Getting Started with Azure Continuous Deployment Pipelines

Azure continuous deployment pipelines allow you to automate the build, test, and deployment of your application to Azure, reducing manual errors and increasing deployment frequency.

You can create a pipeline in Azure DevOps by selecting the project and repository you want to use, then clicking on the "New pipeline" button.

The first step in creating a pipeline is to define a YAML file that specifies the build and deployment process, which can include tasks such as running unit tests, building the application, and deploying it to Azure.

This YAML file is where you'll specify the triggers, variables, and other settings that control how your pipeline runs.

Azure CD Components are the backbone of a successful continuous deployment pipeline. The key components include Source Control, which is typically Azure DevOps Repos or GitHub, where the application code resides.

The Build Stage is where the source code is compiled, tests are run, and build artifacts are produced. This stage is crucial in ensuring that the code is stable and ready for deployment.

Here are the key components of Azure CD Components in a concise list:

Azure CD Components are the backbone of a successful continuous delivery pipeline. The key components are Source Control, Build Stage, Release Stage, Deployment Gates, Approve Workflow, Artifacts, Release Triggers, Environment Variables, and Logs and Monitoring.

Source Control is the foundation of your pipeline, and it's where your application code lives. It can be Azure DevOps Repos or GitHub.

The Build Stage is where your source code is compiled, and tests are run. This stage produces build artifacts that are then used in the next stage.

The Release Stage is where your built artifacts are deployed to target environments such as development, staging, and production.

Deployment Gates are an optional stage where additional quality checks occur before deployment to the next stage.

Approve Workflow is a manual stage where builds are approved before being promoted to production.

Artifacts are the outputs of the Build Stage, and they're used to pass to the Release Stage for deployment.

Release Triggers automatically start a release whenever new artifacts are available.

Environment Variables are managed within the pipeline to arrange settings based on each environment.

Logs and Monitoring track the execution of the pipeline, giving you insights into failures and performance metrics.

The Modern Platform is designed for cloud-native applications, offering dynamic builds and progressive delivery. This next-generation platform is a game-changer for developers.

Platform Engineering vs DevOps highlights key differences between these two approaches. One of the main differences is that Platform Engineering focuses on building and maintaining the platform, while DevOps focuses on the development process.

CI/CD vs. DevOps explores the relationship between these two concepts. In short, CI/CD is a subset of DevOps that focuses on continuous integration and delivery.

Here are some CI/CD best practices for DevOps success:

CI/CD on AWS provides a solid foundation for building and deploying cloud-native applications. By following best practices, you can ensure a smooth and efficient development process.

Your deployment source is the location of your application code, typically a repository hosted by version control software like GitHub, BitBucket, or Azure Repos for production apps.

For development and test scenarios, the deployment source may be a project on your local machine. This allows you to work on your code without having to push it to a remote repository.

A build pipeline reads your source code from the deployment source and executes a series of steps to get the application in a runnable state. These steps can include compiling code, minifying HTML and JavaScript, running tests, and packaging components.

You can choose a build pipeline that suits your needs, such as Azure Pipelines, or execute the build pipeline locally.

Azure DevOps Pipelines provide a web interface for creating jobs containing steps necessary to produce a production artifact for your software. You can trigger processes from any external repository, including GitHub, SVN, or your local Git server.

Here are some predefined templates for build applications developed in various languages:

You can select a template that matches your language stack and customize it as needed.

Azure Continuous Deployment offers several deployment mechanisms to put your built application into the /home/site/wwwroot directory of your web app. This directory is a mounted storage location shared by all instances of your web app.

App Service supports Kudu endpoints, FTP and WebDeploy, and deployment tools like Azure Pipelines and Jenkins use one of these mechanisms. Kudu is an open-source developer productivity tool that handles continuous deployments and provides HTTP endpoints for deployment.

You can choose from these options to deploy your application. Here are the supported deployment mechanisms:

The deployment mechanism is the action used to put your built application into the /home/site/wwwroot directory of your web app. The /wwwroot directory is a mounted storage location shared by all instances of your web app.

There are three supported deployment mechanisms: Kudu endpoints, FTP and WebDeploy, and Azure Pipelines, Jenkins, and editor plugins.

Kudu endpoints provide HTTP endpoints for deployment, such as zipdeploy/. This allows for continuous deployments and is a part of the Kudu tool that runs as a separate process in Windows App Service, and as a second container in Linux App Service.

To upload files via FTP or WebDeploy, you'll need to use your site or user credentials.

Here are the supported deployment mechanisms:

These mechanisms don't go through Kudu, making them a viable option for users who don't want to use Kudu.

Using slots is a game-changer for reducing downtime during deployments. You can deploy your app to a staging environment, validate your changes, and do smoke tests before swapping with production.

To use slots effectively, you need a Standard App Service Plan tier or better. This allows you to deploy to a staging environment and warm up worker instances to match production scale.

Swapping slots eliminates downtime because it warms up the necessary worker instances. This means your app will be available to users without a break in service.

Azure DevOps provides numerous features for development teams, including source code repository, requirements management, project management, automated builds, lab management, and release management.

Continuous Integration (CI) is a key aspect of DevOps, and Azure DevOps offers built-in CI capabilities that can be integrated with popular third-party tools such as GitHub, Jenkins, and Docker.

Azure DevOps also offers scalability, automation of build, test, and deployment tasks, real-time monitoring, and customizable dashboards to track progress and identify blockages.

Automation of package configuration on release pipelines is crucial, and Azure DevOps provides a secure files feature that retrieves sensitive data, uses it for a release, and destroys it once deployed.

To automate package configuration, you can leverage the secure files feature in Azure DevOps, which retrieves sensitive data, uses it for a release, and destroys it once deployed, reducing the risk of human error and security risks.

Here are some benefits of using Azure DevOps for CI/CD:

Use DevOps to streamline your development process and automate tasks. Azure DevOps is Microsoft's end-to-end solution for development teams, providing numerous features such as source code repository, requirements management, project management, automated builds, and release management.

You can use Azure DevOps to configure a DevOps build and release pipeline to automatically build, tag, and deploy your container when new commits are pushed to your selected branch. This is done through the Deployment Center in the Azure portal.

Azure DevOps provides a secure way to manage sensitive data by using the secure files feature. This feature retrieves secure files, uses them for a release, and once it is deployed, destroys the sensitive data.

By using Azure DevOps with Octopus Deploy, you can create a powerful combination that includes source control, build/CI, and bug tracking, along with powerful release management, deployment, and runbook automation capabilities.

Here are some benefits of using Azure DevOps for CI/CD:

In DevOps and Automation, following best practices is crucial for success.

Azure CI/CD pipelines can be optimized with the right approach.

Adopting Azure CI/CD pipeline best practices will help you make the most of the tooling.

You can learn more about additional best practices in our guide to CI/CD best practices.

Boards are a crucial part of any software development project, and Azure Boards offers a robust set of tools to manage them.

Azure Boards provides native support for Scrum, Kanban, and Agile processes, making it easy to adapt to different project needs.

Configurable dashboards are also a key feature of Azure Boards, allowing you to tailor your project management to your specific needs.

Integrated reporting and calendar views are also available, giving you a clear overview of your project's progress.

Azure Boards' tools are scalable, so you can adapt to changing business needs without having to worry about your project management system.

Continuous deployment is a game-changer for ensuring smooth and efficient code deployment. It's essential to deploy code to non-production slots, such as staging, before deploying to production.

For instance, if your project follows the Gitflow design, you should continuously deploy to a staging slot for each testing, QA, and staging branch. This allows stakeholders to easily assess and test the deployed branch.

Continuous deployment should never be enabled for production slots, instead, deploy your production branch to a non-production slot and swap it in when you're ready to release.

Writing the deployment configuration is the final step in the process. This involves creating a folder named .circleci and a file named config.yml within it, where you define a deploy job that uses orbs, such as the azure-cli orb and the node orb, to deploy your function app.

The deploy job should install the Azure CLI and login with the service principal account, and then deploy the function app using the func azure functionapp publish command. This will display the function endpoint in the Deploy to Azure function App step details.

When deploying code, it's essential to continuously deploy to designated branches for testing, QA, and staging, which is known as the Gitflow design.

This allows stakeholders to easily assess and test the deployed branch. Continuous deployment should never be enabled for production, instead deploying the production branch to a non-production slot.

To automate the deployment process, a script is written to deploy the function app and continuously deploy it anytime updates are pushed to the GitHub repository.

At the root of the project, a folder named .circleci is created, containing a file named config.yml. Inside config.yml, a deploy job is defined using two orbs, the azure-cli orb and the node orb.

The node orb is used as the executor to provide a Node.js environment, while the azure-cli orb is used to install the Azure CLI and login with the service principal account.

The azure-functions-core-tools is installed using npm, and is used to deploy the function app using the func azure functionapp publish command. The function endpoint is displayed in the Deploy to Azure function App step details.

Configuration as Code is a best practice that involves writing and storing configuration data in code, rather than in traditional configuration files. This approach is especially useful for automating deployment processes.

To implement Configuration as Code, you can create a folder named .circleci at the root of your project and a file named config.yml within it. Inside config.yml, you can define a deploy job that uses orbs to provide a Node.js environment and install the Azure CLI.

The deploy job should use azure-functions-core-tools to deploy the function app using the func azure functionapp publish command. This command requires the function app name and the --javascript flag to define the project as a Node.js/JavaScript project. The function endpoint is displayed in the Deploy to Azure function App step details.

By using Configuration as Code, you can automate the deployment process and avoid exposing sensitive data to unauthorized parties. This is especially important when dealing with configuration files that contain secrets.