Introduction to Hybrid Cloud Computing with Artificial Intelligence
Cloud computing is a technology for storing and accessing data and programs over the internet instead of one’s own hard drive. Cloud is just another word for the internet.With the help of cloud computing,users can access software’s and applications from wherever they want,while it is being hosted on third party server or most of them call it as -in “the cloud”. This is really beneficial as one does not have to worry about things such as storage, power, scalability, etc. We just get the final output .
With the help of cloud computing , we eliminate the cost of storage/power as it becomes responsibility of the cloud provider.The user has to only pay for the resources he used,upgrades are automatic and scaling up or down is easy.Cloud based applications can be hosted for days/weeks/months according to the user’s requirement.In recent times,cloud is being accessed by many people.With more and more people shifting towards cloud based service,it has bright future ahead of itself.
Types of Clouds:
Basically there are three types of clouds:
- Public Cloud
- Private Cloud
- Hybrid Cloud
Public Cloud : The public cloud is defined as computing services offered by third-party providers over the public Internet, making them available to anyone who wants to use or purchase them. They may be free or sold on-demand, allowing customers to pay only per usage for the CPU cycles, storage, or bandwidth they consume. ~ From Microsoft
Examples:
Amazon;
IBM;
Google;
Azure;
Elastic Cloud Computing(EC2);
Disadvantages Of Public Cloud :
The security and privacy of data present inside a Public cloud service remains a concern for many businesses. The Public cloud services offered by many providers are secure to some extent.Using the Public cloud services means that you are sharing the same infrastructure with the other customers. The maintenance and the management has been entirely taken care by the service provider. The users have no control over it.The atmosphere of the Public cloud service can limit any customization process. Hence, customization of resources or services is almost made impossible in a Public cloud service.Public cloud models lacks on the side of customer support.
Private Cloud : The private cloud is defined as computing services offered either over the Internet or a private internal network and only to select users instead of the general public. Also called an internal or corporate cloud, private cloud computing gives businesses many of the benefits of a public cloud— including self-service, scalability, and elasticity — with the additional control and customization available from dedicated resources over a computing infrastructure hosted on-premises. ~From Microsoft
Hybrid Cloud : Hybrid cloud refers to a mixed computing, storage, and services environment made up of on-premises infrastructure, private cloud services, and a public cloud — such as Amazon Web Services (AWS) or Microsoft Azure — with orchestration among the various platforms. Using a combination of public clouds, on-premises computing, and private clouds in your data center means that you have a hybrid cloud infrastructure.
Artificial Intelligence : Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.Some activities computers with artificial intelligence are designed for include -
Learning;
Speech Recognition;
Problem Solving.
Hybrid cloud computing with artificial intelligence — Hybrid cloud computing with AI are perfect match for each other. Combining the data stored within cloud with data driven AI machines , humans can analyze more data faster with more accuracy than ever before.The necessity for quicker and real-time decision making has led the explosion of data from Internet Of Things (IOT) will reshape the very aspect of cloud.
Examples of AI services in a hybrid cloud computing environment are Amazon’s Deep Scalable Sparse Tensor Network Engine(DST NE) and Google’s Tensor Flow.
A next-gen cloud AI platform should be able to deploy a program authored using a deep learning framework like Tensor Flow or Torch across hundreds of nodes that are provisioned on demand GPU capabilities.
