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Install Percona Server for MongoDB on Azure Kubernetes Service (AKS)

This guide shows you how to deploy Percona Operator for MongoDB on Microsoft Azure Kubernetes Service (AKS). The document assumes some experience with the platform. For more information on the AKS, see the Microsoft AKS official documentation .


The following tools are used in this guide and therefore should be preinstalled:

  1. Azure Command Line Interface (Azure CLI) for interacting with the different parts of AKS. You can install it following the official installation instructions for your system .

  2. kubectl to manage and deploy applications on Kubernetes. Install it following the official installation instructions .

Also, you need to sign in with Azure CLI using your credentials according to the official guide .

Create and configure the AKS cluster

To create your cluster, you will need the following data:

  • name of your AKS cluster,
  • an Azure resource group , in which resources of your cluster will be deployed and managed.
  • the amount of nodes you would like tho have.

You can create your cluster via command line using az aks create command. The following command will create a 3-node cluster named my-cluster-name within some already existing resource group named my-resource-group:

$ az aks create --resource-group my-resource-group --name my-cluster-name --enable-managed-identity --node-count 3 --node-vm-size Standard_B4ms --node-osdisk-size 30 --network-plugin kubenet  --generate-ssh-keys --outbound-type loadbalancer

Other parameters in the above example specify that we are creating a cluster with machine type of Standard_B4ms and OS disk size reduced to 30 GiB. You can see detailed information about cluster creation options in the AKS official documentation .

You may wait a few minutes for the cluster to be generated.

Now you should configure the command-line access to your newly created cluster to make kubectl be able to use it.

az aks get-credentials --resource-group my-resource-group --name my-cluster-name

Install the Operator and deploy your MongoDB cluster

  1. Deploy the Operator. By default deployment will be done in the default namespace. If that’s not the desired one, you can create a new namespace and/or set the context for the namespace as follows (replace the <namespace name> placeholder with some descriptive name):

    $ kubectl create namespace <namespace name>
    $ kubectl config set-context $(kubectl config current-context) --namespace=<namespace name>

    At success, you will see the message that namespace/<namespace name> was created, and the context (<cluster name>) was modified.

    Deploy the Operator using the following command:

    $ kubectl apply --server-side -f
    Expected output serverside-applied serverside-applied serverside-applied serverside-applied
    serviceaccount/percona-server-mongodb-operator serverside-applied serverside-applied
    deployment.apps/percona-server-mongodb-operator serverside-applied
  2. The operator has been started, and you can deploy your MongoDB cluster:

    $ kubectl apply -f
    Expected output created


    This deploys default MongoDB cluster configuration, three mongod, three mongos, and three config server instances. Please see deploy/cr.yaml and Custom Resource Options for the configuration options. You can clone the repository with all manifests and source code by executing the following command:

    $ git clone -b v1.16.2

    After editing the needed options, apply your modified deploy/cr.yaml file as follows:

    $ kubectl apply -f deploy/cr.yaml

    The creation process may take some time. When the process is over your cluster will obtain the ready status. You can check it with the following command:

    $ kubectl get psmdb
    Expected output
    NAME              ENDPOINT                                           STATUS   AGE
    my-cluster-name   my-cluster-name-mongos.default.svc.cluster.local   ready    5m26s

Verifying the cluster operation

It may take ten minutes to get the cluster started. When kubectl get psmdb command finally shows you the cluster status as ready, you can try to connect to the cluster.

To connect to Percona Server for MongoDB you need to construct the MongoDB connection URI string. It includes the credentials of the admin user, which are stored in the Secrets object.

  1. List the Secrets objects

    $ kubectl get secrets -n <namespace>

    The Secrets object you are interested in has the my-cluster-name-secrets name by default.

  2. View the Secret contents to retrive the admin user credentials.

    $ kubectl get secret my-cluster-name-secrets -o yaml
    The command returns the YAML file with generated Secrets, including the MONGODB_DATABASE_ADMIN_USER and MONGODB_DATABASE_ADMIN_PASSWORD strings, which should look as follows:

    Sample output

    The actual login name and password on the output are base64-encoded. To bring it back to a human-readable form, run:

    $ echo 'MONGODB_DATABASE_ADMIN_USER' | base64 --decode
    $ echo 'MONGODB_DATABASE_ADMIN_PASSWORD' | base64 --decode
  3. Run a container with a MongoDB client and connect its console output to your terminal. The following command does this, naming the new Pod percona-client:

    $ kubectl run -i --rm --tty percona-client --image=percona/percona-server-mongodb:7.0.8-5 --restart=Never -- bash -il

    Executing it may require some time to deploy the corresponding Pod.

  4. Now run mongosh tool inside the percona-client command shell using the admin user credentialds you obtained from the Secret, and a proper namespace name instead of the <namespace name> placeholder. The command will look different depending on whether sharding is on (the default behavior) or off:

    $ mongosh "mongodb://databaseAdmin:databaseAdminPassword@my-cluster-name-mongos.<namespace name>.svc.cluster.local/admin?ssl=false"
    $ mongosh "mongodb+srv://databaseAdmin:databaseAdminPassword@my-cluster-name-rs0.<namespace name>.svc.cluster.local/admin?replicaSet=rs0&ssl=false"


    If you are using MongoDB versions earler than 6.x (such as 5.0.26-22 instead of the default 7.0.8-5 variant), substitute mongosh command with mongo in the above examples.


If kubectl get psmdb command doesn’t show ready status too long, you can check the creation process with the kubectl get pods command:

$ kubectl get pods
Expected output
NAME                                               READY   STATUS    RESTARTS   AGE
my-cluster-name-cfg-0                              2/2     Running   0          11m
my-cluster-name-cfg-1                              2/2     Running   1          10m
my-cluster-name-cfg-2                              2/2     Running   1          9m
my-cluster-name-mongos-0                           1/1     Running   0          11m
my-cluster-name-mongos-1                           1/1     Running   0          11m
my-cluster-name-mongos-2                           1/1     Running   0          11m
my-cluster-name-rs0-0                              2/2     Running   0          11m
my-cluster-name-rs0-1                              2/2     Running   0          10m
my-cluster-name-rs0-2                              2/2     Running   0          9m
percona-server-mongodb-operator-665cd69f9b-xg5dl   1/1     Running   0          37m

If the command output had shown some errors, you can examine the problematic Pod with the kubectl describe <pod name> command as follows:

$ kubectl describe pod my-cluster-name-rs0-2

Review the detailed information for Warning statements and then correct the configuration. An example of a warning is as follows:

Warning FailedScheduling 68s (x4 over 2m22s) default-scheduler 0/1 nodes are available: 1 node(s) didn’t match pod affinity/anti-affinity, 1 node(s) didn’t satisfy existing pods anti-affinity rules.

Removing the AKS cluster

To delete your cluster, you will need the following data:

  • name of your AKS cluster,
  • AWS region in which you have deployed your cluster.

You can clean up the cluster with the az aks delete command as follows (with real names instead of <resource group> and <cluster name> placeholders):

$ az aks delete --name <cluster name> --resource-group <resource group> --yes --no-wait

It may take ten minutes to get the cluster actually deleted after executing this command.


After deleting the cluster, all data stored in it will be lost!

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Last update: 2024-07-23