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# Examples
After [installing the CLI](install.md) and [creating a cluster](first-steps.md) we've collected a few Kubernetes example applications for deploying in your cluster. They highlight different features and give a first hands-on experience working with Kubernetes in a Constellation cluster. If you have experience with Kubernetes deployments there shouldn't be any sensible differences. Have fun exploring your Confidential Kubernetes!
Before trying out the example applications, make sure you [installed the Constellation CLI](install.md) and [created a cluster](first-steps.md). From there, the examples shown here are designed to work on a freshly created cluster and don't require any further prerequisites.
Check out the following examples:
* [Emojivoto](examples/emojivoto.md): A simple but fun demo application to test the general functionality of your confidential cluster.
* [Online Boutique](examples/online-boutique.md): An e-commerce demo application by Google consisting of 11 separate microservices.
* [Horizontal Pod Autoscaling](examples/horizontal-scaling.md): An example demonstrating Constellation's autoscaling capabilities.

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# Emojivoto
For a simple but fun demo application to test the general functionality of your confidential cluster, take a look at [Emojivoto](https://github.com/BuoyantIO/emojivoto).
<!-- vale off -->
<img src={require("../../_media/example-emojivoto.jpg").default} alt="emojivoto - Web UI" width="552"/>
<!-- vale on -->
1. Deploy the application:
```bash
kubectl apply -k github.com/BuoyantIO/emojivoto/kustomize/deployment
```
2. Wait until it becomes available:
```bash
kubectl wait --for=condition=available --timeout=60s -n emojivoto --all deployments
```
3. Forward the web service to your machine:
```bash
kubectl -n emojivoto port-forward svc/web-svc 8080:80
```
4. Visit [http://localhost:8080](http://localhost:8080)

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# Horizontal Pod Autoscaling
This example demonstrates Constellation's autoscaling capabilities by utilizing a slightly adapted version of the Kubernetes [HorizontalPodAutoscaler Walkthrough](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/). During the following steps, we will see Constellation be able to spawn new VMs on demand, add them to the cluster and later on delete them again when the load has settled down.
## Requirements
The cluster needs to be initialized with Kubernetes 1.23 or higher. In addition, autoscaling must be enabled to trigger Constellation to assign new nodes dynamically.
Just for this example specifically, the cluster should have as few worker nodes in the beginning as possible. Starting with a small cluster having only *one* control plane node and *one* worker node using one of the low-end supported VMs is recommended for an easier demonstration and saving costs. The example has been tested on Azure using a `Standard_DC4as_v5` and on GCP using `n2d-standard-4` instance.
## Setup
1. Install the Kubernetes Metrics Server:
```bash
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml
```
2. Deploy the HPA example server that's supposed to be scaled under load.
This is almost the same as the example which can be found in the official Kubernetes HPA walkthrough, with the only difference being increased CPU limits and requests to facilitate the triggering of node scaling events.
```bash
cat <<EOF | kubectl apply -f -
apiVersion: apps/v1
kind: Deployment
metadata:
name: php-apache
spec:
selector:
matchLabels:
run: php-apache
replicas: 1
template:
metadata:
labels:
run: php-apache
spec:
containers:
- name: php-apache
image: registry.k8s.io/hpa-example
ports:
- containerPort: 80
resources:
limits:
cpu: 900m
requests:
cpu: 600m
---
apiVersion: v1
kind: Service
metadata:
name: php-apache
labels:
run: php-apache
spec:
ports:
- port: 80
selector:
run: php-apache
EOF
```
3. Create a HorizontalPodAutoscaler.
It's recommended to set an average CPU utilization across all Pods of 20% with the above server CPU limits and requests to see one additional worker nodes being created later. Note that the CPU utilization used here isn't 1:1 the host CPU utilization, but rather the requested CPU capacities (20% of 600 milli-cores CPU across all Pods). Take a look at the [original tutorial](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/#create-horizontal-pod-autoscaler) for more information on the HPA configuration.
```bash
kubectl autoscale deployment php-apache --cpu-percent=20 --min=1 --max=10
```
4. Create a Pod which generates load onto the server:
```bash
kubectl run -i --tty load-generator --rm --image=busybox:1.28 --restart=Never -- /bin/sh -c "while true; do wget -q -O- http://php-apache; done"
```
5. Wait for a few minutes until new nodes are added to the cluster. See below for how to monitor the state of the HorizontalPodAutoscaler, the list of nodes and the behavior of the autoscaler.
6. To kill the load generator, press CTRL+C and run:
```bash
kubectl delete pod load-generator
```
7. The cluster-autoscaler checks every few minutes if nodes are underutilized and can be removed from the cluster. It will taint such candidates for removal and wait additional 10 minutes before the nodes are eventually removed and deallocated. The whole process can take ~20 minutes in total.
## Monitoring
:::tip
For better observability, run the listed commands in different tabs in your terminal.
:::
You can watch the status of the HorizontalPodAutoscaler with the current CPU, the target CPU limit, and the number of replicas created with:
```bash
kubectl get hpa php-apache --watch
```
From time to time compare the list of nodes to check the behavior of the autoscaler:
```bash
kubectl get nodes
```
For deeper insights, take a look at the logs of the autoscaler Pod which contains more details about the scaling decision process:
```bash
kubectl logs -f deployment/constellation-cluster-autoscaler -n kube-system
```

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# Online Boutique
[Online Boutique](https://github.com/GoogleCloudPlatform/microservices-demo) is an e-commerce demo application by Google consisting of 11 separate microservices. Constellation is automatically able to set up a load balancer on your CSP, making it easy to expose services from your confidential cluster without any additional setup required.
<!-- vale off -->
<img src={require("../../_media/example-online-boutique.jpg").default} alt="Online Boutique - Web UI" width="662"/>
<!-- vale on -->
1. Create a namespace:
```bash
kubectl create ns boutique
```
2. Deploy the application:
```bash
kubectl apply -n boutique -f https://github.com/GoogleCloudPlatform/microservices-demo/raw/main/release/kubernetes-manifests.yaml
```
3. Wait for all services to become fully available:
```bash
kubectl wait --for=condition=available --timeout=300s -n boutique --all deployments
```
4. Get the external facing IP address of the frontend (with `<your-ip>` being a placeholder for the assigned IP from your CSP):
```terminal-session
kubectl get service frontend-external -n boutique | awk '{print $4}'
EXTERNAL-IP
<your-ip>
```
5. Enter the IP from the result in your browser to browse the online shop.

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# First steps
The following steps will guide you through the process of creating a cluster and deploying a sample app. This example assumes that you have successfully [installed and set up Constellation](install.md).
## Create a cluster
1. Create the configuration file for your selected cloud provider.
<tabs>
<tabItem value="azure" label="Azure" default>
On Azure you also need a *user-assigned managed identity* with the [correct permissions](install.md?id=authorization).
Then execute:
```bash
constellation config generate azure
```
</tabItem>
<tabItem value="gcp" label="GCP" default>
```bash
constellation config generate gcp
```
</tabItem>
</tabs>
This creates the file `constellation-conf.yaml` in your current working directory. Edit this file to set your cloud subscription IDs and optionally customize further options of your Constellation cluster. All configuration options are documented in this file.
For more details, see the [reference section](../reference/config.md#required-customizations).
2. Download the measurements for your configured image.
```bash
constellation config fetch-measurements
```
This command is necessary to download the latest trusted measurements for your configured image.
For more details, see the [verification section](../workflows/verify.md).
3. Create the cluster with one control-plane node and two worker nodes. `constellation create` uses options set in `constellation-conf.yaml` automatically.
<tabs>
<tabItem value="azure" label="Azure" default>
```bash
constellation create azure --control-plane-nodes 1 --worker-nodes 2 --instance-type Standard_D4a_v4 -y
```
</tabItem>
<tabItem value="gcp" label="GCP" default>
```bash
constellation create gcp --control-plane-nodes 1 --worker-nodes 2 --instance-type n2d-standard-2 -y
```
</tabItem>
</tabs>
This should give the following output:
```shell-session
$ constellation create ...
Your Constellation cluster was created successfully.
```
4. Initialize the cluster
```bash
constellation init
```
This should give the following output:
```shell-session
$ constellation init
Creating service account ...
Your Constellation cluster was successfully initialized.
Constellation cluster's identifier g6iMP5wRU1b7mpOz2WEISlIYSfdAhB0oNaOg6XEwKFY=
Kubernetes configuration constellation-admin.conf
You can now connect to your cluster by executing:
export KUBECONFIG="$PWD/constellation-admin.conf"
```
The cluster's identifier will be different in your output.
Keep `constellation-mastersecret.json` somewhere safe.
This will allow you to [recover your cluster](../workflows/recovery.md) in case of a disaster.
5. Configure kubectl
```bash
export KUBECONFIG="$PWD/constellation-admin.conf"
```
## Deploy a sample application
1. Deploy the [emojivoto app](https://github.com/BuoyantIO/emojivoto)
```bash
kubectl apply -k github.com/BuoyantIO/emojivoto/kustomize/deployment
```
2. Expose the frontend service locally
```bash
kubectl wait --for=condition=available --timeout=60s -n emojivoto --all deployments
kubectl -n emojivoto port-forward svc/web-svc 8080:80 &
curl http://localhost:8080
kill %1
```
## Terminate your cluster
```bash
constellation terminate
```
This should give the following output:
```shell-session
$ constellation terminate
Terminating ...
Your Constellation cluster was terminated successfully.
```

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# Installation and Setup
Constellation runs entirely in your cloud environment and can be easily controlled via a dedicated Command Line Interface (CLI).
The installation process will guide you through the steps of installing the CLI on your machine, verifying it, and connecting it to your Cloud Service Provider (CSP).
### Prerequisites
Before we start, make sure the following requirements are fulfilled:
- Your machine is running Ubuntu or macOS
- You have admin rights on your machine
- [kubectl](https://kubernetes.io/docs/tasks/tools/) is installed
- Your cloud provider is Microsoft Azure or Google Cloud
## Install the Constellation CLI
The Constellation CLI can be downloaded from our [release page](https://github.com/edgelesssys/constellation/releases). Therefore, navigate to a release and download the file `constellation`. Move the downloaded file to a directory in your `PATH` (default: `/usr/local/bin`) and make it executable by entering `chmod s+x constellation` in your terminal.
Running `constellation` should then give you:
```shell-session
$ constellation
Manage your Constellation cluster.
Usage:
constellation [command]
...
```
### Optional: Enable shell autocompletion
The Constellation CLI supports autocompletion for various shells. To set it up, run `constellation completion` and follow the steps.
## Verify the CLI
For extra security, make sure to verify your CLI. Therefore, install [cosign](https://github.com/sigstore/cosign). Then, head to our [release page](https://github.com/edgelesssys/constellation/releases) again and, from the same release as before, download the following files:
- `cosign.pub` (Edgeless System's cosign public key)
- `constellation.sig` (the CLI's signature)
You can then verify your CLI before launching a cluster using the paths to the public key, signature, and CLI executable:
```bash
cosign verify-blob --key cosign.pub --signature constellation.sig constellation
```
For more detailed information read our [installation, update and verification documentation](../architecture/orchestration.md).
## Set up cloud credentials
The CLI makes authenticated calls to the CSP API. Therefore, you need to set up Constellation with the credentials for your CSP.
### Authentication
In the following, we provide you with different ways to authenticate with your CSP.
:::danger
Don't use the testing methods for setting up a production-grade Constellation cluster. In those methods, secrets are stored on disk during installation which would be exposed to the CSP.
:::
<tabs>
<tabItem value="azure" label="Azure" default>
**Testing**
To try out Constellation, using a cloud environment such as [Azure Cloud Shell](https://docs.microsoft.com/en-us/azure/cloud-shell/overview) is the quickest way to get started.
**Production**
For production clusters, use the [Azure CLI](https://docs.microsoft.com/en-us/cli/azure/) on a trusted machine:
```bash
az login
```
Other options are described in Azure's [authentication guide](https://docs.microsoft.com/en-us/cli/azure/authenticate-azure-cli).
</tabItem>
<tabItem value="gcp" label="GCP" default>
Enable the following cloud APIs first:
- [Compute Engine API](https://console.cloud.google.com/marketplace/product/google/compute.googleapis.com)
- [Cloud Resource Manager API](https://console.cloud.google.com/apis/library/cloudresourcemanager.googleapis.com)
- [Identity and Access Management (IAM) API](https://console.developers.google.com/apis/api/iam.googleapis.com)
**Testing**
- If you are running from within a Google VM, and the VM is allowed to access the necessary APIs, no further configuration is needed.
- If you are using the [Google Cloud Shell](https://cloud.google.com/shell), make sure your [session is authorized](https://cloud.google.com/shell/docs/auth). For example, execute `gsutil` and accept the authorization prompt.
**Production**
For production clusters, use one of the following options on a trusted machine:
- Use the [`gcloud` CLI](https://cloud.google.com/sdk/gcloud)
```bash
gcloud auth application-default login
```
This will ask you to log in to your Google account, and then create your credentials.
The Constellation CLI will automatically load these credentials when needed.
- Set up a service account and pass the credentials manually
Follow [Google's guide](https://cloud.google.com/docs/authentication/production#manually) for setting up your credentials.
</tabItem>
</tabs>
### Authorization
<tabs>
<tabItem value="azure" label="Azure" default>
Your user account needs the following permissions to set up a Constellation cluster:
- `Contributor`
- `User Access Administrator`
Additionally, you need to [create a user-assigned managed identity](https://docs.microsoft.com/en-us/azure/active-directory/managed-identities-azure-resources/how-manage-user-assigned-managed-identities) with the following roles:
- `Virtual Machine Contributor`
- `Application Insights Component Contributor`
The user-assigned identity is used by the instances of the cluster to access other cloud resources.
You also need an empty resource group per cluster. Notice that the user-assigned identity has to be created in a
different resource group as all resources within the cluster resource group will be deleted on cluster termination.
Last, you need to [create an Active Directory app registration](https://docs.microsoft.com/en-us/azure/active-directory/develop/quickstart-register-app#register-an-application) (you don't need to add a redirect URI).
As supported account types choose 'Accounts in this organizational directory only'. Then [create a client secret](https://docs.microsoft.com/en-us/azure/active-directory/develop/howto-create-service-principal-portal#option-2-create-a-new-application-secret), which will be used by Kubernetes.
On the cluster resource group, [add the app registration](https://docs.microsoft.com/en-us/azure/role-based-access-control/role-assignments-portal?tabs=current#step-2-open-the-add-role-assignment-page)
with role `Owner`.
User-assigned identity, cluster resource group, app registration client ID and client secret value need to be set in the `constellation-conf.yaml` configuration file.
</tabItem>
<tabItem value="gcp" label="GCP" default>
Your user account needs the following permissions to set up a Constellation:
- `compute.*` (or the subset defined by `roles/compute.instanceAdmin.v1`)
Follow Google's guide on [understanding](https://cloud.google.com/iam/docs/understanding-roles) and [assigning roles](https://cloud.google.com/iam/docs/granting-changing-revoking-access).
Additionally, you need a service account with the following permissions:
- `Compute Instance Admin (v1) (roles/compute.instanceAdmin.v1)`
- `Compute Network Admin (roles/compute.networkAdmin)`
- `Compute Security Admin (roles/compute.securityAdmin)`
- `Compute Storage Admin (roles/compute.storageAdmin)`
- `Service Account User (roles/iam.serviceAccountUser)`
The key for this service account is passed to the CLI and used by Kubernetes to authenticate with the cloud.
You can configure the path to the key in the `constellation-conf.yaml` configuration file.
GCP instances come with a [default service account](https://cloud.google.com/iam/docs/service-accounts#default) attached
that's used by the instances to access the cloud resources of the cluster. You don't need to configure it.
</tabItem>
</tabs>
### Troubleshooting
If you receive an error during any of the outlined steps, please verify that you have executed all previous steps in this documentation. Also, feel free to ask our active community on [Discord](https://discord.com/invite/rH8QTH56JN) for help.
### Next Steps
Once you have followed all previous steps, you can proceed [to deploy your first confidential Kubernetes cluster and application](first-steps.md).