Courses and hands-on labs designed to help you pass Microsoft's AZ 400 Microsoft Azure DevOps Solution Certification. Learn the foundations of Azure DevOps in this complete learning path that is designed to teach you the ins-and-outs of continuous integration and deployment, pipelines, automation and much more!
This course builds on the “Introduction to ARM Templates with Visual Studio” course. In this course, you will learn about design and creation best practices, you will also learn about the various functions available when authoring ARM Templates. Other topics covered are Nested Templates, Deployment, and Troubleshooting. Throughout the course, you will walk the authoring and deployment of a multi-tier architecture defined in a single ARM Template (which is then broken into multiple nested templates).
In this course, you will learn about Microsoft Azure Resource Manager which is the deployment and management service for resources in Azure. It is the consistent layer for creating, updating, and deleting resources in an Azure Subscription. This course will explain the architecture of resource manager and take a deep dive into topics such as resource providers and resources.
This course begins by covering and explaining what DevOps is and how to apply it within an organization to build successful projects. It then dives into the core techniques and technologies that enable DevOps through Infrastructure as Code (IaC) and Automation. The technical content in this course will expose you to using technologies liks Azure CLI, Azure PowerShell, and Azure Resource Manager (ARM) Templates to perform automation, as well as tools like Git and Visual Studio Team Services (VSTS) to implement automated deployments, continuous integration (CI), and continuous delivery (CD).
In this module, you will gain the knowledge and skills to design a DevOps strategy. Students will learn how to plan for transformation, select a project, and create team structures. Students will also learn how to develop quality and security strategies. Planning for migrating and consolidating artifacts and source control will also be covered.
In this module, you will gain the knowledge and skills to deploy an application infrastructure in DevOps pipelines. Students will learn how to implement infrastructure as code and configuration management, how to provision Azure infrastructure using common automation tools, and how to deploy an application infrastructure using various Azure services and deployment methodologies. Students will also learn how to integrate 3rd party deployment tools with Azure, such as Chef and Puppet to incorporate compliance and security into the release pipeline.
In this module, you will gain the knowledge and skills to implement continuous delivery. Students will learn how to design a release strategy, set up a release management workflow, and implement an appropriate deployment pattern.
In this module, you will gain the knowledge and skills to implement continuous feedback. Students will learn how to recommend and design system feedback mechanisms, implement a process for routing system feedback to development teams, and optimize feedback mechanisms.
In this module, you will gain the knowledge and skills to implement the DevOps practices of continuous integration. Students will learn how to implement continuous integration in an Azure DevOps pipeline, how to manage code quality and security principles, and how to implement a container build strategy.
In this module, you will gain the knowledge and skills to implement dependency management. Students will learn how to design a dependency management strategy and manage security and compliance.
In this module, you will gain the knowledge and skills to implement DevOps processes. Students will learn how to use source control, scale Git for an enterprise, implement and manage build infrastructure, manage application configuration and secrets, and implement a mobile DevOps strategy.
This class introduces the students to Azure Resource Manager (ARM) templates, with a focus on how to create and deploy templates for Azure Infrastructure-as-a-Service.The course opens by explaining the advantages of using template-based deployment. Students then learn in detail how to structure a Resource Manager template, and how to create a template using Visual Studio. Template deployment is covered next, including coverage of a range of deployment options, tools, and troubleshooting tips. The course closes with an introduction to some more advanced template techniques, including loops, nested and linked templates, and how to integrate templates with Key Vault to protect secrets during deployment.Examples given in this course focus on Azure infrastructure services, including virtual machines, storage, and networking. However, the overall course content will be useful for anyone wanting to learn how to create Templates for any Azure service.
In this course, the student will be introduced to Docker. We’ll start by understanding the basics of containers and how they came to be. Then, we’ll learn how to install Docker on various platforms. We will cover the components that make up Docker including: The Docker Engine, Docker Images, and Docker Containers. We’ll cover how to containerize an application. We’ll also talk about how networking works with Docker and wrap up with a discussion of how data persistence works within the Docker ecosystem.
In this course, we will cover and introduction to Kubernetes. We will start off by covering what role Kubernetes plays in the container space and how it can simplify container orchestration. We’ll cover scaling, self-healing, load-balancing, and rolling updates. Then, we’ll cover all the ways to install Kubernetes. The remainder of the module with cover the core components of Kubernetes including: Pods, ReplicaSets, Services, and Deployments.
In this hands on course, students will learn about Microsoft Windows Containers. This course starts with an overview of Windows Container platform and its core capabilities. We will then cover use of Microsoft Nano Server and Windows Server Core inside containers. Also covered in the course is usage of Docker CLI (Command Line Interface) alongside PowerShell to perform common tasks like building container images using Dockerfile, running and removing containers. The course wraps up by looking ahead at various application frameworks like ASP.NET 4.5 / ASP.NET Core and IIS Server that are available to run inside Windows Containers.
In this course, students will learn how to deploy and manage common Azure IaaS resources using Azure PowerShell and the Azure CLI.
Welcome to the Running Containers on Azure Course! We'll start off by discussing Microsoft Azure’s managed service offerings for container technologies. We'll then discuss the Azure Container Registry and compare it to other container registry platforms. Next, we’ll go into Azure Container Instances and discuss why and when to use Azure Container Instances followed by how to persist data when running containers in Azure. Finally, we'll cover Azure Kubernetes Service and discuss the advantages that come along with a managed Kubernetes service.
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 about the agile planning and portfolio management tools and processes provided by Azure Boards and how they can help you quickly plan, manage, and track work across your entire team. You will explore the product backlog, sprint backlog, and task boards which can be used to track the flow of work during the course of an iteration.
In this lab, you will learn the basics of authoring and deploying an Azure Resource Manager (ARM) template using Visual Studio 2019 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, you will see how open source tools, such as Terraform, can be leveraged to implement Infrastructure as Code (IaC) and how to automate your infrastructure deployments in the cloud with Terraform and Azure Pipelines.
In this hands-on lab, you will learn how Trey Research can leverage Deep Learning technologies to scan through their vehicle specification documents to find compliance issues with new regulations. You will standardize the model format to ONNX and observe how this simplifies inference runtime code, enabling pluggability of different models and targeting a broad range of runtime environments and most importantly, improves inferencing speed over the native model. You will build a DevOps pipeline to coordinate retrieving the latest best model from the model registry, packaging the web application, deploying the web application and inferencing web service. After a first successful deployment, you will make updates to both the model, the and web application, and execute the pipeline once to achieve an updated deployment. You will also learn how to monitor the model’s performance after it is deployed so Trey Research can be proactive with performance issues.At the end of this hands-on lab, you will be better able to implement end-to-end solutions that fully operationalize deep learning models, inclusive of all application components that depend on the model.
In this lab we'll guide you through the steps to deploy a request splitting ambassador that will split 10% of the incoming HTTP requests to an experimental server and the rest to a primary web server using Azure Kubernetes Service (AKS). This pattern is commonly used for testing new features or user experience to a small subset of users.
In this lab, you will learn how to use the Azure PowerShell cmdlets to deploy a pre-built Azure Resource Manager template.This template leverages the PowerShell DSC Custom script extension to automatically configure the virtual machines that are defined in the template.
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 will learn about the release management features available in Azure Pipelines that automate the deployment of applications. These features help development and operations teams integrate with Team Foundation Server to configure and automate complex deployments of their automated builds to target stages more easily. Development teams can also model their release processes and track approvals, sign-offs, and visualize their release status.
In this lab, you will learn how to configure continuous integration (CI) and continuous deployment (CD) for your applications using Build and Release in Azure Pipelines. This scriptable CI/CD system is both web-based and cross-platform, while also providing a modern interface for visualizing sophisticated workflows. Although we won't demonstrate all of the cross-platform possibilities in this lab, it is important to point out that you can also build for iOS, Android, Java (using Ant, Maven, or Gradle) and Linux.
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.
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 provision an Azure Web App and App Service Plan. Then, you will configure a "Staging" Deployment Slot and deploy source code to it from a Github repository. Finally, you will perform a deployment slot swap to push the code deployment from Staging into Production.
In this lab, you will learn the fundamentals of automating Azure Web Apps using the Azure CLI tools. With the tools, you will provision an Azure Web App and App Service Plan. Then, you will configure a "Staging" Deployment Slot and deploy source code to it from a Github repository. Finally, you will perform a deployment slot swap to push the code deployment from Staging into Production.
In this this lab you will learn how to setup and configure Azure Automation to execute runbooks for common task automation. This will will teach you how to create an Azure Automation Account, configure runbook assets, setup source control, and teach you how to create and trigger runbooks via webooks for automating tasks against one or more Azure Virtual Machines.
Azure Container Instances enables deployment of Docker containers onto Azure infrastructure without provisioning any virtual machines or adopting any higher-level service. In this tutorial, you build a small web application in Node.js and package it in a container that can be run using Azure Container Instances.
In this lab, you will build and run container based on IIS Server, ASP.NET 4.5 and ASP.Net Core Frameworks. You will use Dockerfile to create container image and then use Docker CLI commands to launch thecontainers. Finally, you will work work with docker commands to access container logs and stats including CPU and memory.
In this lab, you learn how to author an Azure Resource Manager template that uses nested templates and dependencies to create an orchestrated deployment. In this example, you will deploy a Virtual Network, and then a virtual machine running Windows Server Active Directory which includes a DNS server. After the DNS service is deployed, you will update the virtual network to refer to its IP address for DNS connectivity. From there, you will deploy a client that is domain joined to validate that DNS has been updated in the correct order.
In this lab, you will use the Azure Resource Manager (ARM) REST API, via the Azure Resource Explorer, to provision and Azure Function App hosted on an App Service Plan using Consumption plan pricing. Then you will provision a new Azure Storage Account, and update it's configuration to use Read-Access Geo-Redundant Storage to replicate the data stored to a read-only, secondary Azure Region / Location.
In this lab, you will perform several maintenance operations on an existing IaaS application. All operations will be carried out by making direct calls to the Azure Resource Manager REST API, using the Resource Explorer tool. This lab will automatically provision several virtual machines and will take 15-25 minutes to fully start.
In this Lab, you will use the Nerd Dinner Application. Nerd Dinner is an Open Source ASP.NET MVC Project that helps nerds and computer people plan get-togethers. You can see the site running LIVE at http://www.nerddinner.com. You will move the application DB to Azure SQL instance and add the Docker support to the application to run the application in Azure Container Instances.
Application Insights is an extensible Application Performance Management (APM) service for web developers on multiple platforms. You can use it to monitor your live web applications and other services. It automatically detects performance anomalies, includes powerful analytics tools to help you diagnose issues, and helps you continuously improve performance and usability. It works for apps on a wide variety of platforms including .NET, Node.js and Java EE, hosted on-premises, hybrid, or any public cloud. It even integrates with your DevOps process with connection points available in a variety of development tools. It can even monitor and analyze telemetry from mobile apps by integrating with Visual Studio App Center.In this lab, you'll learn about how you can add Application Insights to an existing web application, as well as how to monitor the application via the Azure portal.
In this lab, you will learn how to make direct calls to the Azure Resource Manager REST API. There are various different tools available to make these API calls Each exercise focuses on a different tool, and on different features of the REST API.
Azure DevOps supports two types of version control, Git and Team Foundation Version Control (TFVC). Here is a quick overview of the two vesion control systems:Team Foundation Verson Control (TFVC): TFVC is a centralized version control system. Typically, team memvers have only one version of each file on their dev machines. Historical data is maintained only on the server. Branches are path-based and created on the server.Git: Git is a distributed version control system. Git repositories can live locally (such as on a developer's machine). Each developer has a copy of the source repository on their dev machine. Developers can commit each set of changes on their dev machine and perform version control operations such as a history and compare without a network connection.Git is the default version control provider for new projects. You should use Git for version control in your projects unless you have a specific need for centralized version control features in TFVC.In this lab, you will learn how to establish a local Git repository, which can easily be syncronized with a centralized Git repository in Azure DevOps. In addition, you will learn about Git branching and merging support. You will use Visual Studio Code, but the same processess apply for using any Git-compatible client with Azure DevOps.