This learning path contains a collection of courses and hands-on labs designed to help you pass the exam AZ-203 Developing Solutions for Microsoft Azure. More classes will be added shortly!
In this learning path, you will learn how to use services such as Power BI and Spark to surface, process and analyze data to generate intelligence to make more well informed business decisions.
In this learning path, you will learn how to build and architect big data solutions in Microsoft Azure. Topics will include architecting solutions using HD Insight, machine learning, visualizing data with Power BI, understanding lambda architecture patterns and IoT data ingestion. This path will help you prepare for exam Designing and Implementing Big Data Platform Solutions - exam 70-475 and will help you prepare for your MIcrosoft certification.
In this learning path, you will learn how to build and architect SQL focused solutions in Microsoft Azure. Topics will include SQL Server in Azure IaaS, SQL Database and SQL Data warehouse. This course will help you prepare for exam 70-473 Implementing Cloud Data Platform Solutions and prepare for your Microsoft certification.
This path contains courses and labs designed to help you learn about performing data science using services in Microsoft Azure such as Azure ML.
In this module, attendees will learn how to design solutions using Azure Infrastructure as a Service Components. This module will focus on core capabilities, use cases, and general best practices as well as discuss peripheral services such as Azure Backup and Site Recovery.
This course gives you an introduction to Azure Machine Learning (ML) and associated technologies, such as R, Power BI and RStudio. This course begins by covering an introduction to Azure ML, and then we walk through Azure ML as if we were working our way through a Data Science Project. Once the Data Science project is complete, we will look at how you can set up and report on the Azure ML modelling process with Power BI.
In this course, students will learn how to use Azure's built-in capabilities for investigating and diagnosing common networking issues.
This course will be a deep dive into Azure SQL Database performance. We will look at designing an Azure SQL Database architecture for performance. We will look at performance specific features of Azure SQL Database. We will also cover monitoring and troubleshooting.
This module will cover all aspects of big data storage and batch processing. We will start by making the case for big data in Azure. Then we will look at Azure service topics to include Blob Storage, Azure Data Lake Store, Azure Data Lake Analytics, and HDInsight clusters running Hadoop, Hive, Interactive Hive (LLAP) and Spark. Storage topics will focus on choosing the right storage, configuring storage and storage optimization. We will also cover Big Data scenarios including batch processing, interactive clusters, multi-cluster deployments and on-demand clusters.
In this course, students will learn about the core Azure networking features available to Azure Virtual Machines. This module teaches students how Virtual Machine networking is implemented, for external connections to the Internet, for internal connections within Virtual Networks, and for connections to on-premises networks. Students learn how to control network access with Network Security Groups and Application Security Groups as well as how to control network flows with User-Defined Routes. The course finishes with a detailed discussion of both Internet-facing and Intranet-facing DNS scenarios in Azure.
This course helps Azure developers learn how to develop an app service logic app, integrate Azure search within solutions, establish API gateways, develop event based solutions and develop message based solutions
In this course, you will learn how to create web apps by using various Azure Platform as a Service components as as well as understand how to use Azure Container-based services.This course is part of the AZ 300 learning path for Microsoft Azure Architect Technologies.
Students will learn how to analyze resource utilization and consumption, create and configure storage accounts, create and configure a VM for Windows and Linux, create connectivity between virtual networks, implement and manage virtual networking, manage Azure Active Directory, and implement and manage hybrid identities.This course is part of the AZ 300 learning path for Microsoft Azure Architect Technologies.
This course teaches IT Professionals how to create and manage virtual machines as part of an Infrastructure as a Service (IaaS) computing infrastructure. Students learn how to assess their on-premises environment for virtual machine readiness in preparation for moving resources to the cloud to include sizing, pricing, and design considerations.Next, students learn how to create and deploy virtual machines in Azure using the Azure portal, PowerShell, and ARM templates. The course includes instruction on deploying custom images and Linux virtual machines. Then, students learn how to configure the networking and storage components of virtual machines. Deploying highly available virtual machines is critical in the light of planned and unplanned events, and students learn how to use availability sets to ensure that virtual machine resources are available during downtime followed by how to use extensions and Desired State Configuration (DSC) for post deployment automation and configuration tasks.Finally, students learn how to perform virtual machine backups and how to use Azure’s monitoring capabilities to collect, view, and analyze virtual machine diagnostic and log data.
This is course four of the exam prep for AZ-301: Microsoft Azure Architect Design. Students will learn to design a Site Recovery Strategy, design for High Availability, design a disaster recovery strategy for individual workloads and design a Data Archiving Strategy.
In this course the student will learn how to design a data management strategy, design a data protection strategy, design and document data flows, and design a monitoring strategy for the data platform.
In the course the student will learn about designing a storage strategy, networking strategy, compute strategy, and monitoring strategy for infrastructure.
This is course five of the exam prep for AZ-301: Microsoft Azure Architect Design. Students will learn how to design deployments, design migrations and design API integration strategy in Microsoft Azure.
This is course two of the exam prep for AZ-301: Microsoft Azure Architect Design.The Design for Identity and Security course teaches design identity management, design authentication, design authorization, design for risk prevention and identity, and how to design a monitoring strategy for identity and security.
This is course one of the exam prep for AZ-301: Microsoft Azure Architect Design. This course covers a range of topics, including the gathering of information and workload requirements, how to optimize a consumption strategy, and how to design an auditing and monitoring strategy.
In this course students will gain the knowledge and skills needed to implement Azure IaaS services and features in their development solutions. The course covers provisioning virtual machines, using Batch Service to deploy/maintain resources, and how to create containerized solutions by using Azure Kubernetes Service.
In this course you will gain the knowledge and skills needed to implement Azure Platform as a Service feature and services in their development solutions. Students will learn how to create and manage Azure App Service resources, integrate push and offline sync in their mobile apps, and how to document an API. Students will also learn how to create and test Azure Functions.
In this course students will gain the knowledge and skills needed to leverage Azure storage services and features in their development solutions. It covers Azure Table storage, Azure Cosmos DB, Azure Blob, and developing against relational databases in Azure.
This course will expose the student to developing solutions that use Cosmos DB storage, developing solutions that use a relational database, configuring a message-based integration architecture, and how to develop for autoscaling.This course is part of the AZ 300 learning path for Microsoft Azure Architect Technologies.
This course teaches IT Professionals how to implement Azure storage solutions for a variety of scenarios. Students learn about the different storage accounts and services as well as basic data replication concepts and available replication schemes. Students are also introduced to Storage Explorer as a convenient way to work with Azure storage data. Students also learn the types of storage and how to work with managed and custom disks. Azure blob storage is how Azure stores unstructured data in the cloud, and students learn how to work with blobs and blob containers. They also learn how to use Azure Files to work with file shares that are accessed via the Server Message Block (SMB) protocol. In addition to blob storage, this course covers Table and Queue storage as storage options for structured data. Students then learn how to secure and manage storage using Shared Access Signatures (SAS) and Azure Backup using Recovery Services Vault. Next, students learn how to use Azure File Sync to centralize an organization’s file Shares in Azure Files. Content Delivery Network (CDN) is used to store cached content on a distributed network of servers that are close to end-users. Students learn how to optimize content delivery with Azure CDN as well as how to transfer large amounts of data using the Azure Import/Export service. Lastly, students learn how to monitor Azure storage by configuring metrics and alerts and using the Activity Log. Students learn how to analyze usage trends, trace requests, and diagnose issues with a storage account.
Learn how to Implement authentication in applications (certificates, Azure AD, Azure AD Connect, token-based), implement secure data (SSL and TLS), and manage cryptographic keys in Azure Key Vault.This course is part of the AZ 300 learning path for Microsoft Azure Architect Technologies.
Welcome to the Implement Azure Security course. This course covers some of the foundational elements for implementing secure applications and data in the cloud as part of a sound security strategy for your organization. We will also cover Azure Key Vault, a service that provides secure storage of your secrets and other sensitive information, followed by the approaches and considerations of disk and data encryption in Azure.
Students will learn how to migrate servers to Azure, configure serverless computing, implement application load balancing, integrate on-premises network with Azure virtual network, manage role-based access control (RBAC) and implement Multi-Factor Authentication (MFA).This course is part of the AZ 300 learning path for Microsoft Azure Architect Technologies.
In this hands-on course, students will learn about Azure SQL Data Warehouse. This course will review basic architecture of Azure SQL Data Warehouse. We will cover tools used with Azure SQL Data Warehouse, loading SQL Data Warehouse and basic workload management in SQL Data Warehouse.
This course introduces students to Azure Data Factory V2. Students will learn about the different phases of a Data Factory Pipeline. Students will then cover Data Factory Architecture, terminology, the copy activity, file formats, integration runtimes, scheduling and triggers, and data factory management.
In this course, students will learn the fundamentals of hybrid networking in Azure. This includes connecting Azure virtual networks to on-premises systems for communications between on-premises users and systems and Azure services - both private such as virtual machines and public such as Azure SQL and Azure App Services. Students will also learn about the available VPN types and how to configure them.
This course looks at services and tools used for machine learning with Azure. This course will introduce students to Machine Learning Server, SQL Server Machine Learning Services, Cognitive Toolkit, the Data Science Virtual Machine, and the Azure AI Gallery.This course will assist you in preparing for the "Using Other Services for Machine Learning" section of the "Perform Cloud Data Science with Azure Machine Learning" Microsoft Exam 70-774.
In this course, students will learn the fundamentals of load balancing in Azure and explore Azure load balancing services in detail. Services include Azure Load Balancer, Azure Application Gateway, and Azure Traffic Manager. In addition, students will learn how these services can be combined to build resilient application architectures for both IaaS and PaaS hosted applications.
This course teaches IT Professionals how to manage their Azure subscriptions to include access, policies, compliance, and how to track and estimate service usage and related costs. Students learn how cloud resources are managed in Azure through user and group accounts and how to grant appropriate access to Azure AD users, groups, and services through role-based access control (RBAC). Students also discover the core monitoring tools and capabilities provided by Azure including Azure Alerts and Activity Log. Students are then introduced to Log Analytics as a broad data analytics solution as well as how to use this service to query and analyze operational data. Finally, students learn about the Azure Resource Manager (ARM) deployment model and how to work with resources, resource groups and ARM templates.There are three modules in this course altogether:Manage Azure Subscriptions and Resources OverviewMonitor Subscription ResourcesAzure Cost Management and OptimizationBecause this course is the first course in the series for the Azure Administrator exams, there is a considerable amount of foundational content that is covered here in order to prepare students for the remaining courses in the curriculum. As a result, students are provided with a lesson that covers tips and tricks for working in the Azure portal as well as an introduction to key tools used in the Azure environment such as the Cloud Shell and Resource Explorer. Emphasis is laid on PowerShell and the command line interface (CLI) as important skills to acquire not only in preparation for the exam, but for the job role itself.
In this course, students will learn how to manage and configure Azure Active Directory in basic and advanced deployment scenarios. Students will learn how to manage hybrid identity to include attribute writeback as well as how to manage devices with Azure Active Directory.
In this course students will gain the knowledge and skills needed to ensure applications hosted in Azure are operating efficiently and as intended. Students will learn how Azure Monitor operates and how to use tools like Log Analytics and Application Insights to better understand what is happening in their application. Students will also learn how to implement autoscale, instrument their solutions to support monitoring and logging, and use Azure Cache and CDN options to enhance the end-user experience.
This module will provide an overview of big data, IoT and machine learning solutions in Azure. We will define the meaning of big data and look at the reasons why you might need a big data solution. We will then move on to a discussion of the analytics maturity model to understand how machine learning extracts value from big data. Next, we will review the lambda architecture which is the dominant architecture for big data solutions. We will look at the Azure components used in big data solutions and how they fit together to build an end-to-end lambda architecture in Azure. Finally, we will wrap up with a discussion of the Cortana Intelligence Suite and the value that it brings to big data and analytics solutions in Azure.
This course builds on your Power BI skills and walks you through the interfaces of both the Online and Desktop offerings before embarking on a journey that will show you how to ingest data, transform data, create reports and dashboards before publishing and using your data sets, reports and dashboards in the Power BI online tenant.The course will help prepare students to take the Microsoft 70-778, Analyzing and Visualizing Data with Power BI certification exam.
The Real-Time Ingestion and Processing in Azure course covers information about implementing real-time event stream ingestion and processing within Microsoft Azure. The course starts with an overview of the Lambda Architecture and what a Message Broker is used for. The course continues to cover the Azure Event Hubs and Azure IoT Hub services used for event stream ingestion, and Azure Stream Analytics and HDInsight for integrating real-time event processing. Finally, the course finishes with an overview of a few example architectures to give a better perspective on architecting Real-Time Ingestion and Processing solutions within the Microsoft Azure cloud. This course should help in preparation for the 70-534 exam, Architecting Microsoft Azure Solutions.
In this course, students will learn how to implement and configure advanced security controls in Azure Active Directory, including Multi-Factor Authentication and Privileged Identity Management. These controls are implemented to secure user identities in Azure Active Directory and provide advanced reporting, authentication, and authorization through the Azure AD identity service.
In this hands-on course, students will learn about running SQL Server in Azure. This course will review basic Azure networking and storage using the Azure Resource Manager architecture to prepare students for building SQL Server solutions in Azure. The primary focus of this course is SQL Server cloud and hybrid-cloud solutions on Azure Infrastructure as a Service (IaaS). This course will cover best practices for deploying SQL Server on Azure Virtual Machines including standalone SQL Servers and hybrid Availability Groups. The course will look at SQL Server features that take advantage of Azure Storage such as SQL Server Managed Backup, Azure Snapshot Backups, and SQL Server data files hosted on Azure Storage.
In this module, you will focus on pricing and support models available with Microsoft to include but not limited to Azure subscriptions, planning and managing costs, support options available with Azure, and the service lifecycle in Azure.
In this module you will learn basic cloud concepts to include but not limited to the following: Why Cloud Services?, Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS), Public, Private, and Hybrid cloud models.
In this module, you will learn the basics of core services available within Microsoft Azure to include but not limited to Core Azure architectural components, Core Azure Services and Products, Azure Solutions, and Azure management tools.
In this module, you will learn about security, privacy, compliance, and trust with Microsoft Azure. You will become familiar with the following topics: securing network connectivity in Azure, core Azure identity services, security tools and features, Azure governance methodologies, monitoring and reporting in Azure, and privacy, compliance and data protection standards in Azure.
In this lab, you will learn to build powerful dashboards and reports in Power BI. You will learn to take advantage of advanced data analytics features of Power BI such as DAX queries, KPIs and R scripts.
In this lab, you will learn the basics of authoring and deploying an Azure Resource Manager (ARM) template using Visual Studio 2017 focused on infrastructure as a service (IaaS) technologies. You will author a template that deploys a virtual machine that automatically configures a web server with a sample app as well as a virtual machine with SQL Server and a database for the sample app.
In this lab, you learn the basics of authoring and deploying an Azure Resource Manager (ARM) template using Visual Studio Code, focused on Infrastructure as a Service (IaaS) technologies. You author a template that deploys a virtual machine, which gets automatically configured as a web server with a sample web app, as well as configuring a second virtual machine which gets configured with SQL Server and a database for the sample app.
In this lab, learn how to work with Azure Storage. Topics covered include: Using the Azure Portal, Azure Storage Explorer, Visual Studio 2017 and PowerShell. All aspects of Azure Storage will be explored including: Blobs, Files, Tables and Queues.
In this lab, you will create a simple URL Shortener application written in C# using Azure Functions serverless compute and the Azure Functions Tools for Visual Studio 2017. The application will make use of Azure Functions Proxies, and host the homepage of the application as a static web page in Azure Storage. The app also uses Azure Storage Tables for the backend data store for the URLs and their shortened address codes.
In this lab, you will create a new Azure Function that exposes an HTTP endpoint to enable the function to be triggered on-demand. The HTTP endpoint accepts two query string parameters from the HTTP request. The function outputs a calculated value based on the input parameters.
In this lab, you will create an Azure Data Lake Store Gen2 account. You will learn to lock down and manage access of the Data Lake Store, taking advantage of both role-based access control and Data Lake Store Azure AD integration. Finally, you will process a bulk ingest using Hadoop distcp utility.
In this lab, you will use the Azure cross-platform CLI tools (version 2.0) to learn the fundamentals of creating and managing Azure Virtual Machines.
In this lab you will create an Azure SQL Database using the Azure Portal and connect to it using SQL Server Management Studio. You will then migrate a SQL Server database hosted on a virtual machine to an Azure SQL Database.
In this lab, you will create a Linux virtual machine running in Azure, and connect to it using SSH. You will then delete the virtual machine, and clean up associated resources.
In this lab, you will create a Windows virtual machine running in Azure, and connect to it using Remote Desktop. You will then delete the virtual machine, and clean up associated resources.
Today, data is being collected in ever-increasing amounts, at ever-increasing velocities, and in an ever-expanding variety of formats. This explosion of data is colloquially known as the Big Data phenomenon.In order to gain actionable insights into big-data sources, new tools need to be leveraged that allow the data to be cleaned, analyzed, and visualized quickly and efficiently. Azure HDInsight provides a solution to this problem by making it exceedingly simple to create high-performance computing clusters provisioned with Apache Spark and members of the Spark ecosystem. Rather than spend time deploying hardware and installing, configuring, and maintaining software, you can focus on your research and apply your expertise to the data rather than the resources required to analyze that data.Apache Spark is an open-source parallel-processing platform that excels at running large-scale data analytics jobs. Spark’s combined use of in-memory and disk data storage delivers performance improvements that allow it to process some tasks up to 100 times faster than Hadoop. With Microsoft Azure, deploying Apache Spark clusters becomes significantly simpler and gets you working on your data analysis that much sooner.In this lab, you will experience HD Insight with Spark first-hand. After provisioning a Spark cluster, you will use the Microsoft Azure Storage Explorer to upload several Jupyter notebooks to the cluster. You will then use these notebooks to explore, visualize, and build a machine-learning model from food-inspection data — more than 100,000 rows of it — collected by the city of Chicago. The goal is to learn how to create and utilize your own Spark clusters, experience the ease with which they are provisioned in Azure, and, if you're new to Spark, get a working introduction to Spark data analytics.
In this lab, you will learn to build, monitor, manage and troubleshoot data pipelines with Azure Data Factory V2. You will learn to use the Copy Data wizard to build pipeline with no coding. You will build a custom pipeline to copy data from Blob storage to a table in Azure SQL Database. You will build a tumbling window pipeline to pick up data on a daily basis. Finally, you will learn to use the Management Monitoring tools to troubleshoot pipeline failures.
Learn Azure Active Directory features: In this lab you will learn the different aspects and key features of Azure Active Directory, and more specifically how it integrates in a hybrid identity solution. Note: This lab pre-deploys several resources and will take 15-20 minutes to start.
In this lab, you will learn the foundations of deploying and configuring virtual machines in Microsoft Azure. You will configure a web farm using availability sets, load balancing, and virtual machine extensions to deploy a web app. You will configure diagnostics and monitoring for the virtual machine as well as setup network security groups to lower any potential attack surface area.
In this lab, you will learn the foundations of deploying and configuring virtual machines in Microsoft Azure. You will configure a web farm using availability sets, load balancing, and virtual machine extensions to deploy a web app as well as deploy and configure a SQL Server for the web application database.
In this lab, an AKS cluster is deployed using the Azure CLI. A multi-container application consisting of web front end and a Redis instance is then run on the cluster. Once completed, the application is accessible over the internet.
In this lab, you learn about the different capabilities of Azure NetworkWatcher. The lab starts from the initial steps of enabling Azure Network Watcher in multiple Azure regions and deploying the Azure Network Watcher Virtual Machine extension to several VMs that are already deployed in your subscription. You learn how to use Azure Network Watcher Topology, you will then execute a network packet capture from the Azure Portal and PowerShell, and learn how to interpret and analyze the contents of a capture file by using different tools. Then you will move over to using IP Flow Verify and NetworkSecurity Group View features of Azure Network Watcher. In the last exercises, you will review the VPN Diagnostics capability.
In this lab, you will create an Azure Storage Account (Blobs, Tables, Queues) and access it by using a Java-based web app that uses it for storing data and images. You will be able to use the Azure Storage Explorer to examine the storage account contents while using the application to see how it works.
In this lab, an Azure Virtual Machine disk will be encrypted using the following steps:Deploy a VM into Azure that is not encryptedObtain and run the Azure Disk Encryption Prerequisites Azure PowerShell scriptEncrypt your virtual machines
In this lab, you will use AzureML to set up a model to forecast prices. We will also use R and RStudio in order to learn more R programming. Predicting the increase in sales from a number of factors is an example of regression, or you could simply call it scoring, which is a more familiar term. If you want to know how small variations in input variables affect outcome, then you likely want to use a regression method. If you’re trying to predict scores, regression is likely a good choice for this business requirement. There are different types of regression, and the selection of regression method depends on the business problem that you are trying to solve. For example, if you want to work out the probability that an object is in a given class, then you could use logistic regression, which is aimed at estimating class probabilities. In practical terms, what does that actually mean? Well, an example might be estimating the probability of fraud in a credit card purchase, where we might want to work out the probability that it is a fraudulent purchase. We are also going to use a new method to work with missing data. In the Missing Data task, the PCA option approximates the covariance for the full dataset to reconstruct the missing data. In practice, this means that AzureML will use the PCA method to ‘guess’ what the missing data will be. For each column, AzureML will add an additional column which will identify whether the data was originally missing, or whether it was present. Later on, this makes it easier to visualize the data since we can include or exclude data which was originally missing, in line with the user requirements or to promote further analysis.
In this lab, you will create a virtual network that will allow the virtual machines you create to securely connect with each other. You will then create two virtual machines and specify the virtual network configuration and the availability set configuration along with storage for the virtual machine.
In this lab, you will create an Azure Web App and a SQL Database and configure the popular content management system (CMS) Orchard CMS. You will then configure the web app to automatically scale based on actual CPU usage.
This lab is designed to help you become familiar with several features of Microsoft Azure Log Analytics. You will learn how to setup a Log Analytics workspace and install the agent on several VMs. From there, you will configure data sources from Azure as well as diagnostic data from the VMs and learn the fundamentals of querying data and events using the Log Analytics query language.
In this lab, you learn about the deploying A Test VM and configuring Azure Monitor on that VM by applying some condition and action items. If the VM reaches the defined thresholds, Azure Monitor will generate alerts.
In this lab, you will configure Azure Site Recovery to protect a sample n-tier application by configuring replication from the source Azure region to a target Azure region. Once the initial replication has completed and the application is protected, you will perform a test fail over and validate application functionality. Finally, you will accomplish the cleanup of the test failover resources.Note: This lab pre-deploys several resources and will take 15-20 minutes to start.
In this lab, you will learn how to configure a .NET application to send exception and telemetry data to Application Insights. You will also learn how to navigate the application insights UI to review the captured data as well as setup alerts.
In this lab, you will learn how to use Visual Studio Code to author an ARM Template that declares the Azure Resources necessary to host an Azure Web App, Azure SQL Database, and Azure Application Insights.
In this lab, you will be introduced to basic concepts for developing with Azure Storage using Visual Studio 2017 and C#.
In this lab, you will set up an Azure Machine Learning Studio account. You will then walk through the various features and capabilities of Azure Machine Learning Studio. You will load data from local and external sources. You will clean, manipulate and transform the data to make it usable for machine learning. Finally, you will create a binary classification model using two-class boosted decision trees to build a targeted mailing list.
In this lab, you will create, deploy, and configure an application using Java and the Azure Service Bus to demonstrate the use of messaging with queues. Your first exercise will be to create a development environment where you can create and debug Java code. After that, you will create a Service Bus queue, an Azure Function, and an Azure Cosmos DB database to demonstrate the full message cycle. The Java web application, running in Docker on your development machine, will use the Service Bus queue to communicate with the Azure function which will process the message and finally save the result into the Cosmos DB database.
In this lab, the student will learn the basics of messaging patterns between software systems and how to use the Azure Service Bus as a messaging solution.
In this lab, you will create an Azure Traffic Manager profile, and use it to distribute traffic between 3 Azure Web App endpoints deployed to different global locations. You will learn how to use the Azure portal to configure the different ways in which Traffic Manager distributes traffic between endpoints, and how to configure endpoint health checks and test endpoint failover, for high-availability applications.
In this lab, you will use Visual Studio and ASP.NET to learn how to use Cosmos DB as a backend for an MVC application. You will learn how to programmatically read and write data, create and call a user-defined functions as well as understand management capabilities such as users and permissions, monitoring and scalability options.
In this lab, you will learn the fundamentals of how to use the Azure PowerShell cmdlets to create and manage Azure Virtual Machines. Exercises will include performing common operations like stopping and starting VMs, creating VMs, attaching additional storage and creating and updating virtual machines.
In this lab, you will create 3 virtual networks in two different regions. You will configure site-to-site connectivity between the regions using a VPN Gateway. You will next configure a client machine (the lab virtual machine) to connect to one of the virtual networks using point-to-site connectivity. Finally, you will configure virtual network to virtual network connectivity using virtual network peering. This will also allow traffic from the 3rd virtual network to transit over the VPN gateway.
In this lab, you will learn how to configure and manage an Azure Cosmos DB Account (formerly Azure DocumentDB), including how to query and manage JSON documents within a Collection. Among the topics covered are using SQL language syntax to perform document queries that return JSON results, and implementing and testing global data replication and fail over.
In this lab, we will walk through management and monitoring of an Elastic Pool. First, we will create an Elastic Pool and add our databases to the pool. Then we will monitor the performance of our pool using TSQL Scripts and the Azure Portal.
In this lab, you will learn the foundations of deploying and configuring virtual machines in Microsoft Azure. You will configure a web farm using availability sets, load balancing, and virtual machine extensions to deploy a web app. You will configure diagnostics and monitoring for the virtual machine as well as setup network security groups to lower any potential attack surface area. This lab pre-provisions an environment that you will use for testing diagnostics capabilities and may take up to 30 minutes before it's ready.
In this lab, you will learn the fundamentals of configuring and managing virtual machine diagnostics and alerts as well as learn some useful troubleshooting techniques for Azure Virtual Machines.This lab pre-provisions an environment that you will use for testing diagnostics capabilities and may take up to 30 minutes before it's ready.
In this lab you will learn how to migrate an traditional three-tier web application (web, business logic, and data) from on-premises to Azure using Azure Site Recovery and Azure Database Migration Service.Note: This lab pre-deploys several resources and will take 20-30 minutes to start.
In this lab, you learn how to configure virtual networking peering.Virtual network peering enables you to seemlessly connect two Azure virtual networks. Once peered, the virtual networks appear as one, for connectivity purposes. The traffic between virtual machines in the peered virtual networks is routed through the Microsoft backbone infrastructure, much like traffic is routed between virtual machines in the same virtual network, through private IP addresses only.Note 1: This lab will connect two virtual networks within the same region. Peering across regions is currently in preview.Note 2: If you want a more in-depth view of virtual network connectivity (including site-to-site and point-to-site) try the Introduction to Virtual Network Connectivity lab.
Dashboard in a Day (DIAD) is a hands-on lab designed for Business Analysts that will take you through creating stunning reports, connecting to different data sources, and sharing data with your team mates. This lab will cover the breadth of Power BI capabilities.
In this lab, you will use Java to write a back-end console application and register it with Azure Active Directory. You will then create a Key for the Registered app, and write code to generate an Access Token for the application to use when calling the Azure AD Graph API. Code will also be written to call the Azure AD Graph REST API from within Java using the Access Token for authentication.
In this lab, you learn about deploying SQL Server on Azure virtual machines. This lab will walk you through some common setup and configuration tasks for running SQL Server in Azure infrastructure as a service.
In this lab, you will build a machine learning experiment using Azure Machine Learning. You will start by creating a Machine Learning Workspace in the Azure Portal. You will then login to ML Studio where you will import an external dataset, clean the dataset, choose a machine learning algorithm and train your model. Finally, you will score and evaluate your model to determine its accuracy.
In this lab, you learn to leverage Machine Learning Server and SQL Server Machine Learning Services to execute R code. You will use pre-installed tools of the Data Science Virtual Machine to execute Jupyter Notebooks and execute remote R code against Machine Learning Server. You will then leverage SQL Server Machine Learning Services to execute R code in SQL Server.