Prerequisites

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

1. AWS Command Line Interface (AWS CLI) for interacting with the different parts of AWS. You can install it following the official installation instructions for your system.
2. eksctl to simplify cluster creation on EKS. It can be installed along its installation notes on GitHub.
3. kubectl to manage and deploy applications on Kubernetes. Install it following the official installation instructions.

Also, you need to configure AWS CLI with your credentials according to the official guide.

Create the EKS cluster

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

• name of your EKS cluster,
• AWS region in which you wish to deploy your cluster,
• the amount of nodes you would like tho have,
• the desired ratio between on-demand and spot instances in the total number of nodes.

The most easy and visually clear way is to describe the desired cluster in YAML and to pass this configuration to the eksctl command.

The following example configures a EKS cluster with one managed node group:

apiVersion: eksctl.io/v1alpha5
kind: ClusterConfig

metadata:
    name: test-cluster
    region: eu-west-2

nodeGroups:
    - name: ng-1
      minSize: 3
      maxSize: 5
      instancesDistribution:
        maxPrice: 0.15
        instanceTypes: ["m5.xlarge", "m5.2xlarge"] # At least two instance types should be specified
        onDemandBaseCapacity: 0
        onDemandPercentageAboveBaseCapacity: 50
        spotInstancePools: 2
      tags:
        'iit-billing-tag': 'cloud'
      preBootstrapCommands:
          - "echo 'OPTIONS=\"--default-ulimit nofile=1048576:1048576\"' >> /etc/sysconfig/docker"
          - "systemctl restart docker"

When the cluster configuration file is ready, you can actually create your cluster by the following command:

$ eksctl create cluster -f ~/cluster.yaml

Install the Operator

1. Create a namespace and set the context for the namespace. The resource names must be unique within the namespace and provide a way to divide cluster resources between users spread across multiple projects.

   So, create the namespace and save it in the namespace context for subsequent commands 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 was modified.

2. Use the following git clone command to download the correct branch of the percona-server-mongodb-operator repository:

   git clone -b v1.6.0 https://github.com/percona/percona-server-mongodb-operator
   

   After the repository is downloaded, change the directory to run the rest of the commands in this document:

   cd percona-server-mongodb-operator
   

3. Deploy the Operator with the following command:

   kubectl apply -f deploy/bundle.yaml
   

   The following confirmation is returned:

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

4. The operator has been started, and you can create the Percona Server for MongoDB:

   $ kubectl apply -f deploy/cr.yaml
   

   The creation process may take some time. The process is over when all Pods have reached their Running status. You can check it with the following command:

   kubectl get pods
   

   The result should look as follows:

   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-55659468f7-2kvc2            1/1     Running   0          11m
   my-cluster-name-mongos-55659468f7-7jfqc            1/1     Running   0          11m
   my-cluster-name-mongos-55659468f7-dfwcj            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-6fc78d686d-26hdz   1/1     Running   0          37m
   

5. During previous steps, the Operator has generated several secrets, including the password for the root user, which you will need to access the cluster.

   Use kubectl get secrets command to see the list of Secrets objects (by default Secrets object you are interested in has my-cluster-secrets name). Then kubectl get secret my-cluster-secrets -o yaml will return the YAML file with generated secrets, including the MONGODB_USER_ADMIN and MONGODB_USER_ADMIN_PASSWORD strings, which should look as follows:

   ...
   data:
     ...
     MONGODB_USER_ADMIN_PASSWORD: aDAzQ0pCY3NSWEZ2ZUIzS1I=
     MONGODB_USER_ADMIN_USER: dXNlckFkbWlu
   

   Here the actual password is base64-encoded, and echo 'aDAzQ0pCY3NSWEZ2ZUIzS1I=' | base64 --decode will bring it back to a human-readable form.

6. Check connectivity to a newly created cluster.

   First of all, 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:4.4.2-4 --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 userAdmin) and password obtained from the secret:

   mongo "mongodb://userAdmin:userAdminPassword@my-cluster-name-mongos.<namespace name>.svc.cluster.local/admin?ssl=false"