# Part 3: Deploy VM

## What Will You Do

In this part of the self-paced exercise, you will deploy a virtual machine workload to your cluster running KubeVirt.

---

## Step 1: Create Workload Namespace

In this step, you will create a namespace for the virtual machine. The "namespace.yaml" file in the "/getstarted/kubevirt/workload" directory of the forked repository contains the declarative specification for the namespace resource.

- Open a Terminal (macOS/Linux) or Command Prompt (Windows) and navigate to the folder where you forked the Git repository
- Navigate to the folder "/getstarted/kubevirt/workload"
- Type the command

```bash
rctl create namespace -f namespace.yaml
```

If you did not encounter any errors, you can optionally verify if everything was created correctly on the controller.

- In your project, select **Infrastructure -> Namespaces**
- You should see a namespace called **vm**

Next, you will publish the namespace to the cluster.

- Type the command below

```bash
rctl publish namespace vm
```

---

## Step 2: Deploy Virtual Machine Workload

In this step, you will create a workload resource for the virtual machine. The "vm-workload.yaml" file in the "/getstarted/kubevirt/workload" directory of the forked repository contains the declarative specification for the workload.

The following items may need to be updated/customized if you used alternate names.

- project: defaultproject
- clusters: kubevirt-cluster

```yaml
name: vm
namespace: vm
project: defaultproject
type: NativeYaml
clusters: kubevirt-cluster
payload: ./vm.yaml
```

Note that the workload's name is "vm" and it is of type "k8s YAML". The actual k8s YAML file for the VM is in the payload "vm.yaml" file.

```bash
rctl create workload vm-workload.yaml
```

If there were no errors, you should see a message like below

```bash
Workload created successfully
```

Now, let us publish the newly created VM workload to the cluster. The workload can be deployed to multiple clusters as per the configured "placement policy". In this case, you are deploying to a single cluster with the name "kubevirt-cluster".

```bash
rctl publish workload vm
```

---

## Step 3: Verify Workload

In the web console, click on **Applications -> Workloads**. You should see something like the following.

Now, let us verify the virtual machine is running.

- Click on the kubectl link in the cluster card and type the following command

```bash
kubectl get vm -n vm
```

You should see something like the following showing the VM in a running state.

```bash
NAME     AGE   STATUS    READY
testvm   50s   Running   True
```

---

## Step 4: Download KubeVirt's virtctl CLI

The virtctl CLI is needed for the use of advanced features to interact with virtual machines.

- On your machine, run the following commands

```bash
VERSION=$(kubectl get kubevirt.kubevirt.io/kubevirt -n kubevirt -o=jsonpath="{.status.observedKubeVirtVersion}")
ARCH=$(uname -s | tr A-Z a-z)-$(uname -m | sed 's/x86_64/amd64/') || windows-amd64.exe
echo ${ARCH}
curl -L -o virtctl https://github.com/kubevirt/kubevirt/releases/download/${VERSION}/virtctl-${VERSION}-${ARCH}
chmod +x virtctl
sudo install virtctl /usr/local/bin
```

---

## Step 5: Access Virtual Machine

In this step, you will access the virtual machine using the previously installed virtctl CLI.

- Run the below command to access the VM

```bash
virtctl console testvm -n vm
```

- Login to the VM using the onscreen credentials.

You are now able to use the VM terminal.

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## Recap

Congratulations! At this point, you have successfully deployed a virtual machine to the Kubernetes cluster and accessed the VM's terminal.

---