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.

Prerequisites¶

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

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.
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¶

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 https://raw.githubusercontent.com/percona/percona-server-mongodb-operator/v1.14.0/deploy/bundle.yaml

Expected output

customresourcedefinition.apiextensions.k8s.io/perconaservermongodbs.psmdb.percona.com serverside-applied
customresourcedefinition.apiextensions.k8s.io/perconaservermongodbbackups.psmdb.percona.com serverside-applied
customresourcedefinition.apiextensions.k8s.io/perconaservermongodbrestores.psmdb.percona.com serverside-applied
role.rbac.authorization.k8s.io/percona-server-mongodb-operator serverside-applied
serviceaccount/percona-server-mongodb-operator serverside-applied
rolebinding.rbac.authorization.k8s.io/service-account-percona-server-mongodb-operator serverside-applied
deployment.apps/percona-server-mongodb-operator serverside-applied

The operator has been started, and you can deploy your MongoDB cluster:
```
$ kubectl apply -f https://raw.githubusercontent.com/percona/percona-server-mongodb-operator/v1.14.0/deploy/cr.yaml
```
Expected output
```
perconaservermongodb.psmdb.percona.com/my-cluster-name created
```
Note

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 v1.14.0 https://github.com/percona/percona-server-mongodb-operator
```
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.

You will need the login and password for the admin user to access the cluster. Use kubectl get secrets command to see the list of Secrets objects (by default the Secrets object you are interested in has my-cluster-name-secrets name). Then kubectl get secret my-cluster-name-secrets -o yaml command will return the YAML file with generated Secrets, including the MONGODB_DATABASE_ADMIN_USER and MONGODB_DATABASE_ADMIN_PASSWORD strings, which should look as follows:
```
...
data:
  ...
  MONGODB_DATABASE_ADMIN_PASSWORD: aDAzQ0pCY3NSWEZ2ZUIzS1I=
  MONGODB_DATABASE_ADMIN_USER: ZGF0YWJhc2VBZG1pbg==
```
Here the actual login name and password are base64-encoded. Use echo 'aDAzQ0pCY3NSWEZ2ZUIzS1I=' | base64 --decode command to bring it back to a human-readable form.
Run a container with a MongoDB client and connect its console output to your terminal. The following command will do this, naming the new Pod percona-client:
```
$ kubectl run -i --rm --tty percona-client --image=percona/percona-server-mongodb:4.4.18-18 --restart=Never -- bash -il
```
Executing it may require some time to deploy the correspondent Pod.
Now run mongo tool in the percona-client command shell using the login (which is normally databaseAdmin), a proper password 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:
if sharding is onif sharding is off
$ mongo "mongodb://databaseAdmin:databaseAdminPassword@my-cluster-name-mongos.<namespace name>.svc.cluster.local/admin?ssl=false"
$ mongo "mongodb+srv://databaseAdmin:databaseAdminPassword@my-cluster-name-rs0.<namespace name>.svc.cluster.local/admin?replicaSet=rs0&ssl=false"

Troubleshooting¶

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.

Warning

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

Contact Us

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Last update: 2023-09-11