28/10/22, 10:00 Exercise - Deploy an application on your Azure Kubernetes Service cluster - Training | Microsoft Learn

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Exercise - Deploy an application on your

Azure Kubernetes Service cluster
10 minutes

In this exercise, you'll deploy your company's website as a test app onto Azure Kubernetes Service
(AKS). The website is a static website with an underlying technology stack of HTML, CSS, and
JavaScript. It doesn't receive as many requests as the other services and provides us with a safe
way to test deployment options.

７ Note

The code for the web app is available in this GitHub repository if you want to explore the
source code further. Also, this sample app will be deployed on a Linux node pool only.

） Important

You need your own Azure subscription to run this exercise, and you might incur charges. If
you don't already have an Azure subscription, create a free account before you begin.

Create a deployment manifest

You create a deployment manifest file to deploy your application. The manifest file allows you to
define what type of resource you want to deploy and all the details associated with the workload.

Kubernetes groups containers into logical structures called pods, which have no intelligence.
Deployments add the missing intelligence to create your application. Let's create a deployment
file.

1. Sign in to Azure Cloud Shell if you haven't done so already.

Azure Cloud Shell

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28/10/22, 10:00 Exercise - Deploy an application on your Azure Kubernetes Service cluster - Training | Microsoft Learn

2. In Cloud Shell, create a manifest file for the Kubernetes deployment called deployment.yaml
by using the integrated editor.

Bash

touch deployment.yaml

3. Open the integrated editor in Cloud Shell by entering code .

4. Open the deployment.yaml file, and add the following code section of YAML.

YAML

# deployment.yaml

apiVersion: apps/v1 # The API resource where this workload resides

kind: Deployment # The kind of workload we're creating

metadata:

name: contoso-website # This will be the name of the deployment

In this code, you added the first two keys to tell Kubernetes the apiVersion and kind of
manifest you're creating. The name is the name of the deployment. You'll use it to identify
and query the deployment information when you use kubectl .

 Tip

For more information about apiVersion and what values to put in this key, see the
official Kubernetes documentation. Find a link at the end of this module.

5. A deployment wraps a pod. You make use of a template definition to define the pod
information within the manifest file. The template is placed in the manifest file under the
deployment specification section.

Update the deployment.yaml file to match the following YAML.

YAML

# deployment.yaml

apiVersion: apps/v1

kind: Deployment

metadata:

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etadata:

name: contoso-website

spec:

template: # This is the template of the pod inside the deployment

metadata: # Metadata for the pod

labels:

app: contoso-website

Pods don't have given names when they're created inside deployments. The pod's name will
be the deployment's name with a random ID added to the end.

Notice the use of the labels key. You add the labels key to allow deployments to find and
group pods.

6. A pod wraps one or more containers. All pods have a specification section that allows you to
define the containers inside that pod.

Update the deployment.yaml file to match the following YAML.

YAML

# deployment.yaml

apiVersion: apps/v1

kind: Deployment

metadata:

name: contoso-website

spec:

template: # This is the template of the pod inside the deployment

metadata:

labels:

app: contoso-website

spec:

containers: # Here we define all containers

- name: contoso-website

The containers key is an array of container specifications because a pod can have one or
more containers. The specification defines an image , a name , resources , ports , and other
important information about the container.

All running pods will follow the name contoso-website-<UUID> , where UUID is a generated
ID to identify all resources uniquely.

7. It's a good practice to define a minimum and a maximum amount of resources that the app
is allowed to use from the cluster. You use the resources key to specify this information.

Update the d l t l file to match the follo ing YAML

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28/10/22, 10:00 Exercise - Deploy an application on your Azure Kubernetes Service cluster - Training | Microsoft Learn
Update the deployment.yaml file to match the following YAML.

YAML

# deployment.yaml

apiVersion: apps/v1

kind: Deployment

metadata:

name: contoso-website

spec:

template: # This is the template of the pod inside the deployment

metadata:

labels:

app: contoso-website

spec:

containers:

- image: mcr.microsoft.com/mslearn/samples/contoso-website
name: contoso-website

resources:

requests: # Minimum amount of resources requested

cpu: 100m
memory: 128Mi

limits: # Maximum amount of resources requested

cpu: 250m
memory: 256Mi

Notice how the resource section allows you to specify the minimum resource amount as a
request and the maximum resource amount as a limit.

8. The last step is to define the ports this container will expose externally through the ports
key. The ports key is an array of objects, which means that a container in a pod can expose
multiple ports with multiple names.

Update the deployment.yaml file to match the following YAML.

YAML

# deployment.yaml

apiVersion: apps/v1

kind: Deployment

metadata:

name: contoso-website

spec:

template: # This is the template of the pod inside the deployment

metadata:

labels:

app: contoso-website

spec:
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28/10/22, 10:00 Exercise - Deploy an application on your Azure Kubernetes Service cluster - Training | Microsoft Learn
spec:

nodeSelector:

kubernetes.io/os: linux

containers:

- image: mcr.microsoft.com/mslearn/samples/contoso-website
name: contoso-website

resources:

requests:

cpu: 100m
memory: 128Mi

limits:

cpu: 250m
memory: 256Mi

ports:

- containerPort: 80 # This container exposes port 80

name: http # We named that port "http" so we can refer to it later

Notice how you name the port by using the name key. Naming ports allows you to change
the exposed port without changing files that reference that port.

9. Finally, add a selector section to define the workloads the deployment will manage. The
selector key is placed inside the deployment specification section of the manifest file. Use
the matchLabels key to list the labels for all the pods managed by the deployment.

Update the deployment.yaml file to match the following YAML.

YAML

# deployment.yaml

apiVersion: apps/v1

kind: Deployment

metadata:

name: contoso-website

spec:

selector: # Define the wrapping strategy

matchLabels: # Match all pods with the defined labels

app: contoso-website # Labels follow the `name: value` template

template: # This is the template of the pod inside the deployment

metadata:

labels:

app: contoso-website

spec:

nodeSelector:

kubernetes.io/os: linux

containers:

- image: mcr.microsoft.com/mslearn/samples/contoso-website
name: contoso-website

resources:

requests:

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equests:

cpu: 100m
memory: 128Mi

limits:

cpu: 250m
memory: 256Mi

ports:

- containerPort: 80

name: http

７ Note

In an AKS cluster which has multiple node pools (Linux and Windows), the deployment
manifest file listed above also defines a nodeSelector to tell your AKS cluster to run the
sample application's pod on a node that can run Linux containers.

Linux nodes can't run Windows containers and vice versa.

10. Save the manifest file and close the editor.

Apply the manifest

1. In Cloud Shell, run the kubectl apply command to submit the deployment manifest to your
cluster.

Bash

kubectl apply -f ./deployment.yaml

The command should output a result similar to the following example.

Output

deployment.apps/contoso-website created

2. Run the kubectl get deploy command to check if the deployment was successful.

Bash

kubectl get deploy contoso-website

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The command should output a table similar to the following example.

Output

NAME READY UP-TO-DATE AVAILABLE AGE

contoso-website 0/1 1 0 16s

3. Run the kubectl get pods command to check if the pod is running.

Bash

kubectl get pods

The command should output a table similar to the following example.

Output

NAME READY STATUS RESTARTS AGE

contoso-website-7c58c5f699-r79mv 1/1 Running 0 63s

Next unit: Enable network access to an application

Continue Ｔ

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