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Introduction to Azure Data Factory Integration Runtime

Azure data factory integration runtime is a compute infrastructure used in azure synapse pipeline and azure data factory to provide capabilities of integration across multiple environments of the network. In Azure, the data factory and synapse pipeline define the action which we perform. Linked service in azure defines the compute service of the target data store. Runtime integration provides the bridge between azure linked services.

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Key Takeaways

The trigger pipeline stores the instance metadata. The pipeline connects to data stores and computes services in Azure regions to move data between compute services.

At the time of creating an instance of a data factory or workspace of the synapse, we need to specify its location.

What is Azure Data Factory Integration Runtime?

The azure data factory runtime integration provides the reference of linked service activity as well as the computing environment where we can run the activity or dispatch the same. It allows the activity that was performed into the possible region to the compute service or target data store for maximizing performance and allowing flexibility for meeting compliance requirements.

How to Create Integration Runtime?

The below step shows how we can create the azure integration as follows. First, we are connecting to the Azure portal.

1. In the first step, we are login into the azure portal by using the specified credentials of the azure portal as follows.

3. After opening the create resource tab, we are opening the integration runtime to create new integration as follows.

5. After selecting the runtime setup of integration, we will define the name, type, and region of integration as follows.

6. After defining the name, type, and region of integration, we will define the data flow.

7. After defining the data flow, we will edit the linked service and add our integration into it.

8. After adding the integration, we can check that azure data factory integration is created in the dashboard.

Azure Integration Runtime SSIS

The azure integration runtime is a fully managed cluster of azure virtual machines that were used to run our SSIS packages. We can bring our own SQL database or a managed instance of SQL for the SSIS catalog. We can increase the power to compute the node size of scale by specifying the number of nodes in the cluster. We can manage the running azure cost of our integration by starting and stopping the demand for requirements.

While using familiar tools such as a SQL server management studio and server data tools such as on-premises SSIS to deploy and manage the existing SSIS package with little change. We use the azure SQL database server to manage data by using IP/Firewall network service endpoint rules to connect managed instances or the azure SQL database server.

We are creating an SSIS DB instance on behalf of a single database as part of an elastic pool of managed instances. We can access the SSIS through the public network or through a virtual network.

Types of Azure Data Factory Integration Runtime

Azure data factory offers three types of integration runtime; we need to choose the type as per our needs and need to choose as per network environment capabilities and data integration capabilities.

Below is the type of integration runtime as follows:

Azure – Azure supports data flow, activity dispatch, and data movement into the public network. It will support data flow, activity dispatch, and data movement with private link support. This type is commonly used when creating azure data factory runtime integration.

Self-hosted – Self-hosted supports activity dispatch and data movement into the public network. It will support activity dispatch and data movement in private link support. This type is frequently used when creating azure data factory runtime integration.

Azure-SSIS – When the Azure SSIS package is executed, it will support the public network. The public link will be supported when the Azure SSIS package is executed. This type is used when developing the SSIS package.

Integration Runtime Location

The integration runtime location defines the back-end compute and the SSIS package execution, which we have performed.

We can set the below location as follows:

Azure IR location – We can set an Azure IR location region in which activity execution of dispatch takes place. The effort is made automatically to copy the activity, which detects the sink data store location, then we use IR in the same region. When copying data to an Azure blob in the west US, the blob is detected in the US region, and the copy activity is performed in the IR. The synapse region workspace is used for the data flow of IR. During the activity, we can see which locations are having an impact.

Self-hosted IR location – The self-hosted IR location is logically associated with the synapse workspace or data factory that was used to support the functionalities that we provided. As a result, there is no explicit property of self-hosted IR. When performing data movement, self-hosted IR extracts data from the source and writes it to the destination.

Azure SSIS IR location – To achieve the performance, the azure SSIS location must be chosen. The location of our Azure SSIS does not have to be the same as that of our data factory, but it must be the same as that of our SQL database. If we do not already have a database, we must create one in the same location where the virtual network is created. Using the same method, we are creating an Azure SSIS IR for the same location in order to reduce data movement and associated costs.

Command

In the below example, we are creating the azure data factory integration runtime by using the command as follows.

1. In the first step, we are launching the windows PowerShell in our local system as follows.

2. After launching the PowerShell, now in this step, we create the variable and copy and paste the same in the script as follows.

$SubscriptionName = "Azure_sub" $ResourceGroupName = "Azure_grp" $DataFactoryLocation = "EastUS" $SharedDataFactoryName = "Azure_df" $SharedIntegrationRuntimeName = "Azure_IR" $SharedIntegrationRuntimeDescription = "Azure integration runtime" $LinkedDataFactoryName = "Azure_LDF" $LinkedIntegrationRuntimeName = "Azure_LDFR" $LinkedIntegrationRuntimeDescription = "Azure integration runtime linked source"

3. After creating the script now in this step, we login into the azure portal through windows Powershell as follows.

Select-AzSubscription -SubscriptionName $SubscriptionName

4. After login into the azure portal now, in this step, we are running the following command to create the data directory as follows.

Set-AzDataFactoryV2 -ResourceGroupName $ResourceGroupName ` -Location $DataFactoryLocation ` -Name $SharedDataFactoryName

Integration Runtime Network Environment

Azure integration runtime is used to connect compute services and data stores to publicly accessible endpoints. To enable the virtual network managed by the Azure runtime to connect data stores for the purpose of using the private link service in the network environment.

We have options in the synapse workspaces to limit outbound traffic from the managed virtual network of integration runtime. All ports in Azure Data Factory are open for outbound communications. The azure SSIS integration runtime is integrated with the virtual network to provide outbound communication controls.

Conclusion

Azure data factory integration runtime is a compute infrastructure used in azure synapse pipeline and azure data factory to provide network integration capabilities across multiple network environments. The self-hosted integration performs copy operations between the private network and the cloud data store.

Recommended Articles

This is a guide to Azure Data Factory Integration Runtime. Here we discuss the introduction, how to create integration runtime, types, location, and command. You can also look at the following articles to learn more –

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8 Best Data Integration Tools To Look Over In 2023

Data integration is the process of retrieving data from disparate source systems into meaningful and valuable information. It integrates data collected in such a way that it can create reliable, inclusive, current and correct information for business reporting and analysis. The source systems collect data from a number of devices and in a variety of formats. A complete data integration solution delivers trusted data from various sources. There are several data integration tools available in today’s constantly evolving marketplace, all racing to keep up with the intensifying incursion of data. So, let’s take a deep dive into top data integration tools that are widely used in today’s market.  

As a data integration platform as a service and used by SMBs, and large companies, Dell Boomi supports many application integrations processes. It provides several prevailing integration and data management capabilities. Dell Boomi’s data integration capabilities range from a large library of on-premises, private cloud and public cloud endpoint connectors, to ETL (extract, transform and load) support. It allows sites to manage their data integration in one central place through a unified reporting portal. According to the reports, Dell Boomi is well suited to shift, manage, oversee and compose data across hybrid IT architectures. Features: •  A visual interface to constitute application integrations •  Design integration processes •  Workflow and business process automation •  The lightweight, dynamic run-time engine •  Automatic integration updates •  Support for a wide array of IoT protocols •  Activity monitoring and event tracking  

SnapLogic is an integration platform-as-a-service tool that enables faster connections and the incessant updating and evolution of data and analytics systems. It assists in stimulating the adoption of cloud apps such as Workday, Salesforce, and ServiceNow. Features: •  State-of-the-art Application & Data Integration Services •  Transferring data securely from one location to another •  Offering a tool to set up integrations leveraging visual interface without coding •  Providing tools to manage the flow of data throughout its life cycle from creation and initial storage to removal •  Supporting event or transaction-based integrations that counter to changes in real-time •  Supporting various connectors across SaaS, Enterprise, Big Data, Mainframe, Files •  Delivers integration to Big Data sources like Hadoop and other NoSQL sources  

Informatica data integration tool, PowerCenter, is a comprehensive platform for data integration, migration, validation. It is widely used in large enterprises and midsize businesses. PowerCenter runs along with an extensive catalogue of related products for cloud application integration, big data integration, data cleansing, master data management (MDM) and other data management functions. PowerCenter often unites with Informatica’s Data Integration Hub and its PowerExchange line of packaged connectors. Features: •  Centralized error logging system. •  Facilitating logging errors and discarding data into relational tables •  Built-in intelligence to enhance performance •  Superior design with enforced best practices on code development •  Synchronization among geographically distributed team members •  Code integration with other external software configuration tools  

Offering fast, easy, cost-effective data access and availability, Attunity Connect is an easy-to-use data integration solution. It enables real-time, unified connectivity for relational and non-relational data sources. Features: •  Access of a broad area of enterprise data sources •  Advance universal and service-oriented integration •  Delivering industry-leading mainframe integration •  Easy Integration with web applications •  Data-driven business event detection •  Streamline and stimulate integration using a comprehensive software suite for VSAM, IMS/DB, and DB2 data  

Xplenty’s data integration platform offers simple visualized data pipelines for automated data flows across a number of sources and destinations. The company’s cloud-based, easy-to-use, data integration service makes it easy to transfer, process and convert more data, faster, lessening preparation time where companies can unleash insights quickly. Features: •  Centralize and prepare data for BI •  Moving and transforming data between internal databases or data warehouses •  Sending additional third-party data to Heroku Postgres, a SQL database as a service, or directly to Salesforce •  Rest API connector to pull in data from any Rest API.  

Oracle Data Integrator 12c is a best-of-breed data integration platform for organizations that utilize other Oracle systems and applications and want close-fitting data integration with these systems. The platform unites with Oracle Database, Oracle GoldenGate, Oracle Fusion Middleware, Oracle Big Data Appliance and Exadata. Its core functionality is based on ELT architecture. Features: •  Declarative Flow-Based User Interface •  Reusable Mappings •  Multiple Target Support •  Runtime Performance Enhancements •  XML Improvements •  Oracle Warehouse Builder Integration •  Unique Repository IDs •  Oracle GoldenGate Integration Improvements  

SAP Data Services is an ETL tool providing a single enterprises level solution for data integration, transformation, data quality, data profiling, and text data processing from a wide range of sources into a target database or data warehouse. It can be utilized stand-alone or with other SAP products. SAP Data Services tool explores, cleanses, boosts, integrates and manages data from SAP and non-SAP sources, including relational databases, enterprise applications, files and big data sources such as Hadoop and NoSQL databases.

Runtime Type Identification In Java

Runtime Type Identification in short RTTI is a feature that enables retrieval of the type of an object during run time. It is very crucial for polymorphism as in this oops functionality we have to determine which method will get executed. We can also implement it for primitive datatypes like Integers, Doubles and other datatypes. In this article, we will explain the use case of Runtime Type Identification in Java with the help of examples. Program for Runtime Type Identification Let’s discuss a few methods that can help us to identify type of object: instanceOf It is a comparison operator that checks whether an object is an instance of a specified class or not. Its return type is Boolean, if the object is an instance of a given class then it will return true otherwise false.

Syntax nameOfObject instanceOf nameOfClass; getClass()

It is a method of ‘java.lang’ package and is used to return the run time class of a specified object. It does not accept any arguments.

Syntax nameOfObject.getClass();

It is the general syntax to call this method.

getName()

It returns the name of entities such as class, interface and primitives of specified objects of a given class. Its return type is String.

Syntax nameOfClassobject.getName(); Example 1

The following example illustrates the use of instanceOf.

public class Main { public static void main(String[] args) { String st1 = "Tutorials Point"; if(st1 instanceof String) { System.out.println("Yes! st1 belongs to String"); } else { System.out.println("No! st1 not belongs to String"); } } } Output Yes! st1 belongs to String

In the above code, we have declared and initialized a String. The if-else block checked whether ‘st1’ is a String type or not using ‘instanceOf’.

Example 2

In the following example, we compare if two objects are of the same type or not using getClass() and getName() methods.

import java.util.*; class Student { String name; int regd; Student(String name, int regd) { chúng tôi = name; chúng tôi = regd; } } public class Main { public static void main(String[] args) { Student st1 = new Student("Tutorialspoint", 235); Student st2 = new Student("Tutorix", 2011); Class cls1 = st1.getClass(); Class cls2 = st2.getClass(); if(cls1.getName() == cls2.getName()) { System.out.println("Both objects belongs to same class"); } else { System.out.println("Both objects not belongs to same class"); } } } Output Both objects belongs to same class Example 3

In this particular example, we will declare and initialize two primitives and their corresponding wrapper classes. Then, using getClass() we will fetch the name of their classes.

public class Main { public static void main(String[] args) { double d1 = 50.66; int i1 = 108; Double data1 = Double.valueOf(d1); Integer data2 = Integer.valueOf(i1); System.out.println("Value of data1 = " + data1 + ", its type: " + data1.getClass()); System.out.println("Value of data2 = " + data2 + ", its type: " + data2.getClass()); } } Output Value of data1 = 50.66, its type: class java.lang.Double Value of data2 = 108, its type: class java.lang.Integer Conclusion

In this article, we have explored Runtime Type Identification, it is more of a type introspection. We use this feature when we need to compare two objects and also during polymorphism as it allows us to retrieve pieces of information about classes, interfaces and so forth.

Microsoft Azure Vs Amazon Web Services

Difference Between Microsoft Azure vs Amazon Web Services

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Head to Head Comparison Between Microsoft Azure and Amazon Web Services (Infographics)

Below is the top 22 difference between Microsoft Azure and Amazon Web Services:

Key Differences Between Microsoft Azure and Amazon Web Services

Both Microsoft Azure vs Amazon Web Services are popular choices in the market; let us discuss some of the major Difference Between Microsoft Azure and Amazon Web Services:

Amazon Web Services are far behind in hybrid deployment of a cloud, while Azure is far ahead in a hybrid deployment. It allows hosting applications on a local server as well as on the cloud.

AWS allows the client to pick and choose and build the cloud services as they need while Microsoft product is simple to use and you need to use as Microsoft has designed their product.

Amazon Web Services covers the basic enterprise of cloud services while Microsoft Azure also covers basic enterprise quite well.

AWS is way ahead to apt and aligns with Linux and open-source projects, while Azure has caught up for not aligning with open source apps.

Amazon’s comprehensive admin controls operate core features like Compute, Storage, Databases, Networking and Content development while Azure’s Build Infrastructure, Gain Insights from data, Manage to identify and access, Develop modern application covers core features like Compute, Database, Storage, Networking and Content development.

Amazon Web Services provides a Big Data framework – Elastic MapReduce on their cloud platform, while Azure provides Big Data framework – HDInsight on their cloud platform.

Amazon Web Services provide real-time analytics and stream processing on their platform, while Azure provides real-time data processing and analytics over its platform.

Amazon Web Services is very much flexible with VM, database, apps development on their platform and the same is considered on Azure Platform.

AWS and Azure offer you a free trial. You can utilize this offer to decide which services to use.

Microsoft Azure almost doubled its revenues in the year 2023 that is approximately $1.5 billion, while Amazon Web Services claims approximately to $9.7 billion, which is45% increase in revenue. AWS revenues increased by nearly three times as much as Azure´s revenue. It was commercially launched in the year 2010.

Today it is available to 54 regions, spread across 140 countries. Azure has more than 100 services with great end-to-end tools. 120000, new customer subscriptions per month. Microsoft offers all three of the major categories of cloud computing, Platform As a Service (PaaS), Software As a Service (SsaS), Infrastructure As a Service (IaaS). It deals with PaaS and IaaS offerings under the brand name of Microsoft Azure.

AWS is a comprehensive, evolving cloud computing platform provided by Amazon. It provides a cloud platform as an Infrastructure as a Service (IaaS), Software as a Service (SaaS) and Platform as a service (SaaS). It provides Infrastructure as a Service (IaaS) into five different Storage, Computes, Database, Content Delivery, and Networking categories. AWS was the first company to offer a pay-as-you-go cloud computing model.

Microsoft Azure and Amazon Web Services Comparison Table

Below is the topmost comparison between Microsoft Azure and Amazon Web Services.

Basis of Comparison between Microsoft Azure vs Amazon Web Services

Amazon Web Services

Platform As A Service Azure supports Cloud Services AWS supports Elastic Beanstalk

Instances Family Azure support 4 AWS support 7

Instance Types  Maximum up to 33 Maximum up to 38

Caching Azure supports Redis Cache ASW supports Elastic Cache

Analytics Azure Support tool- Azure Stream Analytics AWS support tool – Amazon Kinesis

Data Warehouse Azure Supports SQL Data Warehouse ASW supports Redshift

Virtual Networking Virtual Network Virtual Private Cloud

Administration Log Analytics, Operations Management Suite, Resource Health, Storage Explorer Application Discovery Service, System manager, Personal Health Dashboard

Pricing For Infrastructure pay Per Minute For Infrastructure pay Per Hour

Big Data Platform Less mature comparing AWS for Big Data environment More mature for Big Data environment

Hadoop HDInsight Elastic Map Reduce

NoSQL Databases Azure Document DB Amazon Dynamo DB

Security Features Provides security by enabling permissions on the whole account More Secured as security is provided through user-defined roles with exceptional permission controls.

Object Size Limits 4.75 TB 5 TB

How many platforms are Matured Azure is 8 years old AWS is 18 years old

Market Capture 20% of the entire cloud market 62% of the entire cloud market

Maximum Processor in VM 128 128

Maximum Memory in VM 3800 GB 3904 GB

SAL Availability 99.90% 99.95%

Operating System Supported RHEL, OpenSUSE, Windows, SLES, CoreOS, CentOS, Cloud Linux, Debian, FreeBSD, Ubuntu, Oracle Linux RHEL, Ubuntu, Oracle Linux, Cloud Linux, CentOS, Windows, SLES, Windows, FreeBSD, Debian, CoreOS

Platform Public Cloud Platform for Microsoft An on-demand cloud computing platform for Amazon Web Services

Open Source Community Not much open-source tool supported A large number of Open Source Tool-Supported

Conclusion

We are generating a very huge volume of data, and everyday data are piling up. Most of the data are stored in the cloud. And it opened the door of more growth and business opportunities to cloud vendors. With the exponential growth and demand of Cloud Technology, public cloud vendor are in very high demands. Cloud vendors are increasing their services and reducing their commercials to lead in the market. 62 % of the market share is occupied by AWS, while 20% by Azure. Amazon AWS and Microsoft Azure are truly game player of cloud services. They are important players in the cloud industry. Both Microsoft Azure vs Amazon Web Services are well matured and providing a long list of services. You can choose any of them based on your project requirement. Due to competition, both Microsoft Azure vs Amazon Web Services is trying to attract the customer. Amazon AWS offers the most cloud services, but if you are looking for a hybrid approach, then Microsoft Azure is a better choice. Microsoft Azure vs Amazon Web Services both companies provide excellent developer and IT resources along with top-notch support. Either platform is sure to have the capabilities to accomplish organizational needs.

Recommended Articles

This has been a guide to the top difference between Microsoft Azure vs Amazon Web Services. We also discuss the Microsoft Azure vs Amazon Web Services head to head differences, key differences, infographics, and a comparison table. You may also have a look at the following articles to learn more.

Lesson Plans And Resources For Arts Integration

All teachers at Bates Middle School are expected to use arts integration in their classrooms. Science teacher Stacey Burke (center) and her colleagues share some of their arts-integrated lessons below.

Dance in science, pop art in Spanish, or photography in math — there’s no end to the ways arts can be integrated into other curricula. Educators from Bates Middle School, in Annapolis, Maryland, share arts-integrated lessons and resources that you can use in your school.

Resources on This Page:

Arts-Integrated Lesson Plans

Professional-Development Presentations

Arts-Integration Templates

Additional Documents from Bates Middle School

Maryland Department of Education Arts-Integration Glossary

Useful Websites on Arts Integration

Lesson Plans

Sample arts-integration presentations, lesson plans, quizzes, and other documents from various teachers and classes at Bates Middle School.

6th Grade Science: Rotation and Revolution

Presentation  - lecture on rotation and revolution

Lesson Plan  - lesson plan on solar system, sun, and galaxy

Dance Assignment  - dance choreography that students need to incorporate into their project

Task Cards  - elements of dance to be used to demonstrate rotation and revolution

Exit Ticket  - student-reflection worksheet for rotation and revolution

Quiz  - sample quiz given at the end of the lesson

6th Grade Science: Creative Comparison between Planets and Painting

Presentation  - lecture on physical characteristics of planets integrated with color value concepts

Presentation  - presentation on Ars Ad Astra Project and warm-up routine for observing and imagining

Worksheet  - blank worksheet used for creative comparisons exercise

6th Grade Social Studies: Monochromatic Mapping

Presentation  - lecture on monochromatic mapping

7th Grade Intro to Spanish: Pop Art and Spanish Vocabulary

Overview  - students study the elements of pop artist Roy Lichtenstein and create comic strip using basic Spanish vocabulary

Presentation  - lecture on pop art

Presentation  - presentation and warm-up routine with Lichtenstein’s art and activity using Spanish dialogue

Worksheet  - tree map on colors, shapes, and lines and how they contribute to the artwork

Worksheet  - worksheet used to plan comic strip with Spanish dialogue and visual description for each panel

Student Reflection  - self-reflection worksheet for students to review their comic strip

8th Grade Math: Photo Story

Presentation  - lecture given on photographic composition for photo story project

Lesson Plan  - goals for photo story and how students will use principles of design to represent linear relationships

Rubric  - grading rubric for the photo story project

Storyboard  - blank storyboards used for digital photo story projects

8th Grade Visual and Language Arts: Portraits

Presentation  - presentation on characteristics of portraits from different art movements, including cubism, fauvism, impressionism, pop, and realism

Lesson Plan  - outline of a project in which students will compose a personal narrative detailing a life event

Activity  - matching cards game in which students match artwork to correct art movement

Student Reflection  - self-reflection worksheet on characterization and portraiture

Personal Analysis  - worksheet for student analysis of their self-portrait

8th Grade Science: Dance and Acceleration

Presentation  - lecture on velocity and speed, dance, and movement

Overview  - outline of a project in which students utilize the elements of dance to calculate and graph acceleration

Worksheet  - worksheet for dance challenge in which students calculate and compare speed by measuring dance movements they choreograph

Professional-Development Presentations

Professional-development presentations provided by Pat Klos, arts-integration specialist for Anne Arundel County Public Schools in Annapolis, Maryland

Active Strategies

Activity  - PD activity about different active strategies that integrate dance, song, and other mixed media with science, math, language arts, and social studies

Art History

Presentation  - lecture on 20th-century artists and art movements

Writing and Visual Arts

Presentation  - lecture identifying and demonstrating art-inspired writing strategies

Presentation  - presentation and warm-up routine for writing and visual arts lesson

Principles of Design

Presentation  - lecture on principles of design, including balance, emphasis, unity, and proportion

Presentation  - lecture on objective versus nonobjective art

Foldable  - foldable with all the principles of design

Worksheet  - worksheet for principles of design to use with selected artwork

Artful Thinking

Artful Thinking is an approach to teaching creative thinking developed by Harvard’s Project Zero in collaboration with the Traverse City Area Public Schools in Michigan.

Presentation  - lecture on implementing Artful Thinking routines that will help students

Artful Thinking Routines  - various routines used for artful thinking, including, games, comprehension, and analysis

Arts-Integration Templates

Blank templates for arts-integration documents used at Bates Middle School

Additional Documents from Bates Middle School

Maryland Department of Education Arts-Integration Glossary

Glossary of arts-integration terms provided by Maryland’s Department of Education

Visual Arts  - terminology used for visual arts

Dance  - terminology used for dance

Music  - terminology used for music

Theater  - terminology used for theater

Useful Websites on Arts Integration

Bates Middle School – school’s website

Artful Thinking (Project Zero) – program designed to be used by everyday teachers; focuses on experiencing and appreciating art rather than making art

Arts and Science Council – organization whose goal is to build appreciation, participation, and support for the arts, science, history, and heritage in Charlotte-Mecklenburg

The Kennedy Center ArtsEdge – the Kennedy Center’s free digital resource for teaching through and about the arts

The Kennedy Center ArtsEdge Lessons Plans – lesson plans provided by ArtsEdge, The Kennedy Center’s free digital resource

Masterpiece to Mathematics: Using Art to Teach Fraction, Decimal, and Percent Equivalents – article from the National Council of Teachers of Mathematics detailing how students created their own optical art and connected it to rational numbers through mathematical and visual representations of rational numbers

Arts Integration Solutions – nonprofit that looks to transform the education system by bringing arts integration to every child, in every classroom, helping them succeed in math, science, literacy, and life

More Edutopia Resources on Arts Integration:

Create A Virtual Machine For Free On Microsoft Azure

This article was published as a part of the Data Science Blogathon.

Introduction

This article will show how we can create a free student account on Microsoft Azure without any credit/debit card details and get $100 free for the first 12 months. The prerequisite is that you must have a school or university email address to avail of this benefit.

After creating the student account, I will also show you how you can create a virtual machine on it to deploy your web applications.

First, let’s discuss Microsoft Azure in more detail.

It is a public cloud computing platform developed by Microsoft. It includes a computing engine, analytics, storage, networking, etc. It also provides a portal for users to manage their cloud services and resources that they have taken from Microsoft.

Below are the various services offered by Microsoft Azure:

This tutorial will use its Compute Engine service and create a Virtual Machine to host web applications.

Let’s get started, 😉

Creating a Student Account

In this section, we will create our free student account. As I mentioned earlier, you must have a school or university email.

1. Go to the Microsoft Azure Website.

3. Now login to your Microsoft Account, or you can create a new account if you don’t have any.

Note: Do not use your Work/Institution email while signing in on your Microsoft Account. Log in using any of your personnel’s Gmail or Yahoo email addresses. We will later use the Work/Institution email to verify the student account.

4. After successful login, a Student Verification Page opens, in which you have to enter your Work/Institution email address to verify your academic status.

If your Work/Institution email is valid, you will receive an activation link on your Work/Institution email address to activate your account.

After activating the account, you will be automatically redirected to your Azure Portal. Or, you can also access your portal via that link.

It is what your Azure Portal looks like:

Creating a Virtual Machine

In this section, we will create our Ubuntu Virtual machine on Microsoft Azure.

2. Navigate to Create and then select Azure virtual machine. Refer to the image below.

3. Enter the VM Credentials

Navigate to the Basics tab and create a new Resource Group. Also, enter the Name and Region of the VM.

Note: Sometimes, you will face an issue with the availability of the VMs, that the VMs are not available in the selected region due to the high demand. It mainly occurs in the free tier accounts. If you don’t find any available region, leave that part empty and let Azure select a suitable region automatically.

Now select the following:

Select Availability zone as Zones 1 because we want our server only in one zone. But you can also select multiple zones if you wish for higher availability and fewer downtimes.

Then select the Operating System of your choice. In this tutorial, we have chosen a Ubuntu Server.

Finally, please choose the size of the server. It depends on your budget and requirements.

Then we will set an SSH Public Key to access our VM Remotely. Also, we will select the Inbound port rules to none. Inbound port rules are used to create the firewall settings, and we will make these settings later in the Networking section of the VM.

What is SSH?

SSH (Secure Shell) is a network protocol that enables a secure connection between two machines. It allows transferring files and data in a highly secure manner, using encryption algorithms to encrypt the data during the transfer.

By SSH, we will connect our Local Machine to that VM using a private-public key pair.

Now Navigate to the Disks section, where we will select the type and size of the Disk that we want to use with the VM.

You can select between an HDD or an SSD based on your budget.

Now, you have to create a disk of the particular size that you want to use.

You can select the Size and Type of the Disk according to your requirement.

After creating the Disk, move next to the Networking section.

Now we will select the PORTs in which we want to listen to the requests. Also, please enter the name of your security group, and then we will add a new Inbound rule.

For the Source, we will select * to open all the ports. But for the Destination, we will select only some specific ports on which we can make our server listen to requests. In this tutorial, we will open default PORT 80 and PORT 5000.

Note: You must run your web server on PORT 80 or on PORT 5000 to access your web page publically.

Now go back to your Networking section.

We will not use a Load Balancer at this time. It is used to distribute the traffic between many servers. If you want to know what is a load balancer and wants to create it. You can refer to my other article. In this, I have demonstrated how can we create a load balancer on the Google Cloud Platform.

Now Navigate directly to the Tags section. We don’t have something to change in the Management and Advanced Section. But if you want to explore it, you can also explore it.

We will create a Tag name in the Tags section to categorize the resources.

After that, please review all the configurations of the VM before the final commitment.

Review all the configurations here

Note: Never share your Private key with anyone. Also, keep it with you because you cannot download it again.

Your downloaded private key must look like this:

Save your private key. You don’t get it later on if you have deleted it. Now, you will be redirected to your VM instance.

We will now establish a secure connection between our local machine and the VM instance we have just created.

Put the below-highlighted code in your local machine terminal. The code which is shown below is different for your virtual machine.

Now, open your command prompt and paste that code along with the path of the Private Key that you have downloaded previously.

After authenticating successfully, you will be entered into your VM. You can also monitor the CPU usage, RAM usage and Disk Utilization.

Hurray🎉, now the VM is ready to deploy your web applications.

Conclusion

This tutorial discussed how we could create a free student account on Microsoft Azure. Generally, for the standard account, you need a valid credit card or a debit card to verify your payment details. Still, for students, you only need a valid student email address provided by your university or the institution in which you are studying. Microsoft also offers free 100USD for 12 months to try its services.

Instead of Microsoft Azure, you can also use other famous cloud platforms like Google Cloud or Amazon Web Services. They also provide similar services at a competing price. In the upcoming articles, I will try to cover more services of Microsoft Azure.

4. Finally, we have connected our local machine with the VM using the Private SSH Key.

Do check my other articles also.

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