SonarQube is a set of static analyzers that can be used to identify areas of improvement in your code. It allows you to analyze the technical debt in your project and keep track of it in the future. With Maven and Gradle build tasks, you can run SonarQube analysis with minimal setup in a new or existing Azure DevOps Services build task.
References:
https://docs.microsoft.com/en-us/azure/devops/java/sonarqube?view=azure-devops

The basic idea behind Continuous Assurance (CA) is to setup the ability to check for "drift" from what is considered a secure snapshot of a system. Support for Continuous Assurance lets us treat security truly as a
'state' as opposed to a 'point in time' achievement. This is particularly important in today's context when
'continuous change' has become a norm.
There can be two types of drift:
* Drift involving 'baseline' configuration: This involves settings that have a fixed number of possible states (often pre-defined/statically determined ones). For instance, a SQL DB can have TDE encryption turned ON or OFF...or a Storage Account may have auditing turned ON however the log retention period may be less than 365 days.
* Drift involving 'stateful' configuration: There are settings which cannot be constrained within a finite set of well-known states. For instance, the IP addresses configured to have access to a SQL DB can be any (arbitrary) set of IP addresses. In such scenarios, usually human judgment is initially required to determine whether a particular configuration should be considered 'secure' or not. However, once that is done, it is important to ensure that there is no "stateful drift" from the attested configuration. (E.g., if, in a troubleshooting session, someone adds the IP address of a developer machine to the list, the Continuous Assurance feature should be able to identify the drift and generate notifications/alerts or even trigger 'auto-remediation' depending on the severity of the change).
Reference:
https://azsk.azurewebsites.net/04-Continous-Assurance/Readme.html

Explanation:

Step 1: Create a YAML file.
If your AKS cluster is RBAC-enabled, you must create a service account and role binding for use with Tiller.
To create a service account and role binding, create a file named rbac-virtual-kubelet.yaml Step 2: Run kubectl apply.
Apply the service account and binding with kubectl apply and specify your rbac-virtual-kubelet.yaml file.
Step 3: Run helm init.
Configure Helm to use the tiller service account:
helm init --service-account tiller
Youcan now continue to installing the Virtual Kubelet into your AKS cluster.
References:https://docs.microsoft.com/en-us/azure/aks/virtual-kubelet

Explanation:
Deployment Mode
Location specified in the Linked artifact variable

Explanation:

Box 1: microsoft.com/dotnet/sdk:2.3
The first group of lines declares from which base image we will use to build our container ontop of. If the local system does not have this image already, then docker will automatically tryand fetch it. The mcr.
microsoft.com/dotnet/core/sdk:2.1 comes packaged with the .NET core 2.1 SDK installed, so it's up to the task of building ASP .NET core projects targeting version 2.1 Box 2: dotnet restore The next instruction changes the working directory in our container to be /app, so all commands following this one execute under this context.
COPY *.csproj ./
RUN dotnet restore
Box 3: microsoft.com/dotnet/2.2-aspnetcore-runtime
When building container images, it's good practice to include only the production payload and its dependencies in the container image. We don't want the .NET core SDK included in our final image because we only need the .NET core runtime, so the dockerfile is written to use a temporary container that is packaged with the SDK called build-env to build the app.
Reference:
https://docs.microsoft.com/de-DE/virtualization/windowscontainers/quick-start/building-sample-app