Containers Azure Integrator

  • By Canonical Kubernetes
Channel Version Revision Published Runs on
latest/stable 160 160 16 Dec 2021
Ubuntu 20.04 Ubuntu 18.04 Ubuntu 16.04
latest/candidate 137 137 26 Oct 2021
Ubuntu 20.04 Ubuntu 18.04 Ubuntu 16.04
latest/beta 160 160 15 Dec 2021
Ubuntu 20.04 Ubuntu 18.04 Ubuntu 16.04
latest/edge 170 170 31 Jan 2022
Ubuntu 20.04 Ubuntu 18.04 Ubuntu 16.04
juju deploy containers-azure-integrator
Show information

Platform:

Ubuntu
20.04 18.04 16.04

Overview

This charm acts as a proxy to Azure and provides an interface to apply a certain set of changes via roles, profiles, and tags to the instances of the applications that are related to this charm.

Usage

When on Azure, this charm can be deployed, granted trust via Juju to access Azure, and then related to an application that supports the interface. The set of permissions that the related application could request is documented in the interface's Requires API documentation.

For example, CDK has support for this, and can be deployed with the following bundle overlay:

applications:
  azure-integrator:
    charm: cs:~containers/azure-integrator
    num_units: 1
relations:
  - ['azure-integrator', 'kubernetes-master']
  - ['azure-integrator', 'kubernetes-worker']

Then deploy CDK using this overlay:

juju deploy cs:canonical-kubernetes --overlay ./k8s-azure-overlay.yaml

The charm then needs to be granted access to credentials that it can use to setup integrations. Using Juju 2.4 or later, you can easily grant access to the credentials used deploy the integrator itself:

juju trust azure-integrator

To deploy with earlier versions of Juju, or if you wish to provide it different credentials, you will need to provide the cloud credentials via the credentials, charm config options.

Note: The credentials used must have rights to use the API to inspect the instances connecting to it, enable a Managed Service Identity (MSI) for those instances, assign roles to those instances, and create custom roles. This may be different from the access permissions that Juju itself requires.

Resource Usage Note

By relating to this charm, other charms can directly allocate resources, such as managed disks and load balancers, which could lead to cloud charges and count against quotas. Because these resources are not managed by Juju, they will not be automatically deleted when the models or applications are destroyed, nor will they show up in Juju's status or GUI. It is therefore up to the operator to manually delete these resources when they are no longer needed, using the Azure management website or API.

Examples

Following are some examples using Azure integration with CDK.

Creating a pod with a Disk Storage-backed volume

This script creates a busybox pod with a persistent volume claim backed by Azure's Disk Storage.

#!/bin/bash

# create a storage class using the `kubernetes.io/azure-disk` provisioner
kubectl create -f - <<EOY
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: azure-standard
provisioner: kubernetes.io/azure-disk
parameters:
  storageaccounttype: Standard_LRS
  kind: managed
EOY

# create a persistent volume claim using that storage class
kubectl create -f - <<EOY
kind: PersistentVolumeClaim
apiVersion: v1
metadata:
  name: testclaim
spec:
  accessModes:
    - ReadWriteOnce
  resources:
    requests:
      storage: 100Mi
  storageClassName: azure-standard
EOY

# create the busybox pod with a volume using that PVC:
kubectl create -f - <<EOY
apiVersion: v1
kind: Pod
metadata:
  name: busybox
  namespace: default
spec:
  containers:
    - image: busybox
      command:
        - sleep
        - "3600"
      imagePullPolicy: IfNotPresent
      name: busybox
      volumeMounts:
        - mountPath: "/pv"
          name: testvolume
  restartPolicy: Always
  volumes:
    - name: testvolume
      persistentVolumeClaim:
        claimName: testclaim
EOY

Creating a service with an Azure load-balancer

The following script starts the hello-world pod behind an Azure-backed load-balancer.

#!/bin/bash

kubectl run hello-world --replicas=5 --labels="run=load-balancer-example" --image=gcr.io/google-samples/node-hello:1.0  --port=8080
kubectl expose deployment hello-world --type=LoadBalancer --name=hello
watch kubectl get svc -o wide --selector=run=load-balancer-example