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Zero Code light up Example

This example shows how to enable application insights for Kubernetes for ASP.NET Core 6.x WebAPI without code change for the existing project.

It can be accomplished in 2 steps:

  • Add the proper NuGet Package
  • Add Environment Variables

The example below shows the details.

Reference hosting startup package in Dockerfile

Add this line in the Dockerfile:

...
# Adding a reference to hosting startup package. Replace --prerelease with the target version of the package you want to use.
RUN dotnet add package Microsoft.ApplicationInsights.Kubernetes.HostingStartup --prerelease

# Light up Application Insights for Kubernetes using hosting startup.
ENV ASPNETCORE_HOSTINGSTARTUPASSEMBLIES=Microsoft.ApplicationInsights.Kubernetes.HostingStartup
...

Notes: for the environment variable of ASPNETCORE_HOSTINGSTARTUPASSEMBLIES, you could alternatively add it in Kubernetes yaml file as well. For example, in k8s.yaml.

Here's the the full Dockerfile example.

Note: To make your build context as small as possible add a .dockerignore file to your project folder.

Build and run the Docker image

  1. Open a command prompt and navigate to your project folder.

  2. Use the following commands to build and run your Docker image:

    docker build -t ai-k8s-app .
docker container rm test-ai-k8s-app -f # Making sure any existing container with the same name is deleted
docker run -d -p 8080:80 --name test-ai-k8s-app ai-k8s-app
docker logs test-ai-k8s-app

  3. Expect the error

    If you follow the steps above correctly, you shall see the following error in the beginning of the log:

    [Error] [2022-06-10T21:23:10.0412107Z] Application is not running inside a Kubernetes cluster.

    Congratulations, your image is ready to run inside the Kubernetes! The error, as a matter of fact, is a good sign that Application Insights for Kubernetes is injected and it is trying to get the Kubernetes related data. It failed only because it is running outside of the Kubernetes.

  4. Delete the running container after the verification is done:

    docker container rm test-ai-k8s-app -f

Upload the image to container registry

Once verified, the image is ready to be uploaded. Here we use docker hub for example, it works with any Docker image registry:

docker tag ai-k8s-app:latest dockeraccount/ai-k8s-app:latest
docker push dockeraccount/ai-k8s-app:latest

Note: Change the tag properly. For more details, please reference the docker document: Repositories.

Deploy the application in Kubernetes

Now that the image is in the container registry, it is time to deploy it to Kubernetes.

  • You could use default namespace, but it is recommended to put the test application in a dedicated namespace, for example 'ai-k8s-demo'. To deploy a namespace, use content in k8s-namespace.yaml:

    kubectl create -f k8s-namespace.yaml

  • Create a secret for application insights connection string

    Create & deploy a secret using the following yaml.

    apiVersion: v1
kind: Secret
metadata:
  name: app-env-secret
  namespace: ai-k8s-demo # Update to your namespace
type: Opaque
data:
  appinsights-connection-string: eW91IGhhdmUgdG8gZG8gdGhpcywgZG9uJ3QgeW91Pw==   #Base64 encoded connection string.

    Tips: Connection string can be fetched from the Azure Portal. See connection strings for more details.

    Tips: if you are going to create a file in your repository, secrets.yaml for example, adding the path to .gitignore to avoid checking it in by accident.

    For example, you may deploy it like this:

    kubectl create -f .\secrets.yaml

    Refer to Secrets for more info.

  • Setup proper role binding for RBAC enabled clusters

    If you have RBAC enabled for your cluster, permissions need to be granted to the service account to access the cluster info for telemetries. Refer to Configure RBAC permissions for details.

    For example, deploy a role assignment in namespace of ai-k8s-demo by calling:

    kubectl create -f ..\..\docs\sa-role.yaml

    The output looks like this:

    clusterrole.rbac.authorization.k8s.io/appinsights-k8s-property-reader created
    clusterrolebinding.rbac.authorization.k8s.io/appinsights-k8s-property-reader-binding created

  • Deploy the application

    Create a Kubernetes deployment file. Reference k8s.yaml as an example, pay attention to namespace, image and environment variables, making sure they are properly setup.

    Then run the following command to deploy the app:

    kubectl create -f k8s.yaml

    To learn more about Kubernetes deployment, please refer to Deployments.

  • Port forward for testing

    1. Get Pod name:

      kubectl get pod --namespace ai-k8s-demo

      Note down the pod name.

    2. Use port forward to hit your application. For example, listens locally on 8080, forward it to 80 in the pod:

      kubectl port-forward pod/<podName> 8080:80 --namespace ai-k8s-demo

      You will see output:

      Forwarding from 127.0.0.1:8080 -> 80
      Forwarding from [::1]:8080 -> 80
      Handling connection for 8080

    3. Hit the endpoint to generate some traffic. For example:

      curl http://localhost:8080/weatherforecast

      After a while (around 2 minutes), you shall see Application Insights data coming with Kubernetes properties on it.

      Application Insights Events with Kubernetes Properties

Summary

In this example, we modified the Dockerfile a bit to add the required NuGet packages into the project, then we used the environment variables to enable the feature.

We also touched the surface of using secrets to protect sensitive configurations like connection string of the application insights resource.