Draft 2 and Ingress with Web Application Routing

If you read the previous article on Draft 2, we went from source code to deployed application in a few steps:

  • az aks draft create: creates a Dockerfile and Kubernetes manifests (deployment and service manifests)
  • az aks draft setup-gh: setup GitHub OIDC
  • az aks draft generate-workflow: create a GitHub workflow that builds and pushes the container image and deploys the application to Kubernetes

If you answer the questions from the commands above correctly, you should be up and running fairly quickly! ๐Ÿš€

The manifests default to a Kubernetes service that uses the type LoadBalancer to configure an Azure public load balancer to access your app. But maybe you want to test your app with TLS and you do not want to configure a certificate in your container image? That is where the ingress configuration comes in.

You will need to do two things:

  • Configure web application routing: configures Ingress Nginx Controller and relies on Open Service Mesh (OSM) and the Secret Store CSI Driver for Azure Key Vault. That way, you are shielded from having to do all that yourself. I did have some issues with web application routing as described below.
  • Use az aks draft update to configure the your service to work with web application routing; this command will ask you for two things:
    • the hostname for your service: you decide this but the name should resolve to the public IP of the Nginx Ingress Controller installed by web application routing
    • a URI to a certificate on Azure Key Vault: you will need to deploy a Key Vault and upload or create the certificate

Configure web application routing

Although it should be supported, I could not enable the add-on on one of my existing clusters. On another one, it did work. I decided to create a new cluster with the add-on by running the following command:

az aks create --resource-group myResourceGroup --name myAKSCluster --enable-addons web_application_routing

โš ๏ธ Make sure you use the most recent version of the Azure CLI aks-preview extension.

On my cluster, that gave me a namespace app-routing-system with two pods:

Nginx in app-routing-system

Although the add-on should also install Secrets Store CSI Driver, Open Service Mesh, and External DNS, that did not happen in my case. I installed the first two from the portal. I did not bother installing External DNS.

Enabling OSM
Enabling secret store CSI driver

Create a certificate

I created a Key Vault in the same resource group as my AKS cluster. I configured the access policies to use Azure RBAC (role-based access control). It did not work with the traditional access policies. I granted myself and the identity used by web application routing full access:

Key Vault Administrator for myself and the user-assigned managed id of web app routing add-on

You need to grant the user-assigned managed identity of web application routing access because a SecretProviderClass will be created automatically for that identity. The Secret Store CSI Driver uses that SecretProviderClass to grab a certificate from Key Vault and generate a Kubernetes secret for it. The secret will later be used by the Kubernetes Ingress resource to encrypt HTTP traffic. How you link the Ingress resource to the certificate is for a later step.

Now, in Key Vault, generate a certificate:

In Key Vault, click Certificates and create a new one

Above, I use nip.io with the IP address of the Ingress Controller to generate a name that resolves to the IP. For example, will resolve to Try it with ping. It’s truly a handy service. Use kubectl get svc -n app-routing-system to find the Ingress Controller public (external) IP.

Now we have everything in place for draft to modify our Kubernetes service to use the ingress controller and certificate.

Using az aks draft update

Back on your machine, in the repo that you used in the previous article, run az aks draft update. You will be asked two questions:

  • Hostname: use <IP Address of Nginx>.nip.io (same as in the common name of the cert without CN=)
  • URI to the certificate in Key Vault: you can find the URI in the properties of the certificate
There will be a copy button at the right of the certificate identifier

Draft will now update your service to something like:

apiVersion: v1
kind: Service
    kubernetes.azure.com/ingress-host: IPADDRESS.nip.io
    kubernetes.azure.com/tls-cert-keyvault-uri: https://kvdraft.vault.azure.net/certificates/mycert/IDENTIFIER
  creationTimestamp: null
  name: super-api
  - port: 80
    protocol: TCP
    targetPort: 8080
    app: super-api
  type: ClusterIP
  loadBalancer: {}

The service type is now ClusterIP. The annotations will be used for several things:

  • to create a placeholder deployment that mounts the certificate from Key Vault in a volume AND creates a secret from the certificate; the Secret Store CSI Driver always needs to mount secrets and certs in a volume; rather than using your application pod, they use a placeholder pod to create the secret
  • to create an Ingress resource that routes to the service and uses the certificate in the secret created via the placeholder pod
  • to create an IngressBackend resource in Open Service Mesh

In my default namespace, I see two pods after deployment:

the placeholder pod starts with keyvault and creates the secret; the other pod is my app

Note that above, I actually used a Helm deployment instead of a manifest-based deployment. That’s why you see release-name in the pod names.

The placeholder pod creates a csi volume that uses a SecretProviderClass to mount the certificate:


The SecretProviderClass references your Key Vault and managed identity to access the Key Vault:

spec of SecretProviderClass

If you have not assigned the correct access policy on Key Vault for the userAssignedIdentityID, the certificate cannot be retrieved and the pod will not start. The secret will not be created either.

I also have a secret with the cert inside:

Secret created by Secret Store CSI Driver; referenced by the Ingress

And here is the Ingress:

Ingress; note it says 8080 instead of the service port 80; do not change it! Never mind the app. in front of the IP; your config will not have that if you followed the instructions

All of this gets created for you but only after running az aks draft update and when you commit the changes to GitHub, triggering the workflow.

Did all this work smoothly from the first time?

The short answer is NO! ๐Ÿ˜‰At first I thought Draft would take care of installing the Ingress components for me. That is not the case. You need to install and configure web application routing on your cluster and configure the necessary access rights.

I also thought web application routing would install and configure Open Service Mesh and Secret Store CSI driver. That did not happen although that is easily fixed by installing them yourself.

I thought there would be some help with certificate generation. That is not the case. Generating a self-signed certificate with Key Vault is easy enough though.

Once you have web application routing installed and you have a Key Vault and certificate, it is simple to run az aks draft update. That changes your Kubernetes service definition. After pushing that change to your repo, the updated service with the web application routing annotations can be deployed.

I got some 502 Bad Gateway errors from Nginx at first. I removed the OSM-related annotations from the Ingress object and tried some other things. Finally, I just redeployed the entire app and then it just started working. I did not spend more time trying to find out why it did not work from the start. The fact that Open Service Mesh is used, which has extra configuration like IngressBackends, will complicate troubleshooting somewhat. Especially if you have never worked with OSM, which is what I expect for most people.


Although this looks promising, it’s all still a bit rough around the edges. Adding OSM to the mix makes things somewhat more complicated.

Remember that all of this is in preview and we are meant to test drive it and provide feedback. However, I fear that, because of the complexity of Kubernetes, these tools will never truly make it super simple to get started as a developer. It’s just a tough nut to crack!

My own point of view here is that Draft v2 without az aks draft update is very useful. In most cases though, it’s enough to use standard Kubernetes services. And if you do need an ingress controller, most are easy to install and configure, even with TLS.

Trying out Draft 2 on AKS

Sadly no post about good Belgian beer ๐Ÿบ.

Draft 2 is an open-source project that aims ๐ŸŽฏ to make things easier for developers that build Kubernetes applications. It can improve the inner dev loop, where the developers code and test their apps, in the following ways:

  • Automate the creation of a Dockerfile
  • Automate the creation of Kubernetes manifests, Helm charts, or Kustomize configs
  • Generate a GitHub Action workflow to build and deploy the application when you push changes

I have worked with Draft 1 in the past, and it worked quite well. Now Microsoft has integrated Draft 2 in the Azure CLI to make it part of the Kubernetes on Azure experience. A big difference with Draft 1 is that Draft 2 makes use of GitHub Actions (Wait? No Azure DevOps? ๐Ÿ˜ฒ) to build and push your images to the development cluster. It uses GitHub OpenID Connect (OIDC) for Azure authentication.

That is quite a change and lots of bits and pieces that have to be just right. Make sure you know about Azure AD App Registrations, GitHub, GitHub Actions, Docker, etc… when the time comes to troubleshoot.

Let’s see what we can do? ๐Ÿ‘€


At this point in time (June 2022), Draft for Azure Kubernetes Service is in preview. Draft itself can be found here: https://github.com/Azure/draft

The only thing you need to do is to install or upgrade the aks-preview extension:

az extension add --name aks-preview --upgrade

Next, type az aks draft -h to check if the command is available. You should see the following options:


We will look at the first four commands in this post.

Running draft create

With az aks draft create, you can generate a Dockerfile for your app, Kubernetes manifests, Helm charts, and Kustomize configurations. You should fork the following repository and clone it to your machine: https://github.com/gbaeke/draft-super

After cloning it, cd into draft-super and run the following command (requires go version 1.16.4 or higher):

CGO_ENABLED=0 go build -installsuffix 'static' -o app cmd/app/*

The executable runs a web server on port 8080 by default. If that conflicts with another app on your system set the port with the port environment variable: run PORT=9999 ./app instead of just ./app. Now we know the app works, we need a Dockerfile to containerize it.

You will notice that there is no Dockerfile. Although you could create one manually, you can use draft for this. Draft will try to recognize your code and generate the Dockerfile. We will keep it simple and just create Kubernetes manifests. When you run draft without parameters, it will ask you what you want to create. You can also use parameters to specify what you want, like a Helm chart or Kustomize configs. Run the command below:

az aks draft create

The above command will download the draft CLI for your platform and run it for you. It will ask several questions and display what it is doing.

[Draft] --- Detecting Language ---
โœ” yes
[Draft] --> Draft detected Go Checksums (72.289458%)

[Draft] --> Could not find a pack for Go Checksums. Trying to find the next likely language match...
[Draft] --> Draft detected Go (23.101180%)

[Draft] --- Dockerfile Creation ---
Please Enter the port exposed in the application: 8080
[Draft] --> Creating Dockerfile...

[Draft] --- Deployment File Creation ---
โœ” manifests
Please Enter the port exposed in the application: 8080
Please Enter the name of the application: super-api
[Draft] --> Creating manifests Kubernetes resources...

[Draft] Draft has successfully created deployment resources for your project ๐Ÿ˜ƒ
[Draft] Use 'draft setup-gh' to set up Github OIDC.

In your folder you will now see extra files and folders:

  • A manifests folder with two files: deployment.yaml and service.yaml
  • A Dockerfile

The manifests are pretty basic and just get things done:

  • create a Kubernetes deployment that deploys 1 pod
  • create a Kubernetes service of type LoadBalancer; that gives you a public IP to reach the app

The app name and port you specified after running az aks draft create is used to create the deployment and service.

The Dockerfile looks like the one below:

FROM golang

WORKDIR /go/src/app
COPY . .

RUN go mod vendor
RUN go build -v -o app  
RUN mv ./app /go/bin/

CMD ["app"]

This is not terribly optimized but it gets the job done. I would highly recommend using a two-stage Dockerfile that results in a much smaller image based on alpine, scratch, or distroless (depending on your programming language).

For my code, the Dockerfile will not work because the source files are not in the root of the repo. Draft cannot know everything. Replace the line that says RUN go build -v -o app with RUN CGO_ENABLED=0 go build -installsuffix 'static' -o app cmd/app/*

To check that the Dockerfile works, if you have Docker installed, run docker build -t draft-super . It will take some time for the base Golang image to be pulled and to download all the dependencies of the app.

When the build is finished, run docker run draft-super to check. The container should run properly.

The az aks draft create command did a pretty good job detecting the programming language and creating the Dockerfile. As we have seen, minor adjustments might be required and the Dockerfile will probably not be production-level quality.

GitHub OIDC setup

At the end of the create command, draft suggested using setup-gh to setup GitHub. Let’s run that command:

az aks draft setup-gh

Draft will ask for the name of an Azure AD app registration to create. Make sure you are allowed to create those. I used draft-super for the name. Draft will also ask you to confirm the Azure subscription ID and a name of a resource group.

โš ๏ธAlthough not entirely clear from the question, use the resource group of your AKS cluster (not the MC_ group that contains your nodes!). The setup-gh command will grant the service principal that it creates the Contributor role on the group. This ensures that the GitHub Action azure/aks-set-context@v2.0 works.

Next, draft will ask for the GitHub organization and repo. In my case, that was gbaeke/draft-super. Make sure you have admin access to the repo. GitHub secrets will need to be created. When completed, you should see something like below:

Enter app registration name: draft-super
Enter resource group name: rg-aks
โœ” Enter github organization and repo (organization/repoName): gbaeke/draft-superโ–ˆ
[Draft] Draft has successfully set up Github OIDC for your project ๐Ÿ˜ƒ
[Draft] Use 'draft generate-workflow' to generate a Github workflow to build and deploy an application on AKS.

Draft has done several things:

  • created an app registration (check Azure AD)
  • the app registration has federated credentials configured to allow a GitHub workflow to request an Azure AD token when you do pull requests, or push to main or master
  • secrets in your GitHub repo:AZURE_CLIENT_ID, AZURE_SUBSCRIPTION_ID,AZURE_TENANT_ID; these secrets are used by the workflow to request a token from Azure AD using federated credentials
  • granted the app registration contributor role on the resource group that you specified; that is why you should use the resource group of AKS!

The GitHub workflow you will create in the next step will use the OIDC configuration to request an Azure AD token. The main advantage of this is that you do not need to store Azure secrets in GitHub. The action that does the OIDC-based login is azure/login@v1.4.3.

Draft is now ready to create a GitHub workflow.

Creating the GitHub workflow

Use az aks draft generate-workflow to create the workflow file. This workflow needs the following information as shown below:

Please enter container registry name: draftsuper767
โœ” Please enter container name: draft-superโ–ˆ
Please enter cluster resource group name: rg-aks
Please enter AKS cluster name: clu-git
Please enter name of the repository branch to deploy from, usually main: master
[Draft] --> Generating Github workflow
[Draft] Draft has successfully generated a Github workflow for your project ๐Ÿ˜ƒ

โš ๏ธ Important: use the short name of ACR. Do not append azurecr.io!

โš ๏ธ The container registry needs to be created. Draft does not do that. For best results, create the ACR in the resource group of the AKS cluster because that ensures the service principal created earlier has access to ACR to build images and to enable admin access.

Draft has now created the workflow. As expected, it lives in the .github/workflows local folder.

The workflow runs the following actions:

  • Login to Azure using only the client, subscription, and tenant id. No secrets required! ๐Ÿ‘ OIDC in action here!
  • Run az acr build to build the container image. The image is not built on the GitHub runner. The workflow expects ACR to be in the AKS resource group.
  • Get a Kubernetes context to our AKS cluster and create a secret to allow pulling from ACR; it will also enable the admin user on ACR
  • Deploy the application with the Azure/k8s-deploy@v3.1 action. It uses the manifests that were generated with az aks draft create but modifies the image and tag to match the newly built image.

Now it is time to commit our code and check the workflow result:

Looks fine at first glance…

Houston, we have a problem ๐Ÿš€

For this blog post, I was working in a branch called draft, not main or master. I also changed the workflow file to run on pushes to the draft branch. Of course, the federated tokens in our app registration are not configured for that branch, only master and main. You have to be specific here or you will not get a token. This is the error on GitHub:


To fix this, just modify the app registration and run the workflow again:

Quick and dirty fix: update mainfic with a subject identifier for draft; you can also add a new credential

After running the workflow again, if buildImage fails, check that ACR is in the AKS resource group and that the service principal has Contributor access to the group. I ran az role assignment list -g rg-aks to see the directly assigned roles and checked that the principalName matched the client ID (application ID) of the draft-super app registration.

If you used the FQDN of ACR instead of just the short name. you can update the workflow environment variable accordingly:

ACR name should be the short name

After this change, the image build should be successful.

Looking better

If you used the wrong ACR name, the deploy step will fail. The image property in deployment.yaml will be wrong. Make the following change in deployment.yaml:

- image: draftsuper767.azurecr.io.azurecr.io/draft-super


- image: draftsuper767.azurecr.io/draft-super

Commit to re-run the workflow. You might need to cancel the previous one because it uses kubectl rollout to check the health of the deployment.

And finally, we have a winner…


In k9s:

super-api deployed to default namespace

You can now make changes to your app and commit your changes to GitHub to deploy new versions or iterations of your app. Note that any change will result in a new image build.

What about the az aks draft up command? It simply combines the setup of GitHub OIDC and the creation of the workflow. So basically, all you ever need to do is:

  • create a resource group
  • deploy AKS to the resource group
  • deploy ACR to the resource group
  • Optionally run az aks update -n -g --attach-acr (this gives the kubelet on each node access to ACR; as we have seen, draft can also create a pull secret)
  • run az aks draft create followed by az aks draft up


When working with Draft 2, ensure you first deploy an AKS cluster and Azure Container Registry in the same resource group. You need the Owner role because you will change role-based access control settings.

During OIDC setup, when asked for a resource group, type the AKS resource group. Draft will ensure the service principal it creates, has proper access to the resource group. With that access, it will interact with ACR and log on to AKS.

When asked for the ACR name, use the short name. Do not append azurecr.io! From that point on, it should be smooth sailing! โ›ต

In a follow-up post, we will take a look at the draft update command.

Quick Guide to Flux v2 on AKS

Now that the Flux v2 extension for Azure Kubernetes Service and Azure Arc is generally available, let’s do a quick guide on the topic. A Quick Guide, at least on this site ๐Ÿ˜‰, is a look at the topic from a command-line perspective for easy reproduction and evaluation.

This Quick Guide is also on GitHub.


You need the following to run the commands:

  • An Azure subscription with a deployed AKS cluster; a single node will do
  • Azure CLI and logged in to the subscription with owner access
  • All commands run in bash, in my case in WSL 2.0 on Windows 11
  • kubectl and a working kube config (use az aks get-credentials)

Step 1: Register AKS-ExtensionManager and configure Azure CLI

Flux v2 is installed via an extension. The extension takes care of installing Flux controllers in the cluster and keeping them up-to-date when there is a new version. For extensions to work with AKS, you need to register the AKS-ExtensionManager feature in the Microsoft.ContainerService namespace.

# register the feature
az feature register --namespace Microsoft.ContainerService --name AKS-ExtensionManager

# after a while, check if the feature is registered
# the command below should return "state": "Registered"
az feature show --namespace Microsoft.ContainerService --name AKS-ExtensionManager | grep Registered

# ensure you run Azure CLI 2.15 or later
# the command will show the version; mine showed 2.36.0
az version | grep '"azure-cli"'

# register the following providers; if these providers are already
# registered, it is safe to run the commands again

az provider register --namespace Microsoft.Kubernetes
az provider register --namespace Microsoft.ContainerService
az provider register --namespace Microsoft.KubernetesConfiguration

# enable CLI extensions or upgrade if there is a newer version
az extension add -n k8s-configuration --upgrade
az extension add -n k8s-extension --upgrade

# check your Azure CLI extensions
az extension list -o table

Step 2: Install Flux v2

We can now install Flux v2 on an existing cluster. There are two types of clusters:

  • managedClusters: AKS
  • connectedClusters: Azure Arc-enabled clusters

To install Flux v2 on AKS and check the configuration, run the following commands:


# list installed extensions
az k8s-extension list -g $RG -c $CLUSTER -t managedClusters

# install flux; note that the name (-n) is a name you choose for
# the extension instance; the command will take some time
# this extension will be installed with cluster-wide scope

az k8s-extension create -g $RG -c $CLUSTER -n flux --extension-type microsoft.flux -t managedClusters --auto-upgrade-minor-version true

# list Kubernetes namespaces; there should be a flux-system namespace
kubectl get ns

# get pods in the flux-system namespace
kubectl get pods -n flux-system

The last command shows all the pods in the flux-system namespace. If you have worked with Flux without the extension, you will notice four familiar pods (deployments):

  • Kustomize controller: installs manifests (.yaml files) from configured sources, optionally using kustomize
  • Helm controller: installs Helm charts
  • Source controller: configures sources such as git or Helm repositories
  • Notification controller: handles notifications such as those sent to Teams or Slack

Microsoft adds two other services:

  • Flux config agent: communication with the data plane (Azure); reports back information to Azure about the state of Flux such as reconciliations
  • Flux configuration controller: manages Flux on the cluster; checks for Flux Configurations that you create with the Azure CLI

Step 3: Create a Flux configuration

Now that Flux is installed, we can create a Flux configuration. Note that Flux configurations are not native to Flux. A Flux configuration is an abstraction, created by Microsoft, that configures Flux sources and customizations for you. You can create these configurations from the Azure CLI. The configuration below uses a git repository https://github.com/gbaeke/gitops-flux2-quick-guide. It is a fork of https://github.com/Azure/gitops-flux2-kustomize-helm-mt.

โš ๏ธ In what follows, we create a Flux configuration based on the Microsoft sample repo. If you want to create a repo and resources from scratch, see the Quick Guides on GitHub.

# create the configuration; this will take some time
az k8s-configuration flux create -g $RG -c $CLUSTER \
  -n cluster-config --namespace cluster-config -t managedClusters \
  --scope cluster \
  -u https://github.com/gbaeke/gitops-flux2-quick-guide \
  --branch main  \
  --kustomization name=infra path=./infrastructure prune=true \
  --kustomization name=apps path=./apps/staging prune=true dependsOn=["infra"]

# check namespaces; there should be a cluster-config namespace
kubectl get ns

# check the configuration that was created in the cluster-config namespace
# this is a resource of type FluxConfig
# in the spec, you will find a gitRepository and two kustomizations

kubectl get fluxconfigs cluster-config -o yaml -n cluster-config

# the Microsoft flux controllers create the git repository source
# and the two kustomizations based on the flux config created above
# they also report status back to Azure

# check the git repository; this is a resource of kind GitRepository
# the Flux source controller uses the information in this
# resource to download the git repo locally

kubectl get gitrepo cluster-config -o yaml -n cluster-config

# check the kustomizations
# the infra kustomization uses folder ./infrastructure in the
# git repository to install redis and nginx with Helm charts
# this kustomization creates other Flux resources such as
# Helm repos and Helm Releases; the Helm Releases are used
# to install nginx and redis with their respective Helm
# charts

kubectl get kustomizations cluster-config-infra -o yaml -n cluster-config

# the app kustomization depends on infra and uses the ./apps
# folder in the repo to install the podinfo application via
# a kustomize overlay (staging)

kubectl get kustomizations cluster-config-apps -o yaml -n cluster-config

In the portal, you can check the configuration:

Flux config in the Azure Portal

The two kustomizations that you created, create other configuration objects such as Helm repositories and Helm releases. They too can be checked in the portal:

Configuration objects in the Azure Portal


With the Flux extension, you can install Flux on your cluster and keep it up-to-date. The extension not only installs the Flux open source components. It also installs Microsoft components that enable you to create Flux Configurations and report back status to the portal. Flux Configurations are an abstraction on top of Flux, that makes adding sources and kustomizations easier and more integrated with Azure.

Quick Guide to Azure Container Apps

Now that Azure Container Apps (ACA) is generally available, it is time for a quick guide. These quick guides illustrate how to work with a service from the command line and illustrate the main features.


  • All commands are run from bash in WSL 2 (Windows Subsystem for Linux 2 on Windows 11)
  • Azure CLI and logged in to an Azure subscription with an Owner role (use az login)
  • ACA extension for Azure CLI: az extension add --name containerapp --upgrade
  • Microsoft.App namespace registered: az provider register --namespace Microsoft.App; this namespace is used since March
  • If you have never used Log Analytics, also register Microsoft.OperationalInsights: az provider register --namespace Microsoft.OperationalInsights
  • jq, curl, sed, git

With that out of the way, let’s go… ๐Ÿš€

Step 1: Create an ACA environment

First, create a resource group, Log Analytics workspace, and the ACA environment. An ACA environment runs multiple container apps and these apps can talk to each other. You can create multiple environments, for example for different applications or customers. We will create an environment that will not integrate with an Azure Virtual Network.

LA=la-aca # log analytics workspace name

# create the resource group
az group create --name $RG --location $LOCATION

# create the log analytics workspace
az monitor log-analytics workspace create \
  --resource-group $RG \
  --workspace-name $LA

# retrieve workspace ID and secret
LA_ID=`az monitor log-analytics workspace show --query customerId -g $RG -n $LA -o tsv | tr -d '[:space:]'`

LA_SECRET=`az monitor log-analytics workspace get-shared-keys --query primarySharedKey -g $RG -n $LA -o tsv | tr -d '[:space:]'`

# check workspace ID and secret; if empty, something went wrong
# in previous two steps
echo $LA_ID

# create the ACA environment; no integration with a virtual network
az containerapp env create \
  --name $ENVNAME \
  --resource-group $RG\
  --logs-workspace-id $LA_ID \
  --logs-workspace-key $LA_SECRET \
  --location $LOCATION \
  --tags env=test owner=geert

# check the ACA environment
az containerapp env list -o table

Step 2: Create a front-end container app

The front-end container app accepts requests that allow users to store some data. Data storage will be handled by a back-end container app that talks to Cosmos DB.

The front-end and back-end use Dapr. This does the following:

  • Name resolution: the front-end can find the back-end via the Dapr Id of the back-end
  • Encryption: traffic between the front-end and back-end is encrypted
  • Simplify saving state to Cosmos DB: using a Dapr component, the back-end can easily save state to Cosmos DB without getting bogged down in Cosmos DB specifics and libraries

Check the source code on GitHub. For example, the code that saves to Cosmos DB is here.

For a container app to use Dapr, two parameters are needed:

  • –enable-dapr: enables the Dapr sidecar container next to the application container
  • –dapr-app-id: provides a unique Dapr Id to your service
DAPRID=frontend # could be different
IMAGE="ghcr.io/gbaeke/super:1.0.5" # image to deploy
PORT=8080 # port that the container accepts requests on

# create the container app and make it available on the internet
# with --ingress external; the envoy proxy used by container apps
# will proxy incoming requests to port 8080

az containerapp create --name $APPNAME --resource-group $RG \
--environment $ENVNAME --image $IMAGE \
--min-replicas 0 --max-replicas 5 --enable-dapr \
--dapr-app-id $DAPRID --target-port $PORT --ingress external

# check the app
az containerapp list -g $RG -o table

# grab the resource id of the container app
APPID=$(az containerapp list -g $RG | jq .[].id -r)

# show the app via its id
az containerapp show --ids $APPID

# because the app has an ingress type of external, it has an FQDN
# let's grab the FQDN (fully qualified domain name)
FQDN=$(az containerapp show --ids $APPID | jq .properties.configuration.ingress.fqdn -r)

# curl the URL; it should return "Hello from Super API"
curl https://$FQDN

# container apps work with revisions; you are now at revision 1
az containerapp revision list -g $RG -n $APPNAME -o table

# let's deploy a newer version

# use update to change the image
# you could also run the create command again (same as above but image will be newer)
az containerapp update -g $RG --ids $APPID --image $IMAGE

# look at the revisions again; the new revision uses the new
# image and 100% of traffic
# NOTE: in the portal you would only see the last revision because
# by default, single revision mode is used; switch to multiple 
# revision mode and check "Show inactive revisions"

az containerapp revision list -g $RG -n $APPNAME -o table

Step 3: Deploy Cosmos DB

We will not get bogged down in Cosmos DB specifics and how Dapr interacts with it. The commands below create an account, database, and collection. Note that I switched the write replica to eastus because of capacity issues in westeurope at the time of writing. That’s ok. Our app will write data to Cosmos DB in that region.

LOCATION=useast # changed because of capacity issues in westeurope at the time of writing

# create the account; will take some time
az cosmosdb create \
  --name aca-$uniqueId \
  --resource-group $RG \
  --locations regionName=$LOCATION \
  --default-consistency-level Strong

# create the database
az cosmosdb sql database create \
  -a aca-$uniqueId \
  -g $RG \
  -n aca-db

# create the collection; the partition key is set to a 
# field in the document called partitionKey; Dapr uses the
# document id as the partition key
az cosmosdb sql container create \
  -a aca-$uniqueId \
  -g $RG \
  -d aca-db \
  -n statestore \
  -p '/partitionKey' \
  --throughput 400

Step 4: Deploy the back-end

The back-end, like the front-end, uses Dapr. However, the back-end uses Dapr to connect to Cosmos DB and this requires extra information:

  • a Dapr Cosmos DB component
  • a secret with the connection string to Cosmos DB

Both the component and the secret are defined at the Container Apps environment level via a component file.

# grab the Cosmos DB documentEndpoint
ENDPOINT=$(az cosmosdb list -g $RG | jq .[0].documentEndpoint -r)

# grab the Cosmos DB primary key
KEY=$(az cosmosdb keys list -g $RG -n aca-$uniqueId | jq .primaryMasterKey -r)

# update variables, IMAGE and PORT are the same
DAPRID=backend # could be different

# create the Cosmos DB component file
# it uses the ENDPOINT above + database name + collection name
# IMPORTANT: scopes is required so that you can scope components
# to the container apps that use them

cat << EOF > cosmosdb.yaml
componentType: state.azure.cosmosdb
version: v1
- name: url
  value: "$ENDPOINT"
- name: masterkey
  secretRef: cosmoskey
- name: database
  value: aca-db
- name: collection
  value: statestore
- name: cosmoskey
  value: "$KEY"

# create Dapr component at the environment level
# this used to be at the container app level
az containerapp env dapr-component set \
    --name $ENVNAME --resource-group $RG \
    --dapr-component-name cosmosdb \
    --yaml cosmosdb.yaml

# create the container app; the app needs an environment 
# variable STATESTORE with a value that is equal to the 
# dapr-component-name used above
# ingress is internal; there is no need to connect to the backend from the internet

az containerapp create --name $APPNAME --resource-group $RG \
--environment $ENVNAME --image $IMAGE \
--min-replicas 1 --max-replicas 1 --enable-dapr \
--dapr-app-port $PORT --dapr-app-id $DAPRID \
--target-port $PORT --ingress internal \
--env-vars STATESTORE=cosmosdb

Step 5: Verify end-to-end connectivity

We will use curl to call the following endpoint on the front-end: /call. The endpoint expects the following JSON:

 "appId": <DAPR Id to call method on>,
 "method": <method to call>,
 "httpMethod": <HTTP method to use e.g., POST>,
 "payload": <payload with key and data field as expected by Dapr state component>

As you have noticed, both container apps use the same image. The app was written in Go and implements both the /call and /savestate endpoints. It uses the Dapr SDK to interface with the Dapr sidecar that Azure Container Apps has added to our deployment.

To make the curl commands less horrible, we will use jq to generate the JSON to send in the payload field. Do not pay too much attention to the details. The important thing is that we save some data to Cosmos DB and that you can use Cosmos DB Data Explorer to verify.

# create some string data to send
STRINGDATA="'$(jq --null-input --arg appId "backend" --arg method "savestate" --arg httpMethod "POST" --arg payload '{"key": "mykey", "data": "123"}' '{"appId": $appId, "method": $method, "httpMethod": $httpMethod, "payload": $payload}' -c -r)'"

# check the string data (double quotes should be escaped in payload)
# payload should be a string and not JSON, hence the quoting

# call the front end to save some data
# in Cosmos DB data explorer, look for a document with id 
# backend||mykey; content is base64 encoded because 
# the data is not json

echo curl -X POST -d $STRINGDATA https://$FQDN/call | bash

# create some real JSON data to save; now we need to escape the
# double quotes and jq will add extra escapes
JSONDATA="'$(jq --null-input --arg appId "backend" --arg method "savestate" --arg httpMethod "POST" --arg payload '{"key": "myjson", "data": "{\"name\": \"geert\"}"}' '{"appId": $appId, "method": $method, "httpMethod": $httpMethod, "payload": $payload}' -c -r)'"

# call the front end to save the data
# look for a document id backend||myjson; data is json

echo curl -v -X POST -d $JSONDATA https://$FQDN/call | bash

Step 6: Check the logs

Although you can use the Log Stream option in the portal, let’s use the command line to check the logs of both containers.

# check frontend logs
az containerapp logs show -n frontend -g $RG

# I want to see the dapr logs of the container app
az containerapp logs show -n frontend -g $RG --container daprd

# if you do not see log entries about our earlier calls, save data again
# the log stream does not show all logs; log analytics contains more log data
echo curl -v -X POST -d $JSONDATA https://$FQDN/call | bash

# now let's check the logs again but show more earlier logs and follow
# there should be an entry method with custom content; that's the
# result of saving the JSON data

az containerapp logs show -n frontend -g $RG --tail 300 --follow

Step 7: Use az containerapp up

In the previous steps, we used a pre-built image stored in GitHub container registry. As a developer, you might want to quickly go from code to deployed container to verify if it all works in the cloud. The command az containerapp up lets you do that. It can do the following things automatically:

  • Create an Azure Container Registry (ACR) to store container images
  • Send your source code to ACR and build and push the image in the cloud; you do not need Docker on your computer
  • Alternatively, you can point to a GitHub repository and start from there; below, we first clone a repo and start from local sources with the –source parameter
  • Create the container app in a new environment or use an existing environment; below, we use the environment created in previous steps
# clone the super-api repo and cd into it
git clone https://github.com/gbaeke/super-api.git && cd super-api

# checkout the quickguide branch
git checkout quickguide

# bring up the app; container build will take some time
# add the --location parameter to allow az containerapp up to 
# create resources in the specified location; otherwise it uses
# the default location used by the Azure CLI
az containerapp up -n super-api --source . --ingress external --target-port 8080 --environment env-aca

# list apps; super-api has been added with a new external Fqdn
az containerapp list -g $RG -o table

# check ACR in the resource group
az acr list -g $RG -o table

# grab the ACR name
ACR=$(az acr list -g $RG | jq .[0].name -r)

# list repositories
az acr repository list --name $ACR

# more details about the repository
az acr repository show --name $ACR --repository super-api

# show tags; az containerapp up uses numbers based on date and time
az acr repository show-tags --name $ACR --repository super-api

# make a small change to the code; ensure you are still in the
# root of the cloned repo; instead of Hello from Super API we
# will say Hi from Super API when curl hits the /
sed -i s/Hello/Hi/g cmd/app/main.go

# run az containerapp up again; a new container image will be
# built and pushed to ACR and deployed to the container app
az containerapp up -n super-api --source . --ingress external --target-port 8080 --environment env-aca

# check the image tags; there are two
az acr repository show-tags --name $ACR --repository super-api

# curl the endpoint; should say "Hi from Super API"
curl https://$(az containerapp show -g $RG -n super-api | jq .properties.configuration.ingress.fqdn -r)


In this quick guide (well, maybe not ๐Ÿ˜‰) you have seen how to create an Azure Container Apps environment, add two container apps that use Dapr and used az containerapp up for a great inner loop dev experience.

I hope this was useful. If you spot errors, please let me know. Also check the quick guides on GitHub: https://github.com/gbaeke/quick-guides

A look at some of Azure Container App’s new features

A while ago, I created a YouTube playlist about Azure Container Apps. The videos were based on the first public preview. At the time, several features were missing or still needed to be improved (as expected with a preview release):

  • An easy way to create a container app, similar to az webapp up
  • Managed Identity support (system and user assigned)
  • Authentication support with identity providers like Microsoft, Google, Twitter
  • An easy way to follow the logs of a container from your terminal (instead of using Log Analytics queries)
  • Getting a shell to your container for troubleshooting purposes

Let’s take a look at some of these features.

az containerapp up

To manage Container Apps, you can use the containerapp Azure CLI extension. Add it with the following command:

az extension add --name containerapp --upgrade

One of the commands of this extension is up. It lets you create a container app from local source files or from GitHub. With your sources in the current folder, the simplest form of this command is:

az containerapp up --name YOURAPPNAME --source .

The command above creates the following resources:

  • a resource group: mine was called geert_baeke_rg_3837
  • a Log Analytics workspace
  • a Container Apps environment: its name is YOURAPPNAME-env
  • an Azure Container Registry: used to build the container image from a Dockerfile in your source folder
  • the container app: its name is YOURAPPNAME

The great thing here is that you do not need Docker on your local machine for this to work. Building and pushing the container image is done by an ACR task. You only need a Dockerfile in your source folder.

When you change your source code, simply run the same command to deploy your changes. A new image build and push will be started by ACR and a revision of your container app will be published.

โš ๏ธTIP: by default, the container app does not enable ingress from the Internet. To do so, include an EXPOSE command in your Dockerfile.

If you want to try az containerapp up, you can use my super-api sample from GitHub: https://github.com/gbaeke/super-api

Use the following commands to clone the source code and create the container app:

git clone https://github.com/gbaeke/super-api.git
cd super-api
az containerapp up --name super-api --source . --ingress external --target-port 8080

Above, we added the –ingress and –target-port parameters to enable ingress. You will get a URL like https://super-api.livelyplant-fa0ceet5.eastus.azurecontainerapps.io to access the app. In your browser, you will just get: Hello from Super API. If you want a different message, you can run this command:

az containerapp up --name super-api --source . --ingress external --target-port 8080 --env-vars WELCOME=YOURMESSAGE

Running the above command will result in a new revision. Use az containerapp revision list -n super-api -g RESOURCEGROUP -o table to see the revisions of your container app.

There is much more you can do with az containerapp up:

  • Deploy directly from a container image in a registry (with the option to supply registry authentication if the registry is private)
  • Deploy to an existing container app environment
  • Deploy to an existing resource group
  • Use a GitHub repo instead of local sources which uses a workflow to deploy changes as you push them

Managed Identity

You can now easily enable managed identity on a container app. Both System assigned and User assigned are supported. Below, system assigned managed identity was enabled on super-api:

System assigned identity on super-api

Next, I granted the managed identity Reader role on my subscription:

Enabling managed identity is easy enough. In your code, however, you need to obtain a token to do the things you want to do. At a low level, you can use an HTTP call to fetch the token to access a resource like Azure Key Vault. Let’s try that and introduce a new command to get a shell to a container app:

az containerapp exec  -n super-api -g geert_baeke_rg_3837 --command sh

The above command gets a shell to the super-api container. If you want to try this, first modify the Dockerfile and remove the USER command. Otherwise, you are not root and will not be able to install curl. You will also need to use an alpine base image in the second stage instead of scratch (the scratch image does not offer a shell).

In the shell, run the following commands:

apk add curl

The response to the above curl command will include an access token for the Azure Key Vault resource.

A container app with managed identity has several environment variables:

  • IDENTITY_ENDPOINT: http://localhost:42356/msi/token (the endpoint to request the token from)
  • IDENTITY_HEADER: used to protect against server-side request forgery (SSRF) attacks

Instead of using these values to create raw HTTP requests, you can use SDK’s instead. The documentation provides information for .NET, JavaScript, Python, Java, and PowerShell. To try something different, I used the Azure SDK for Go. Here’s a code snippet:

func (s *Server) authHandler(w http.ResponseWriter, r *http.Request) {
	// parse subscription id from request
	subscriptionId := r.URL.Query().Get("subscriptionId")
	if subscriptionId == "" {
		s.logger.Infow("Failed to get subscriptionId from request")

	client := resources.NewGroupsClient(subscriptionId)
	authorizer, err := auth.NewAuthorizerFromEnvironment()
	if err != nil {
		s.logger.Error("Error: ", zap.Error(err))
	client.Authorizer = authorizer

Although the NewAuthorizerFromEnvironment() call above supports managed identity, it seems it does not support the endpoint used in Container Apps and Azure Web App. The code above works fine on a virtual machine and even pod identity (v1) on AKS.

We can use another feature of az containerapp to check the logs:

az containerapp logs show -n super-api -g geert_baeke_rg_3837 --follow

"TimeStamp":"2022-05-05T10:49:59.83885","Log":"Connected to Logstream. Revision: super-api--0yp202c, Replica: super-api--0yp202c-64746cc57b-pf8xh, Container: super-api"}
{"TimeStamp":"2022-05-04T22:02:10.4278442+00:00","Log":"to super api"}
{"TimeStamp":"2022-05-04T22:02:10.4279478+00:00","Log":"read config error Config File "config" Not Found in "[/config]""}
{"TimeStamp":"2022-05-04T22:02:10.4282641+00:00","Log":"client initializing for:"}
{"TimeStamp":"2022-05-04T22:02:10.4282792+00:00","Log":"values","welcome":"Hello from Super API","port":8080,"log":false,"timeout":15}"}

When I try to execute the code that’s supposed to get the token, I get the following error:

{"TimeStamp":"2022-05-05T10:51:58.9469835+00:00","Log":"{error 26 0  MSI not available}","stacktrace":"..."}

As always, it is easy to enable managed identity but tricky to do from code (sometimes ๐Ÿ˜‰). With the new feature that lets you easily grab the logs, it is simpler to check the errors you get back at runtime. Using Log Analytics queries was just not intuitive.


The az container up command makes it extremely simple to deploy a container app from your local machine or GitHub. It greatly enhances the inner loop experience before you start deploying your app to other environments.

The tooling now makes it easy to exec into containers and troubleshoot. Checking runtime errors from logs is now much easier as well.

Managed Identity is something we all were looking forward to. As always, it is easy to implement but do check if the SDKs you use support it. When all else fails, you can always use HTTP! ๐Ÿ˜‰

Building a GitHub Action with Docker

While I was investigating Kyverno, I wanted to check my Kubernetes deployments for compliance with Kyverno policies. The Kyverno CLI can be used to do that with the following command:

kyverno apply ./policies --resource=./deploy/deployment.yaml

To do this easily from a GitHub workflow, I created an action called gbaeke/kyverno-cli. The action uses a Docker container. It can be used in a workflow as follows:

# run kyverno cli and use v1 instead of v1.0.0
- name: Validate policies
  uses: gbaeke/kyverno-action@v1
    command: |
      kyverno apply ./policies --resource=./deploy/deployment.yaml

You can find the full workflow here. In the next section, we will take a look at how you build such an action.

If you want a video instead, here it is:

GitHub Actions

A GitHub Action is used inside a GitHub workflow. An action can be built with Javascript or with Docker. To use an action in a workflow, you use uses: followed by a reference to the action, which is just a GitHub repository. In the above action, we used uses: gbaeke/kyverno-action@v1. The repository is gbaeke/kyverno-action and the version is v1. The version can refer to a release but also a branch. In this case v1 refers to a branch. In a later section, we will take a look at versioning with releases and branches.

Create a repository

An action consists of several files that live in a git repository. Go ahead and create such a repository on GitHub. I presume you know how to do that. We will add several files to it:

  • Dockerfile and all the files that are needed to build the Docker image
  • action.yml: to set the name of our action, its description, inputs and outputs and how it should run

Docker image

Remember that we want a Docker image that can run the Kyverno CLI. That means we have to include the CLI in the image that we build. In this case, we will build the CLI with Go as instructed on https://kyverno.io. Here is the Dockerfile (should be in the root of your git repo):

FROM golang:1.15
COPY src/ /
RUN git clone https://github.com/kyverno/kyverno.git
WORKDIR kyverno
RUN make cli
RUN mv ./cmd/cli/kubectl-kyverno/kyverno /usr/bin/kyverno
ENTRYPOINT ["/entrypoint.sh"]

We start from a golang image because we need the go tools to build the executable. The result of the build is the kyverno executable in /usr/bin. The Docker image uses a shell script as its entrypoint, entrypoint.sh. We copy that shell script from the src folder in our repository.

So go ahead and create the src folder and add a file called entrypoint.sh. Here is the script:

#!/usr/bin/env bash
set -e
set -o pipefail
echo ">>> Running command"
echo ""
bash -c "set -e;  set -o pipefail; $1"

This is just a bash script. We use the set commands in the main script to ensure that, when an error occurs, the script exits with the exit code from the command or pipeline that failed. Because we want to run a command like kyverno apply, we need a way to execute that. That’s why we run bash again at the end with the same options and use $1 to represent the argument we will pass to our container. Our GitHub Action will need a way to require an input and pass that input as the argument to the Docker container.

Note: make sure the script is executable; use chmod +x entrypoint.sh

The action.yml

Action.yml defines our action and should be in the root of the git repo. Here is the action.yml for our Docker action:

name: 'kyverno-action'
description: 'Runs kyverno cli'
  icon: 'command'
  color: 'red'
    description: 'kyverno command to run'
    required: true
  using: 'docker'
  image: 'Dockerfile'
    - ${{ inputs.command }}

Above, we give the action a name and description. We also set an icon and color. The icon and color is used on the GitHub Marketplace:

command icon and color as defined in action.yml (note that this is the REAL action; in this post we call the action kyverno-action as an example)

As stated earlier, we need to pass arguments to the container when it starts. To achieve that, we define a required input to the action. The input is called command but you can use any name.

In the run: section, we specify that this action uses Docker. When you use image: Dockerfile, the workflow will build the Docker image for you with a random name and then run it for you. When it runs the container, it passes the command input as an argument with args: Multiple arguments can be passed, but we only pass one.

Note: the use of a Dockerfile makes running the action quite slow because the image needs to be built every time the action runs. In a moment, we will see how to fix that.

Verify that the image works

On your machine that has Docker installed, build and run the container to verify that you can run the CLI. Run the commands below from the folder containing the Dockerfile:

docker build -t DOCKER_HUB_USER/kyverno-action:v1.0.0 .

docker run DOCKER_HUB_USER/kyverno-action:v1.0.0 "kyverno version"

Above, I presume you have an account on Docker Hub so that you can later push the image to it. Substitute DOCKER_HUB_USER with your Docker Hub username. You can of course use any registry you want.

The result of docker run should be similar to the result below:

>>> Running command

Version: v1.3.5-rc2-1-g3ab75095
Time: 2021-04-04_01:16:49AM
Git commit ID: main/3ab75095b70496bde674a71df08423beb7ba5fff

Note: if you want to build a specific version of the Kyverno CLI, you will need to modify the Dockerfile; the instructions I used build the latest version and includes release candidates

If docker run was successful, push the image to Docker Hub (or your registry):

docker push DOCKER_HUB_USER/kyverno-action:v1.0.0

Note: later, it will become clear why we push this container to a public registry

Publish to the marketplace

You are now ready to publish your action to the marketplace. One thing to be sure of is that the name of your action should be unique. Above, we used kyverno-action. When you run through the publishing steps, GitHub will check if the name is unique.

To see how to publish the action, check the following video:

video starts at the marketplace publishing step

Note that publishing to the marketplace is optional. Our action can still be used without it being published. Publishing just makes our action easier to discover.

Using the action

At this point, you can already use the action when you specify the exact release version. In the video, we created a release called v1.0.0 and optionally published it. The snippet below illustrates its use:

- name: Validate policies
  uses: gbaeke/kyverno-action@v1.0.0
    command: |
      kyverno apply ./policies --resource=./deploy/deployment.yaml

Running this action results in a docker build, followed by a docker run in the workflow:

The build step takes quite some time, which is somewhat annoying. Let’s fix that! In addition, we will let users use v1 instead of having to specify v1.0.0 or v1.0.1 etc…

Creating a v1 branch

By creating a branch called v1 and modifying action.yml to use a Docker image from a registry, we can make the action quicker and easier to use. Just create a branch in GitHub and call it v1. We’ll use the UI:

create the branch here; if it does not exist there will be a create option (here it exists already)

Make the v1 branch active and modify action.yml:

In action.yml, instead of image: ‘Dockerfile’, use the following:

image: 'docker://DOCKER_HUB_USER/kyverno-action:v1.0.0'

When you use the above statement, the image will be pulled instead of built from scratch. You can now use the action with @v1 at the end:

# run kyverno cli and use v1 instead of v1.0.0
- name: Validate policies
  uses: gbaeke/kyverno-action@v1
    command: |
      kyverno apply ./policies --resource=./deploy/deployment.yaml

In the worflow logs, you will see:

The action now pulls the image from Docker Hub and later runs it


We can conclude that building GitHub Actions with Docker is quick and fun. You can build your action any way you want, using the tools you like. Want to create a tool with Go, or Python or just Bash… just do it! If you do want to build a GitHub Action with JavaScript, then be sure to check out this article on devblogs.microsoft.com.

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