In my last article, I discussed the evolution of Cloud Computing technology and how Cloud has been a paradigm shift for the Digital Transformation. Cloud provides businesses with unheralded flexibility while offering them greater versatility and inexpensive solutions for managing their IT systems, where technological developments are happening at a phenomenal pace and more dynamic than ever before.
Cloud Computing has already permeated every facet of online activity. The burgeoning of the Internet of Things (IoT) and Connected devices are transforming the future of cloud technology. It is estimated that by 2025 the ‘Datasphere’ would grow to an incredible 163ZB, that is over a trillion gigabytes. With such an enormous amount of data being generated, the data needs to be stored somewhere which can be accessed by people. Of late, Cloud Computing has become the ideal place for data storage, both for business and personal use.
However, the future of Cloud Computing will see breathtaking innovations in the coming years which will surpass all the innovations seen so far in the following areas:
1. Everything as a Service (EaaS):
Cloud Computing sees continued growth for all its cloud-based services and solutions. Most of these services are already well established with Infrastructure, Platform, and Software as a Service (IaaS, PaaS, and SaaS) all predicted to account for a more significant portion of IT expenditure. The future of cloud service landscape will be very much dominated by the behemoths such as Amazon with its AWS, Google’s service – Google Apps and Google Compute Engine (GCE) and Microsoft Azure.
2. NoOps (No Operations):
NoOps is the concept that an IT environment can become so automated and abstracted from the underlying infrastructure that there is no need for a dedicated team to manage the software-in-house. According to Google’s Chairman, Eric Schmidt, “The current day’s programming model is based on twenty-year-old processes that force developers to think about the infrastructure. The new model will allow the developers to focus on business requirements, while the cloud provider handles the infrastructure and scalability.” The more underlying technologies are abstracted, and less operational tasks are required and hence the term NoOps. The organisations will still need operations, but the focus should shift towards operating the applications and ensuring the cloud platform is meeting its SLAs, and that is a very different model than running the datacentres and middleware.
3. Serverless Architecture:
Cloud Computing welcomes us to a Serverless Era. Serverless computing is a Cloud Computing model in which the platform will dynamically determine and manage the allocation of required infrastructure and automatically provisions and deprovisions the infrastructure to support the application. For example, think how much time is saved when the efforts of developing and managing an infrastructure are removed from the software development lifecycle (SDLC). In today’s environment, most of the time and resources are invested in building systems that can scale and failover. Google’s serverless architecture approaches abstracts that work and gives the developer the quickest path from ideation to production, running on top of the same technology and processes Google uses to run applications like Gmail, YouTube, and others.
With Serverless Computing, the cloud instances are no longer allocated to sit idle til called upon to fuel the applications and other functions. Instead, the resources are provisioned only when a specific event occurs.
Hence, Serverless Architecture also known as “Function as a Service” (FaaS), signifies the next big thing in the journey or the roadmap of Cloud Computing. Gartner predicts that 90% of “Serverless” deployments will occur outside the IT department’s Infrastructure and operations groups. Serverless Computing makes products reliable, scalable and economically viable. Amazon launched AWS Lambda as its first commercial serverless platform in 2014. AWS Lambda allows one to run code without provisioning or managing servers. AWS Lambda remains the most popular choice of serverless computing platform offering, compared to its competitors IBM OpenWhisk or Microsoft Azure functions.
4. Scalable Storage:
The cloud-based storage is likely to increase and become inexpensive. The normalisation of cloud storage and companies advancing towards having their Infrastructure in the cloud, there will be significant growth in the total amount of data to be stored, simultaneously with an increase in the number of service providers. According to Cisco, “The Global storage capacity will increase from 600EB to 1.1ZB in 2018, which is almost twice the available storage of 2017.” The SMBs will be able to create bespoke storage solutions to benefit from cost efficiencies of hosting it on Cloud, while the big organisations will store Big Data in the cloud for data analytics and insights which will help improve their business performances. As these innovations mature, the public cloud delivery mechanism will continue to gain momentum and make the legacy system redundant and uncompetitive.
4. Machine Learning:
According to Eric Schmidt “Google believes machine learning is the next layer of programming. Google’s goal is to make the process of data ingestion, storage, and training machine models as simple as calling an API. This APIs will allow developers to focus on creating incredible new applications without having to understand complex concepts like neural networking. Google has demonstrated its speech, sound, and image recognition services. The Google ‘Cloud Vision API’ can analyse an image and categorise its contents into thousands of categories. For example, the API can take a picture of a person and detect gender, race, and mood. It can look at the background and determine the location of the person and other relevant information about the location. It can read text within the image itself and return it to the user as metadata.”
To Summarize, the future of cloud computing will both compliment and leverage technologies like Artificial Intelligence (AI) and Machine Learning for problem-solving and predict outcomes for things or events that the world has not even thought about it yet.
The next-gen Cloud Computing will focus on abstracting ‘Virtual Infrastructure’ and the operational processes that come along with managing that infrastructure. Complex technologies like AI and Machine Learning will be made simple for data scientists to focus on the data and the developers will be able to enable the data scientists without having to be an expert of the underlying AI and machine learning technologies.
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