Can cloud, Big data, and AI have more turmoil in 2018?

We will see some trends emerging in 2018 with an emphasis on making new technologies easy and cost-effective.
The number of new technologies in 2017 is overwhelming: The cloud has passed faster than analysts expected and offers some new tools with it; AI has been brought into just about all areas of our lives; IoT and edge calculations appear; and a variety of cloud technologies have emerged, such as Kubernetes, no database server and cloud, to name a few. I mentioned a few of these a year ago in my 2017 forecast and it is now time to analyze trends and predict what will happen in the technology sector next year.
Although we love new technology, average business owners, IT buyers and software developers have shed light on this tremendous innovation and do not know how to start turning it into price  business management.We will see several trends emerge in 2018, and their key focus will be on making new technology easy and consumable.

Platform integration and everything becomes no server

Amazon and other cloud service providers are in a race to win and maintain market share, so they continue to raise the level of abstraction and cross-service integration to improve the productivity of the home. Develop and increase the intensity of customer lock. We see Amazon introducing new database-as-a-service services and integrated AI libraries and tools last month. AWS Re: Invent. It also began to make a difference between the different types of serverless: AWS Lambda is now about serverless functionality, while AWS Aurora and Athena are about “database without server”, extends The definition of serverless for any service hides the servers below. Perhaps, many cloud services will be able to call themselves “no server” in the broader sense.
By 2018, we will see cloud service providers focus on further integrating personalized services that come with higher level abstractions concepts. They will also focus on services related to AI, data management and no server. These solutions will make the work of developers and professionals operate their simple and hidden inherent complexity. However, they are at greater risk of lockin.
By 2017, we have seen all of the cloud providers associated with Kubernetes as class combining microservices, reducing the number of locks. By 2018, we will see a growing range of open and commercial services on Kubernetes that can provide multi-tiered replacement services for proprietary cloud services. Nuclio’s Iguazio is a typical example for open and multicloudserverless platforms, as well as Openshiftmulticloud PaaS of Red Hat.

Intelligent Edge vs. Private Clouds

The cloud allows the agility of the enterprise to develop modern applications and data applications, whether it be at startup or large businesses that operate as startups. The challenge is that you can not ignore data gravity, since many data sources are still alive at the boundary or within the enterprise. This is enhanced by 5G bandwidth, latency, new rules like GDPR, and more – forcing you to calculate and store near data sources.

Today’s public cloud model is of service consumption, so that developers and users can bypass IT, bring some serverless functions, use self-service databases, or even upload a video to a cloud service returns it with a translation into the desired language. But you must build the services ourselves when you use the on-prem alternatives, and the technology stack is evolving so rapidly, it is virtually impossible for IT teams build modern services that can be compared to cloud replacement solutions, forcing organizations to cloud.
IT vendors’ solutions labeled “private clouds” are not the same as the real cloud, because they focus on automating IT operations. They do not offer higher level users and developers facing IT-services end up assembling a series of open source or commercial packages individually, adding layers of security. Often, login and configuration management … This has opened up opportunities for cloud providers and new companies to enter the edge and cash space.
Microsoft has introduced Azure Stack, a mini-version of the Azure cloud and unfortunately only contains a small portion of the services that Microsoft provides in the cloud. Amazon started offering edge devices called Snowball Edge, and I hope it will double that effort.
Intelligent edge is not a private cloud. It provides a set of service models and operational models identical to those of the public cloud, but it is accessed locally and in many cases is operated and maintained from a central cloud, just as Operators manage set-top-set boxes.
By 2018, we will see the traditional private cloud market shrink while at the same time the impulse around smarts will increase.Cloud providers will add or enhance edge services and new companies will enter that space, in some cases through integrated services for specific vertical applications or In case of used.

AI from raw technology to embedded features and vertical stack

We have witnessed the rapid rise of computer technology and computer technology by 2017 but despite that hype it is actually used by leading companies in the market such as Amazon, Google and Facebook. AI is not a small business problem, but there is really no reason for most organizations to hire rare data scientists or to build and train AI models from scratch.
We can see how companies like Salesforce built AI in its platform, taking advantage of the huge customer data it hosts. Others are following that path to embed AI into services as a feature. At the same time, we recognize that AI is vertically focused, and we will begin to see AI software solutions for specific industries and verticals such as marketing, retail, healthcare, finance  and security. Users will not need to know the intrinsic neural network or regression algorithm in these solutions. Instead, they will provide data and a set of parameters and get an AI model that can be utilized  in their application.