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Microsoft Azure Interview Questions
Some other ways to manage session states are :
 
* Windows Azure AppFabric caching : It is a distributed in-memory cache service giving fast access, and is officially supported by Microsoft. However, it is slightly expensive. Microsoft recommends this option and is automated provisioned based on the Windows Server AppFabric Caching Technology.

* InProc session : It stores the session in the web server’s memory, thus giving faster access. It is cost-effective but valid for a single instance only.
Yes. We can do so using Azure DevOps. It is a tool that automates the CI/CD process. To do so, you should : 
 
* Replicate (clone) the project into the system
* Commit the code
* Execute CI/CD
* Check the Azure CI/CD pipelines configured by the starter
* Create a sample DevOps project (ASP.NET) using the Azure DevOps Starter resource.
Azure Service Manager (ASM) Azure Resource Manager (ARM)
Provides cloud services majorly for IaaS workload and specific PaaS workloads A new portal that provides services for all IaaS and PaaS workloads
XML driven REST API JSON driven REST API
Removal of a resource is slightly tedious Resource removal is simple and easy by using Resource Groups
Deployment is done using PowerShell script Deployment is done using ARM templates 
Many features are not available in ASM Many features like resource tagging, resource movement within the same region, role-based access control feature etc. are available
Azure machine learning can train, deploy, manage, automate and track machine learning models in a cloud environment. You can use it for classical ML, deep learning, supervised, or unsupervised learning algorithms. Azure machine learning contains many tools like Azure machine learning designer, Jupyter/R notebooks, Machine learning CLI, TensorFlow, scikit-learn, PyTorch etc. 
PowerShell is a set of cmdlets that provides many features for automation. We can create, test, deploy and manage Azure resources and services from the Powershell command line. It is an extension of Windows PowerShell.
Azure data factory uses integration runtime to enable various data integration capabilities across the network environments. Integration runtimes are of three types:
 
Azure integration run time : It can copy data between cloud data stores and can dispatch the activity to various compute services like SQL server or HDInsight for data transformation

Self-hosted integration runtime : Useful to copy data between a cloud data store and a private network data store. It also dispatches transform activities on on-premises or virtual network resources. 

Azure SSIS integration runtime : Using this, we can execute SSIS packages natively in a managed environment. It is useful for shifting SSIS packages to the Azure data factory.
A build is the solution of an output. In Azure projects, you get the record with a .cspkg extension, that is, a Cloud Service Package is utilized for the deployment of your cloud administration.
 
Build Servers : In general terms, a build server is a machine where you put your deployment packages.
 
To utilize Team Foundation Build, you should have no less than one build machine. This machine can be a physical machine or a virtual machine.
 
Build Controllers : Manufacture Controllers are the component in the build system that accepts the build requests from any task inside the group project. Each build controller is dedicated to a solitary team project collection. So, there is a balanced relationship between a team project and a build controller.
 
Build Agents : Build Agents are components in the build system that accomplishes more processor-concentrated work.
To make an Azure HDInsight Cluster, open the Azure portal > click on New > select Data Services > click on HDInsight.
 
Hadoop is the default and native execution of Apache Hadoop.
 
HBase is an Apache open-source NoSQL database based on Hadoop that gives random access and solid consistency for a lot of unstructured data.
 
Apache Storm is a distributed, fault-tolerant, open-source computation system that enables you to process data in real-time.
Cloud computing types are service deployment models which let you choose the level of control over your information and types of services you need to provide. There are three main types of cloud computing services, sometimes called the cloud computing stack because they build on top of one another.
 
The first cloud computing type is infrastructure-as-a-service (IaaS), which is used for Internet-based access to storage and computing power. The most basic category of cloud computing types, IaaS lets you rent IT infrastructure - servers and virtual machines, storage, networks and operating systems - from a cloud provider on a pay-as-you-go basis.
 
The second cloud computing type is platform-as-a-service (PaaS) which gives developers the tools to build and host web applications. PaaS is designed to give users access to the components they require to quickly develop and operate web or mobile applications over the Internet, without worrying about setting up or managing the underlying infrastructure of servers, storage, networks and databases.
 
The third cloud computing type is software-as-a-service (SaaS) which is used for web-based applications. SaaS is a method for delivering software applications over the Internet where cloud providers host and manage the software applications making it easier to have the same application on all of your devices at once by accessing it in the cloud.