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 computer's hard drive. The cloud is just a metaphor for the Internet. Using cloud computing, users are able to access software and applications from wherever they need, while it is being hosted by an outside party — in “the cloud.” This means that they do not have to worry about things such as storage and power, they can simply enjoy the end result.

Using cloud computing, to eliminate those problems that come with storing own data, because they are not managing hardware and software — that becomes the responsibility of an experienced vendor. The shared infrastructure means it works like a utility. Because only pay for what is the need, upgrades are automatic, and scaling up or down is easy. Cloud-based apps can be up and running in days or weeks, and they cost less. Using cloud app, you just open a browser, log in, customize the app, and start using it.

Cloud computing provides the simplest way to access servers, storage, databases and a broad set of application services over the Internet. A Cloud services platform such as Amazon Web Services owns and also maintains the network connected hardware required for these application services.

Types of clouds:

Basically there are three types of clouds in cloud computing. They are:

1. Public clouds

2. Private clouds

3. Hybrid clouds

Public Clouds: This cloud is basically the internet. Service providers use the internet to make resources, such as applications (also known as Software-as-a-service) and storage, available to the general public cloud. Example:

Amazon;

Elastic Compute Cloud (EC2);

IBM’s ;

Blue Cloud;

Sun Cloud;

Google;

AppEngine.

There are some limitations, however; the public cloud may not be the right fit for every organization. The model can limit configuration, security, and SLA specificity, making it less-than-ideal for services using sensitive data that is subject to compliance regulations.

Private Clouds

This types of clouds are data center architectures owned by a single company that provides flexibility, scalability, provisioning, automation, and monitoring. The goal of a private cloud is not sold “as-a-service” offerings to external customers but instead to gain the benefits of cloud architecture without giving up the control of maintaining your own data center.

Hybrid Clouds

A Hybrid Cloud is defined by any combination of Clouds. It could be a Private Cloud and one or more Public Clouds. Likewise, it could be a Virtual Private Cloud and one or more Public Clouds. It is, more than just multiple Clouds. There need to be resources shared among the Clouds. Example: Cloud Bursting.

Hybrid cloud computing:

Hybrid cloud is a composition of two or more distinct clouds such as private, community, or the public that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability. Basically, hybrid cloud computing means managing a public and a private cloud as one, or at the least being able to have management tools across the two environments.

Artificial intelligence:

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. Some of the activities computers with artificial intelligence are designed for include:

Speech recognition;

Learning;

Planning;

Problem-solving.

Hybrid cloud computing with artificial intelligence:-

Combining AI, machine learning, and the data stored with cloud computing technology means that both AI and humans can analyze and gather more data than ever before. Hybrid cloud is a disruptive technology development and a business opportunity. Artificial intelligence is bound to become ubiquitous in every industry; it will impact the enterprises in more profound ways. The necessity for quicker and real-time decision-making and the recent explosion of data from Internet Of Thing(IOT) will reshape every aspect of the enterprise cloud. There will be autonomic, economic-based intelligence to manage multi-cloud environments and ultimately delivers Hybrid cloud computing capabilities.

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.

Claiming that AI can influence a new generation of cloud computing infrastructure is an interesting proposition considering that transformational technology trends such as mobile or the internet of things (IoT) haven’t had a disruptive impact on the cloud computing landscape. However, the analysis makes sense if we factor in an important difference between movements like mobile or IoT and AI.

From the cloud platform perspective, mobile and IoT capabilities materialized as backend services that could be used from mobile applications or IoT devices. In this sense, cloud platforms were not required to provide the runtime to run IoT or mobile platforms but rather services that enable the backend capabilities of those solutions. Contrasting with that model, AI applications require not only sophisticated backend services but a very specific runtime optimized for the GPU intensive requirements of AI solutions. For instance, a next-generation cloud AI platform should be able to deploy a program authored using a deep learning framework like TensorFlow or Torch across hundreds of nodes that are provisioned on demand with optimal GPU capabilities.