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Install Percona Server for MongoDB on Google Kubernetes Engine (GKE)

This guide shows you how to deploy Percona Operator for MongoDB on Google Kubernetes Engine (GKE). The document assumes some experience with the platform. For more information on the GKE, see the Kubernetes Engine Quickstart.


All commands from this guide can be run either in the Google Cloud shell or in your local shell.

To use Google Cloud shell, you need nothing but a modern web browser.

If you would like to use your local shell, install the following:

  1. gcloud. This tool is part of the Google Cloud SDK. To install it, select your operating system on the official Google Cloud SDK documentation page and then follow the instructions.

  2. kubectl. It is the Kubernetes command-line tool you will use to manage and deploy applications. To install the tool, run the following command:

    $ gcloud auth login
    $ gcloud components install kubectl

Create and configure the GKE cluster

You can configure the settings using the gcloud tool. You can run it either in the Cloud Shell or in your local shell (if you have installed Google Cloud SDK locally on the previous step). The following command will create a cluster named my-cluster-name:

$ gcloud container clusters create my-cluster-name --project <project name> --zone us-central1-a --cluster-version 1.23 --machine-type n1-standard-4 --num-nodes=3


You must edit the following command and other command-line statements to replace the <project name> placeholder with your project name. You may also be required to edit the zone location, which is set to us-central1 in the above example. Other parameters specify that we are creating a cluster with 3 nodes and with machine type of 4 vCPUs.

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

When the process is over, you can see it listed in the Google Cloud console

Select Kubernetes EngineClusters in the left menu panel:


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

In the Google Cloud Console, select your cluster and then click the Connect shown on the above image. You will see the connect statement which configures the command-line access. After you have edited the statement, you may run the command in your local shell:

$ gcloud container clusters get-credentials my-cluster-name --zone us-central1-a --project <project name>

Finally, use your Cloud Identity and Access Management (Cloud IAM) to control access to the cluster. The following command will give you the ability to create Roles and RoleBindings:

$ kubectl create clusterrolebinding cluster-admin-binding --clusterrole cluster-admin --user $(gcloud config get-value core/account)
Expected output created

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 (gke_<project name>_<zone location>_<cluster name>) was modified.

    Deploy the Operator using the following command:

    $ kubectl apply -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, one mongos node and one config server node. 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 v1.13.0

    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
You can also track the creation process in Google Cloud console via the Object Browser

When the creation process is finished, it will look as follows:


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.

  1. 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:


    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.

  2. 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:4.4.16-16 --restart=Never -- bash -il

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

  3. 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:

    $ 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"


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.

Alternatively, you can examine your Pods via the object browser

The errors will look as follows:


Clicking the problematic Pod will bring you to the details page with the same warning:


Removing the GKE cluster

There are several ways that you can delete the cluster.

You can clean up the cluster with the gcloud command as follows:

$ gcloud container clusters delete <cluster name>

The return statement requests your confirmation of the deletion. Type y to confirm.

Also, you can delete your cluster via the Google Cloud console

Just click the Delete popup menu item in the clusters list:


The cluster deletion may take time.


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

Last update: 2022-11-03