2020 is just around the corner, and aren’t we all super excited for it? Cloud computing has seen a steady increase in adoption and is enjoying a tremendously growing popularity across the board. This is quite evident from the growing adoption of Amazon’s AWS and Microsoft Azure, which are the top two players in the cloud market. Cloud is definitely not going to lose its sheen anytime soon. 2020 is expected to be an amazing year for the cloud, and there are predictions of bringing in new efficiencies, new interfaces, greater connectivity choices and enhanced application interactions into the cloud. Here are some predictions for what could happen to cloud computing in 2020:
By 2025, 80% of the enterprises will shut down their traditional data centres and would be shifting to the public cloud.
On this path, many organizations have already begun going from data centres to the cloud. Initially organizations took a small step by taking up the cloud as a secondary data centre, and now they are going full-fledged on it. There are even many organizations who are taking up a second availability zone or choosing a second cloud provider to meet their enterprise needs.
Hybrid cloud will be redefined by software
2020 is expected to see the rise of the hybrid cloud. While hardware would still be essential, hybrid cloud would provide flexibility in terms that it could be located anywhere. It is the software then that would coordinate the increasing complexity, which is what would actually be the basis for making the hardware location irrelevant.
SaaS will help organizations wanting to bring microservices APIs directly to their customers
The closest solution that makes this happen, is AWS, whose every component has been built as a microservice directly addressable by customers. AWS lets one write custom authorizers that take in OAuth bearer tokens and convert them into access decisions based on IAM policies. If not anything else, it does need a lot of customization and configuration to be done by the AWS customers. This has also created a need for standards-based, resource-aware API authentication and authorization product, which could come through as a proper named product and not just as an orchestration inside a tutorial. SaaS would indeed provide the authorization and API delivery options for countless businesses who are keen to bring microservices APIs directly to their customers. This need could be realized and fulfilled in 2020, most likely.
Deployment of all new analytic workloads could become cloud-first
2020 could see public cloud becomes the default option for IT departments in most businesses to support any new business initiative, and not just be something looked into for capacity expansion of the existing infrastructure. Enterprises will increasingly make bulk purchase agreements with public cloud vendors in 2020.
aaS offerings would move up the stack
aaS offerings or as-a-Service offerings would increasingly incorporate a many new capabilities that were earlier considered as custom requirements, which would in turn increase the levels of commoditization and duplication. In fact, containerization and solution portability would become important factors for enterprise IT. Cloud vendors would need to focus on deployment-specific point solutions, providing customers the freedom and leverage.
Public cloud would increasingly include full stack data analytics offerings
There are so many public clouds available in the market than there were say 5-7 years ago. There is AWS, Azure, GCP, Alibaba, and so many more. In 2020, these public clouds would aggressively seek to partner with enterprise data analytics vendors who would add great value to the cloud offerings for the customers. As a consequence, in-house data analytic offerings would begin to lose relevance as enterprises would prefer to avoid cloud lock-in.
There would likely be a SaaS apps buying spree for cloud providers
While there are some cloud providers who have the controlling share of the cloud market, newer avenues courtesy emerging technologies, such as, artificial intelligence and machine learning is helping open up the market for newer players and niche players. Gartner has predicted that in 2020, there would be increased IT spending with as-a-Service models which would trigger a lot of things, such as, data centre spending to spending on enterprise software. The key themes for growth for cloud usage would be blending the licenses, subscriptions and usage models. Cloud vendors are also expected to put full thrust on upselling with computing, cloud storage, serverless functions and even artificial intelligence differentiators.
Increased focus on cloud security
It is no secret that as technologies grow and enhance, they become increasingly vulnerable to cyberattacks. In 2020, cloud, coupled with increased deployment of robotics process automation would create an even greater need for securing the system accounts used for automation. The need for Application Programming Interface (API) security would be unlike ever seen before in 2020.
Cloud infrastructure development would heavily rely on DevOps
In roughly the past five years, cloud strategy has gone from waterfall to agile to DevOps. In 2020, developers are expected to take a more centric role in most organizations. With this, there would be a need to deploy infrastructure parts of various applications, the application code and also address aspects of data integration. DevOps will help bring real-time capabilities to packaging and deployment of infrastructure and related services. It would help enterprises in more ways than we can still imagine.
Focus on edge computing integration into core cloud services
In 2020, edge computing would see increased adoption and integration. There will be more of computing and analytics, as well increased abilities to do workflows on the edge. These capabilities had until now been reserved for the data centre or bigger cloud hubs. This would especially be taking place on manufacturing lines. Edge devices are expected to take pictures of the operations on a manufacturing line, which would then be compared to another set of images, the ideal set. If this exercise reveals deviations, the issues would then get addressed in real-time on the production lines. Traditionally, corrective measures are taken much later, while edge computing would help address this in real-time, preventing major losses of time, productivity and resources. These analytics would be done at the edge and not on data centres, since the latency requirements need to be real-time, things need to take place as a product moves further along the production line. Thanks to edge computing, coupled with cloud capabilities, there will be an increase in product quality, while also resulting in a subsequent increase in revenue, reduction in costs and improved customer satisfaction.
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