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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.

Prerequisites

  • An existing AKS cluster. Any cluster is supported, but if you're using Microsoft Entra integration, your cluster must use 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

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.
  • Network policies shows the network policy resources that control traffic flow between pods within your cluster.
  • 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.

👁 Screenshot showing the Kubernetes resources displayed in the Azure portal.

Connect to your AKS 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

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

  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: StatefulSet
metadata:
 name: rabbitmq
spec:
 serviceName: rabbitmq
 replicas: 1
 selector:
 matchLabels:
 app: rabbitmq
 template:
 metadata:
 labels:
 app: rabbitmq
 spec:
 nodeSelector:
 "kubernetes.io/os": linux
 containers:
 - name: rabbitmq
 image: mcr.microsoft.com/azurelinux/base/rabbitmq-server:3.13
 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: 100m
 memory: 256Mi
 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: 100m
 memory: 256Mi
---
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: 2m
 memory: 20Mi
---
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 Apply.

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

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

    👁 Screenshot of the Azure Store application services displayed in the Azure portal.

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.

Tip

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, 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 delegated to access the AKS cluster. For more information, see Access and identity options for AKS.

Viewing Kubernetes resources is inaccessible

You might need to configure authorized IP ranges 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.

  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 <cluster-name> --api-server-authorized-ip-ranges $CURRENT_IP/32

  3. After updating your cluster's authorized IP ranges, run the following command to update and merge your kubeconfig:

    az aks get-credentials --resource-group <resource-group-name> --name <cluster-name>

    The expected output informs you of this update:

    Merged "<cluster-name>" as current context ...

If your AKS cluster is configured as a private cluster, you must access the Azure portal from a network that can reach the subnet where your AKS cluster resides. Otherwise, AKS resources are inaccessible in the portal due to network connectivity issues. To learn more, see Access an AKS private cluster.

Related content

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

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