Is the Data now Transforming to the Cloud?

Nowadays, we are in the era of massive collection of data from tremendous sources and types of data. Internal transactions, social media, mobile devices and automated sensors. Where the benefit of Big Data Analytics take place for generating and finding of useful information.

There are multiple reasons for organizations to switch to cloud in order to gain better performance, costs, flexibility, scalability, agility, and maintenance of digital transformation.

Cloud Computing

Cloud computing can be viewed as one of the most valuable technology for handling the big data and providing the infrastructure as services and these services should be uninterrupted. This computing is one of the cost effective technique for storage and analysis of big data.

Cloud Computing Characteristics

• Shared Infrastructure.

Sharing of physical services, storage, and networking cloud infrastructure is shared across a number of users across virtual software model.

• Dynamic Provisioning.

Rapidly requirements should be automatic services, scalability and enabling expansion services

• Network Access.

Capabilities are available over the network and a continuous internet connection is required for a broad range of devices such as PCs, laptops, and mobile devices, using standards-based APIs (for example, ones based on HTTP).

Deployments of services in the cloud include everything from using business applications to the latest application on the newest smart phones.

• Managed Monitoring.

Resource usage can be monitored, controlled, and reported, providing transparency for both the provider and consumer of the utilized service.

Cloud Services Model

????????Infrastructure as a Service (IaaS): Is a cloud computing model based on the principle that the entire infrastructure is deployed in an on-demand model.

????????Software as a Service (SaaS): Software as a service provides businesses with applications

????????Platform as a Service (PaaS): The PaaS services are one level above the SaaS that provide a ready environment

????????Storage as a Service(StaaS) : These services are commonly known as StaaS it facilitates the cloud applications to scale beyond their limited servers.

????????Data as a Service (DaaS):??Is a?data?management strategy that uses the cloud and/or analytics?services?via a network connection

Cloud Deployment Models

????????Private Cloud??The Private clouds are basically owned by the single organization comprising multiple consumers For example, banks and governments have data security issues that may preclude the use of currently available public cloud services.

????????Public Cloud? ?The cloud infrastructure is provisioned for open use by the general public. It may be owned, managed, and operated by a business, academic, or government organization,?or some combination of them.

??????Amazon Elastic Compute Cloud (EC2), Microsoft Azure, IBM's Blue Cloud, Sun Cloud, and Google Cloud are examples of the public cloud

Hybrid-cloud and?Multi-cloud are two strategies that are quite popular for enterprises creating their cloud strategies. They are often confused terms.

Both Hybrid cloud and multi-cloud refer to cloud deployments that integrate more than one cloud platform. But the difference is in the cloud infrastructure in which is included. A hybrid cloud infrastructure merger two different types of clouds, for example, blends public and private clouds. However, multi-cloud is combining different services from the same type of cloud, especially in the public cloud.

Organizations may also adopt more to hybrid clouds deployments to keep some of their sensitive data and processes controlled through their environments private clouds or on their own premises while taking the advantages of resources and infrastructures on public clouds. Still, the challenges remain the same for complexity, costs, downtime, privacy, security, operational efficiency, and latency.

Requirement & Challenges

When we talk about challenges and problems of cloud migrations many organization faces, we found most of these organizations are afraid of the network or services outages. Downtime is one of the most critical and common issues that might be faced in cloud migration. However, backup environments and strategies play a crucial role to avoid such challenges. Another very important issue companies faces are Data privacy and security as the internet security is the biggest issue IT company are afraid of. Cyberattacks are growing rapidly and data breaches are increasing. So all possible security solutions have to be developed to ensure no data leakage or breach. Interoperability is another demanding issue in cloud migration as it refers to the ability of systems to communicate to each other and it is not easy for an organization to establish proper communication between their applications so it is recommended to adopt internal processes with the cloud provider framework to achieve the proper success of communications.?

AI & Machine Learning in cloud services

Cloud Machine Learning Platforms

like Google Cloud Machine Learning , AWS Machine Learning, and Azure Machine Learning. These services enable you to?build machine learning models that work with any type or size of data.

AI Cloud Services

Technologies like IBM Watson, Microsoft Cognitive Services, Natural Language APIs or Google Cloud Vision allow abstraction of complex AI. It also permits cognitive computing capabilities through simple API calls.