Access Kubernetes resources using the Azure portal

In this article, you learn how to access and manage your Azure Kubernetes Service (AKS) resources using the Azure portal.

Before you begin

To view Kubernetes resources in the Azure portal, you need an AKS cluster. Any cluster is supported, but if you're using Microsoft Entra integration, your cluster must use AKS-managed Microsoft Entra integration. If your cluster uses legacy Microsoft Entra ID, you can upgrade your cluster in the portal or with the Azure CLI. You can also use the Azure portal to create a new AKS cluster.

View Kubernetes resources

1. In the Azure portal, navigate to your AKS cluster resource.

2. From the service menu, select Kubernetes resources. The Kubernetes resources list displays the following categories:

   • Namespaces shows information about the namespaces of your cluster.
   • Workloads shows information about deployments, pods, replica sets, stateful sets, daemon sets, jobs, and cron jobs deployed to your cluster.
   • Services and ingresses shows all of your cluster's service and ingress resources.
   • Storage shows your Azure storage classes and persistent volume information.
   • Configuration shows your cluster's config maps and secrets.
   • Custom resources shows any custom resources deployed to your cluster.
   • Events shows all events related to your cluster.
   • Run command allows you to remotely invoke commands, like kubectl and helm, on your cluster through the Azure API without directly connecting to the cluster.

   

Deploy a sample application

In this section, we deploy the Azure Store application from the AKS quickstart.

Connect to your cluster

To deploy the Azure Store application, you need to connect to your AKS cluster. Follow these steps to connect to your cluster using the Azure portal:

1. From the Overview page of your AKS cluster, select Connect.
2. Follow the instructions to connect to your cluster using Cloud Shell, Azure CLI, or Run command.

Deploy the Azure Store application

1. From the Kubernetes resources list, select Services and ingresses.

2. Select Create > Apply a YAML.

3. Copy and paste the following YAML into the editor:

   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: rabbitmq
   spec:
     replicas: 1
     selector:
       matchLabels:
         app: rabbitmq
     template:
       metadata:
         labels:
           app: rabbitmq
       spec:
         nodeSelector:
           "kubernetes.io/os": linux
         containers:
         - name: rabbitmq
           image: mcr.microsoft.com/mirror/docker/library/rabbitmq:3.10-management-alpine
           ports:
           - containerPort: 5672
             name: rabbitmq-amqp
           - containerPort: 15672
             name: rabbitmq-http
           env:
           - name: RABBITMQ_DEFAULT_USER
             value: "username"
           - name: RABBITMQ_DEFAULT_PASS
             value: "password"
           resources:
             requests:
               cpu: 10m
               memory: 128Mi
             limits:
               cpu: 250m
               memory: 256Mi
           volumeMounts:
           - name: rabbitmq-enabled-plugins
             mountPath: /etc/rabbitmq/enabled_plugins
             subPath: enabled_plugins
         volumes:
         - name: rabbitmq-enabled-plugins
           configMap:
             name: rabbitmq-enabled-plugins
             items:
             - key: rabbitmq_enabled_plugins
               path: enabled_plugins
   ---
   apiVersion: v1
   data:
     rabbitmq_enabled_plugins: |
       [rabbitmq_management,rabbitmq_prometheus,rabbitmq_amqp1_0].
   kind: ConfigMap
   metadata:
     name: rabbitmq-enabled-plugins
   ---
   apiVersion: v1
   kind: Service
   metadata:
     name: rabbitmq
   spec:
     selector:
       app: rabbitmq
     ports:
       - name: rabbitmq-amqp
         port: 5672
         targetPort: 5672
       - name: rabbitmq-http
         port: 15672
         targetPort: 15672
     type: ClusterIP
   ---
   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: order-service
   spec:
     replicas: 1
     selector:
       matchLabels:
         app: order-service
     template:
       metadata:
         labels:
           app: order-service
       spec:
         nodeSelector:
           "kubernetes.io/os": linux
         containers:
         - name: order-service
           image: ghcr.io/azure-samples/aks-store-demo/order-service:latest
           ports:
           - containerPort: 3000
           env:
           - name: ORDER_QUEUE_HOSTNAME
             value: "rabbitmq"
           - name: ORDER_QUEUE_PORT
             value: "5672"
           - name: ORDER_QUEUE_USERNAME
             value: "username"
           - name: ORDER_QUEUE_PASSWORD
             value: "password"
           - name: ORDER_QUEUE_NAME
             value: "orders"
           - name: FASTIFY_ADDRESS
             value: "0.0.0.0"
           resources:
             requests:
               cpu: 1m
               memory: 50Mi
             limits:
               cpu: 75m
               memory: 128Mi
         initContainers:
         - name: wait-for-rabbitmq
           image: busybox
           command: ['sh', '-c', 'until nc -zv rabbitmq 5672; do echo waiting for rabbitmq; sleep 2; done;']
           resources:
             requests:
               cpu: 1m
               memory: 50Mi
             limits:
               cpu: 75m
               memory: 128Mi
   ---
   apiVersion: v1
   kind: Service
   metadata:
     name: order-service
   spec:
     type: ClusterIP
     ports:
     - name: http
       port: 3000
       targetPort: 3000
     selector:
       app: order-service
   ---
   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: product-service
   spec:
     replicas: 1
     selector:
       matchLabels:
         app: product-service
     template:
       metadata:
         labels:
           app: product-service
       spec:
         nodeSelector:
           "kubernetes.io/os": linux
         containers:
         - name: product-service
           image: ghcr.io/azure-samples/aks-store-demo/product-service:latest
           ports:
           - containerPort: 3002
           resources:
             requests:
               cpu: 1m
               memory: 1Mi
             limits:
               cpu: 1m
               memory: 7Mi
   ---
   apiVersion: v1
   kind: Service
   metadata:
     name: product-service
   spec:
     type: ClusterIP
     ports:
     - name: http
       port: 3002
       targetPort: 3002
     selector:
       app: product-service
   ---
   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: store-front
   spec:
     replicas: 1
     selector:
       matchLabels:
         app: store-front
     template:
       metadata:
         labels:
           app: store-front
       spec:
         nodeSelector:
           "kubernetes.io/os": linux
         containers:
         - name: store-front
           image: ghcr.io/azure-samples/aks-store-demo/store-front:latest
           ports:
           - containerPort: 8080
             name: store-front
           env:
           - name: VUE_APP_ORDER_SERVICE_URL
             value: "http://order-service:3000/"
           - name: VUE_APP_PRODUCT_SERVICE_URL
             value: "http://product-service:3002/"
           resources:
             requests:
               cpu: 1m
               memory: 200Mi
             limits:
               cpu: 1000m
               memory: 512Mi
   ---
   apiVersion: v1
   kind: Service
   metadata:
     name: store-front
   spec:
     ports:
     - port: 80
       targetPort: 8080
     selector:
       app: store-front
     type: LoadBalancer
   

4. Select Add.

   Once the application finishes deploying, you see the following services in the Services list:

   • order-service
   • product-service
   • rabbitmq
   • store-front

   

Monitor deployment insights

Enable the monitoring add-on on your AKS cluster

AKS clusters with Container Insights enabled can access various deployment insights in the Azure portal. If you don't have monitoring enabled on your cluster, you can enable it using the following steps:

1. From the service menu of your AKS cluster resource, select Monitoring > Insights > Configure monitoring.

2. On the Configure Container Insights page, select Configure.

   It might take a few minutes for the monitoring solution to deploy and begin collecting data.

View deployment insights

1. From the service menu of your AKS cluster resource, select Workloads.
2. Select a deployment from the list to view deployment insights, such as CPU and memory usage.

Note

You can also select Monitoring > Insights to view more in-depth information about specific nodes and containers.

Clean up resources

If you no longer need the Azure Store application, you can delete the services to avoid incurring Azure costs.

1. From the Kubernetes resources list, select Services and ingresses.
2. Select the services you want to delete, and then select Delete.

Troubleshooting

Unauthorized access

To access the Kubernetes resources, you need access to the AKS cluster, Kubernetes API, and Kubernetes objects. Make sure you're either a cluster administrator or a user with the appropriate permissions to access the AKS cluster. For more information, see Access and identity options for AKS.

Enable resource view

You might need to enable the Kubernetes resource view for existing clusters.

Tip

You can add the AKS feature for API server authorized IP ranges to limit API server access to only the firewall's public endpoint. Another option is to update the --api-server-authorized-ip-ranges/-ApiServerAccessAuthorizedIpRange to include access for a local client computer or the IP address range from which you're browsing the Azure portal. To allow this access, you need the computer's public IPv4 address. You can find this address using the following Azure CLI or Azure PowerShell commands, or you can search "what is my IP address" in your browser.

Azure CLI

1. Retrieve your IP address using the following command:

   CURRENT_IP=$(dig +short myip.opendns.com @resolver1.opendns.com)
   

2. Add your IP address to the AKS approved list using the az aks update command with the --api-server-authorized-ip-ranges parameter.

   az aks update --resource-group <resource-group-name> --name <aks-cluster-name> --api-server-authorized-ip-ranges $CURRENT_IP/32
   

Azure PowerShell

1. Retrieve your IP address using the following command:

   $CURRENT_IP = (Invoke-RestMethod -Uri http://ipinfo.io/json).ip
   

2. Add your IP address to the AKS approved list using the Set-AzAksCluster command with the -ApiServerAccessAuthorizedIpRange parameter.

   Set-AzAksCluster -ResourceGroupName <resource-group-name> -Name <aks-cluster-name> -ApiServerAccessAuthorizedIpRange $CURRENT_IP/32
   

Next steps

This article showed you how to access Kubernetes resources from the Azure portal. For more information about AKS, Core concepts for Azure Kubernetes Service (AKS).