Featured post

Best Machine Learning Book for Beginners

You need a mixof different technologies for Data Science projects. Instead of learning many skills, just learn a few. The four main steps of any project are extracting the data, model development, artificial intelligence, and presentation. Attending interviews with many skills is not so easy. So keep the skills short.
A person with many skills can't perform all the work. You had better learn a few skills like Python, MATLAB, Tableau, and RDBMS. So that you can get a job quickly in the data-science project.
Out of Data Science skills, Machine learning is a new concept. Why because you can learn Python, like any other language. Tableau also the same. Here is the area that needs your 60% effort is Machine learning.  Machine Learning best book to start.

Related Posts How to write multiple IF-conditions in Python Simplified

How to achieve Virtualization in cloud computing real ideas

In order to run applications on a Cloud, one needs a flexible middleware that eases the development and the deployment process.

Middleware Approach to Deploy Application on Cloud

  1. GridGain provides a middleware that aims to develop and run applications on both public and private Clouds without any changes in the application code. 
  2. It is also possible to write dedicated applications based on the map/reduce programming model. Although GridGain provides a mechanism to seamlessly deploy applications on a grid or a Cloud, it does not support the deployment of the infrastructure itself.
  3. It does, however, provide protocols to discover running GridGain nodes and organize them into topologies (Local Grid, Global Grid, etc.) to run applications on only a subset of all nodes.
    Elastic Grid infrastructure provides dynamic allocation, deployment, and management of Java applications through the Cloud. 
  4. It also offers a Cloud virtualization layer that abstracts specific Cloud computing provider technology to isolate applications from specific implementations

Virtualization in CLOUD Computing

With the rapid expansion of Information Technology (IT) infrastructures in recent years, managing computing resources in enterprise environments has become increasingly complex.

In this context, virtualization technologies have been widely adopted by the industry as a means to enable efficient resource allocation and management, in order to reduce operational costs while improving application performance and reliability.
  1. Generally speaking, virtualization aims at partitioning physical resources into logical resources that can be allocated to applications in a flexible manner.
  2. For instance, server virtualization is a technology that partitions the physical machine into multiple Virtual Machines (VMs), each capable of running applications just like a physical machine. By separating logical resources from the underlying physical resources, server virtualization enables flexible assignment of workloads to physical machines.
  3. This not only allows workload running on multiple virtual machines to be consolidated on a single physical machine but also enables a technique called VM migration, which is the process of dynamically moving a virtual machine from one physical machine to another.

Comments

Popular posts from this blog

Hyperledger Fabric: 20 Real Interview Questions

Python IF Statements Multiple Conditions Examples

Best Machine Learning Book for Beginners