Skip to main content

Benefits and usage of Core Azure Architectural Components

Azure core benefits and usage of Azure Architectural Components.
  • Azure Regions provide customer flexibility to bring application closer to the user by allowing them to choose regions closer to them as per the geographical location.
  • Azure provides Region pairs for disaster recovery if there is any natural calamities or any one data center is down due to any technical reason,
  • Azure Availability zone provides you a guaranteed SLA of 99.9%. The availability zone helps to recover from data center level failure.
  • Availability Sets allows you to achieve 99.95% SLA. Availability Sets keeps application online during maintenance or hardware failure with the help of the fault domain and update domain.
  • Azure Resource Group helps you to organize your resources. This helps to delete all the resources in one shot by deleting the resource group.
  • Azure Resource Manager helps to create, configure, manage, delete and control access to the resource groups and all the resources under it. It provides a consistent management layer which allows you to automate the deployment and configuration of these resources using different automation scripting tools such as power shell, Azure CLI or Azure Portal.
I hope this has been informative and thank you for reading!

Comments

Popular posts from this blog

Azure Cloud

What is Cloud Computing? Cloud computing is a term referred to as storing and accessing data over the internet. It doesn't store any data on the hard disk of your personal computer. In cloud computing, you access data from a remote server. What is Microsoft Azure? Azure is a cloud computing platform that was launched by Microsoft in February 2010. It is an open and flexible cloud platform that helps in development, data storage, service hosting, and service management. The Azure tool hosts web applications over the internet with the help of Microsoft data centers.  Types of Azure Clouds There are mainly three types of clouds in Microsoft Azure are:     PAAS     SAAS     IASS  I hope this has been informative and thank you for reading!

Machine Learning in Azure

Machine learning is a method of data analysis that automates analytical model building. It's a branch of Artificial Intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human interaction. This series of articles intend to elaborate the usage of Azure Machine learning and usage of different machine learning tools in Azure ML studio. This is the first post and it walks you through the introduction to the Azure ML studio and how to upload data to the tool. Two most widely adopted machine learning methods are,  Supervised learning: algorithms are trained using labeled examples, such as    an input where the desired output is known Unsupervised learning: is used against data that has no historical labels. The System is not told the "right answer." The algorithm must figure out what is being shown.   Differences between data mining, machine learning and deep learning  Data mining is about to ident...

What is Jenkins, and how to use it for DevOps

Jenkins is an Open Source software written in Java. It provides services like Build Management, and can be used for running tests (functional or UI). It is also used for CI (Continuous Integration) as well as CD (Continuous Delivery). Jenkins is a free tool, easy to install and configure. We can add various plugins which can help in integrating different tools like Azure DevOps, GitHub (for source control), Maven, Ant, MS Build (for build as well as testing), Selenium (UI automation), Ansible (for deployment) and many more. Using Jenkins, it becomes easy to integrate all kinds of tools for build, testing, packaging, analyzing, deploying etc. In this two-part tutorial series, I will discuss integration of Jenkins with various tools such as:     Azure DevOps and GitHub: for Source Control     Java with Eclipse and C# with Visual Studio 2017: for code writing     Apache Ant, Apache Maven and MS Build: for Build Management    Juni...