratic” state as it is available to not just the high and mighty enterprises, but also to startups and smaller entrepreneurs who want to reduce IT costs. Lower costs result in better delivery for both mature and fledgling companies. Tech innovation is also helping fresh firms in the corporate world engage in a fair contest to woo clients. Also, cloud computing enables companies to subscribe to the pay-as-you-go model from providers of Software as a Service (SaaS), Platform as a Service (PaaS) or Infrastructure as a Service (IaaS). Effectively, companies only pay for what they have used in a specific month.
SaaS solutions are generating the most interest among the different models of cloud computing in India, especially because micro, small and medium enterprises contribute most to the SaaS economy.
Cloud computing gives the most significant advantage of reduced responsibility for infrastructure security and maintenance. Users don’t have to worry about tiring upgrades and the physical safety of devices. The service provider supplies infrastructure maintenance as part of the package. Plans can be upgraded or downgraded according to a company’s requirement.
The future of cloud management is through AIOps, which pertains to the use of AI, machine reasoning (MR), and machine learning (ML) technologies that help simplify IT operations, streamline processes, and optimise the use of resources. Considering the fact that AIOps is going to play an essential role in the future, many service providers have now changed tacks by offering AIOps solutions to their clients or consumers to combine big data and AI, ML, and MR capabilities, which can aid in improving and automating event monitoring, service management, improving reliability, uptime, and customer experience, enhancing security, among other processes.
Research by Gartner suggests that by 2025, AI would be catering to 80% of new cloud workloads. It has also predicted that 50% of cloud data centres will deploy advanced robots with AI and ML capabilities, resulting in 30% higher operational efficiency. On the other hand, Forrester had predicted that the global cloud computing market could grow at a 19.3% CAGR between 2020 and 2025.
Numerous opportunities have been unlocked with the usage of AI. With AI and cloud, data processing has been enhanced, AI solutions have become more accessible, security and privacy have improved, automation and optimisation have become intelligent and user experiences have been personalised.
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