Explanation
Graphical user interface, text, application, chat or text message Description automatically generated

Box 1: Lead time
Lead time measures the total time elapsed from the creation of work items to their completion.
Box 2: Cycle time
Cycle time measures the time it takes for your team to complete work items once they begin actively working on them.
Box 3: Burndown
Burndown charts focus on remaining work within a specific time period.
Reference:
https://docs.microsoft.com/en-us/azure/devops/report/dashboards/velocity-guidance?view=vsts
https://docs.microsoft.com/en-us/azure/devops/report/dashboards/cycle-time-and-lead-time?view=vsts
https://docs.microsoft.com/en-us/azure/devops/report/dashboards/configure-burndown-burnup-widgets?view=vs

Explanation

You can set up a CI/CD pipeline to deploy your apps on a Kubernetes cluster with Azure DevOps by leveraging a Linux agent, Docker, and Helm.
Step 1: Create a service principle in Azure Active Directory (Azure AD) We need to assign 3 specific service principals with specific Azure Roles that need to interact with our ACR and our AKS.
Create a specific Service Principal for our Azure DevOps pipelines to be able to push and pull images and charts of our ACR.
Create a specific Service Principal for our Azure DevOps pipelines to be able to deploy our application in our AKS.
Step 2: Add a Helm package and deploy a task to the deployment pipeline This is the DevOps workflow with containers:

Step 3: Add a Docker Compose task to the deployment pipeline.
Dockerfile file is a script leveraged by Docker, composed of various commands (instructions) and arguments listed successively to automatically perform actions on a base image in order to create a new Docker image by packaging the app.
Reference:
https://cloudblogs.microsoft.com/opensource/2018/11/27/tutorial-azure-devops-setup-cicd-pipeline-kubernetes-d

Explanation
PMD is a source code analyzer. It finds common programming flaws like unused variables, empty catch blocks, unnecessary object creation, and so forth.
There is an Apache Maven PMD Plugin which allows you to automatically run the PMD code analysis tool on your project's source code and generate a site report with its results.

Explanation
https://github.com/dotnet/dotnet-docker/blob/master/samples/dotnetapp/README.md

Explanation
In Azure Automation State Configuration, the Desired State Configuration (DSC) configuration files are used to define the desired state of resources on a system. The structure of the code blocks in a DSC configuration file should be organized in a logical and meaningful way.
One way to structure the code blocks is as follows:
* Configuration: This block defines the overall configuration, including any parameters that are used in the configuration.
* Node: This block defines the target node(s) for the configuration, typically specified by the hostname or IP address of the target system.
* Resource: This block defines the resources that are managed by the configuration, including the resource type, module, and properties.
"A configuration script consists of the following parts:
The Configuration block. This is the outermost script block. You define it by using the Configuration keyword and providing a name. In this case, the name of the configuration is MyDscConfiguration.
One or more Node blocks. These define the nodes (computers or VMs) that you are configuring. In the above configuration, there is one Node block that targets a computer named TEST-PC1. The Node block can accept multiple computer names.
One or more resource blocks. This is where the configuration sets the properties for the resources that it is configuring. In this case, there are two resource blocks, each of which call the WindowsFeature resource."
https://docs.microsoft.com/en-us/powershell/dsc/configurations/configurations?view=dsc-1.1#configuration-synt