How to Run HA MongoDB on IBM Cloud Kubernetes Service

This post is part of our ongoing series on running MongoDB on Kubernetes.  We’ve published a number of articles about running MongoDB on Kubernetes for specific platforms and for specific use cases.  If you are looking for a specific Kubernetes platform, check out these related articles.

Running HA MongoDB on Azure Kubernetes Service (AKS)
Running HA MongoDB on Amazon Elastic Container Service for Kubernetes (EKS)
Running HA MongoDB on Red Hat OpenShift
Running HA MongoDB on Google Kubernetes Engine (GKE)
Running HA MongoDB with Rancher Kubernetes Engine (RKE)
Running HA MongoDB on IBM Cloud Private
Failover MongoDB 300% faster and run only 1/3 the pods

And now, onto the post…

IBM Cloud Kubernetes Service is a managed Kubernetes offering running in IBM Cloud. It is designed to deliver powerful tools, intuitive user experience, and built-in security for rapid delivery of applications that can be bound to cloud services related to IBM Watson, IoT, DevOps and data analytics. As a CNCF certified Kubernetes provider, IBM Cloud Kubernetes Service provides intelligent scheduling, self-healing, horizontal scaling, service discovery and load balancing, automated rollouts and rollbacks, and secret and configuration management. The service also has advanced capabilities around simplified cluster management, container security, and isolation policies, the ability to design a cluster with a custom configuration and integrated operational tools for consistency in deployment.

Portworx is a cloud native storage platform to run persistent workloads deployed on a variety of orchestration engines including Kubernetes. With Portworx, customers can manage the database of their choice on any infrastructure using any container scheduler. It provides a single data management layer for all stateful services, no matter where they run.

This tutorial is a walk-through of the steps involved in deploying and managing a highly available MongoDB cluster on IBM Cloud Kubernetes Service (IKS).

In summary, to run HA MongoDB on IKS you need to:

• Launch an IKS cluster running on bare metal servers with software-defined storage (SDS)
• Install cloud native storage solution like Portworx as a Daemonset on IKS
• Create a storage class defining your storage requirements like replication factor, snapshot policy, and performance profile
• Deploy MongoDB using Kubernetes
• Test failover by killing or cordoning node in your cluster
• Expanding the volume size dynamically
• Perform backup and restore through snapshots

Launching an IKS Cluster

For running stateful workloads in a production environment backed by Portworx, it is highly recommended to launch an IKS cluster based on bare metal servers and software-defined storage. The minimum requirements of a worker node to successfully run Portworx include:

• 4 CPU cores
• 4GB memory
• 128GB of raw unformatted storage
• 10Gbps network speed

For details on launching a Kubernetes cluster with bare metal worker nodes, please refer to the documentation of IBM Cloud Kubernetes Service.

We are using an IKS cluster with 4 nodes out of which 3 nodes are running bare metal servers with SDS based on the instance type ms2c.4x32.1.9tb.ssd.encrypted. Only these machines that meet the prerequisite would be used by Portworx.

When we filter the nodes based on the label, we see the below nodes:

$ kubectl get nodes -l beta.kubernetes.io/instance-type=ms2c.4x32.1.9tb.ssd.encrypted
NAME           STATUS   ROLES    AGE    VERSION
10.177.26.18   Ready    <none>   4d7h   v1.13.2+IKS
10.185.22.28   Ready    <none>   4d7h   v1.13.2+IKS
10.73.90.131   Ready    <none>   4d3h   v1.13.2+IKS

To exclude nodes that don’t meet Portworx prerequisites, you can apply a label to skip the installation of Portworx. For example, the below command applies a label on the node with name 10.185.22.14 which doesn’t run on a bare metal server.

$ kubectl label nodes 10.185.22.14  px/enabled=false --overwrite

Installing Portworx in IKS

Installing Portworx on IKS is not very different from installing it on any other Kubernetes cluster. It is recommended that you create an etcd instance through Compose for etcd. You can use the Helm Chart to install Portworx cluster in IKS. Portworx documentation for IKS has the prerequisites and instructions to install and configure Portworx, STORK, and other components.

At the end of the installation, we will have Portworx Daemonset running on the nodes excluding those that are filtered out in the previous step.

Once the IKS cluster is up and running, and Portworx is installed and configured, we will deploy a highly available MongoDB database.

Creating a storage class for MongoDB

Once the IKS cluster is up and running, and Portworx is installed and configured, we will deploy a highly available MongoDB database.

Through storage class objects, an admin can define different classes of Portworx volumes that are offered in a cluster. These classes will be used during the dynamic provisioning of volumes. The storage class defines the replication factor, I/O profile (e.g., for a database or a CMS), and priority (e.g., SSD or HDD). These parameters impact the availability and throughput of workloads and can be specified for each volume. This is important because a production database will have different requirements than a development Jenkins cluster.

In this example, the storage class that we deploy has a replication factor of 3 with I/O profile set to “db,” and priority set to “high.” This means that the storage will be optimized for low latency database workloads like MongoDB and automatically placed on the highest performance storage available in the cluster.

$ cat > px-mongo-sc.yaml << EOF
kind: StorageClass
apiVersion: storage.k8s.io/v1beta1
metadata:
    name: px-ha-sc
provisioner: kubernetes.io/portworx-volume
parameters:
  repl: "3"
  io_profile: "db_remote"
  priority_io: "high"
  fs: "xfs"
EOF

Create the storage class and verify its available in the default namespace.

$ kubectl create -f px-mongo-sc.yaml
storageclass.storage.k8s.io/px-ha-sc created

$ kubectl get sc
NAME                         PROVISIONER                     AGE
default                      ibm.io/ibmc-file                8d
ibmc-file-bronze (default)   ibm.io/ibmc-file                8d
ibmc-file-custom             ibm.io/ibmc-file                8d
ibmc-file-gold               ibm.io/ibmc-file                8d
ibmc-file-retain-bronze      ibm.io/ibmc-file                8d
ibmc-file-retain-custom      ibm.io/ibmc-file                8d
ibmc-file-retain-gold        ibm.io/ibmc-file                8d
ibmc-file-retain-silver      ibm.io/ibmc-file                8d
ibmc-file-silver             ibm.io/ibmc-file                8d
portworx-db-sc               kubernetes.io/portworx-volume   12h
portworx-db2-sc              kubernetes.io/portworx-volume   12h
portworx-null-sc             kubernetes.io/portworx-volume   12h
portworx-shared-sc           kubernetes.io/portworx-volume   12h
px-ha-sc                     kubernetes.io/portworx-volume   19s
px-repl3-sc                  kubernetes.io/portworx-volume   34h
stork-snapshot-sc            stork-snapshot                  12h

Creating a MongoDB PVC on Kubernetes

We can now create a Persistent Volume Claim (PVC) based on the Storage Class. Thanks to dynamic provisioning, the claims will be created without explicitly provisioning a persistent volume (PV).

$ cat > px-mongo-pvc.yaml << EOF
kind: PersistentVolumeClaim
apiVersion: v1
metadata:
   name: px-mongo-pvc
   annotations:
     volume.beta.kubernetes.io/storage-class: px-ha-sc
spec:
   accessModes:
     - ReadWriteOnce
   resources:
     requests:
       storage: 1Gi
EOF

$ kubectl create -f px-mongo-pvc.yaml
persistentvolumeclaim/px-mongo-pvc created

$ kubectl get pvc
NAME           STATUS   VOLUME                                     CAPACITY   ACCESS MODES   STORAGECLASS   AGE
px-mongo-pvc   Bound    pvc-96a2ff1c-31a9-11e9-930d-4e511e6b17c9   1Gi        RWO            px-ha-sc       14s

Deploying MongoDB on IKS

Finally, let’s create a MongoDB instance as a Kubernetes deployment object. For simplicity’s sake, we will just be deploying a single Mongo pod. Because Portworx provides synchronous replication for High Availability, a single MongoDB instance might be the best deployment option for your MongoDB database. Portworx can also provide backing volumes for multi-node MongoDB replica sets. The choice is yours.

$ cat > px-mongo-app.yaml << EOF
apiVersion: apps/v1
kind: Deployment
metadata:
  name: mongo
spec:
  strategy:
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 1
    type: RollingUpdate
  replicas: 1
  selector:
    matchLabels:
      app: mongo  
  template:
    metadata:
      labels:
        app: mongo
    spec:
      schedulerName: stork
      containers:
      - name: mongo
        image: mongo
        imagePullPolicy: "Always"
        ports:
        - containerPort: 27017
        volumeMounts:
        - mountPath: /data/db
          name: mongodb
      volumes:
      - name: mongodb
        persistentVolumeClaim:
          claimName: px-mongo-pvc
EOF

$ kubectl create -f px-mongo-app.yaml
deployment.extensions/mongo created

The MongoDB deployment defined above is explicitly associated with the PVC, px-mongo-pvc created in the previous step.

This deployment creates a single pod running MongoDB backed by Portworx.

$ kubectl get pods
NAME                     READY     STATUS    RESTARTS   AGE
mongo-6bfc8ccbdc-jcwgg   0/1     ContainerCreating   0          12s

We can inspect the Portworx volume by accessing the pxctl tool running with the Mongo pod.

$ VOL=`kubectl get pvc | grep px-mongo-pvc | awk '{print $3}'`
$ PX_POD=$(kubectl get pods -l name=portworx -n kube-system -o jsonpath='{.items[0].metadata.name}')
$ kubectl exec -it $PX_POD -n kube-system -- /opt/pwx/bin/pxctl volume inspect ${VOL}
Volume	:  378818971230765330
	Name            	 :  pvc-96a2ff1c-31a9-11e9-930d-4e511e6b17c9
	Size            	 :  1.0 GiB
	Format          	 :  ext4
	HA              	 :  3
	IO Priority     	 :  LOW
	Creation time   	 :  Feb 16 05:13:26 UTC 2019
	Shared          	 :  no
	Status          	 :  up
	State           	 :  Attached: 6ab3face-615f-4cc7-bcfa-a1872d006e34 (10.185.22.29)
	Device Path     	 :  /dev/pxd/pxd378818971230765330
	Labels          	 :  pvc=px-mongo-pvc,namespace=default
	Reads           	 :  12
	Reads MS        	 :  32
	Bytes Read      	 :  49152
	Writes          	 :  159
	Writes MS       	 :  1180
	Bytes Written   	 :  18075648
	IOs in progress 	 :  0
	Bytes used      	 :  1.5 MiB
	Replica sets on nodes:
		Set 0
		  Node 		 : 10.73.90.131 (Pool 0)
		  Node 		 : 10.177.26.18 (Pool 0)
		  Node 		 : 10.185.22.29 (Pool 0)
	Replication Status	 :  Up
	Volume consumers	 :
		- Name           : mongo-6bfc8ccbdc-jcwgg (bf33a078-31a9-11e9-930d-4e511e6b17c9) (Pod)
		  Namespace      : default
		  Running on     : 10.185.22.29
		  Controlled by  : mongo-6bfc8ccbdc (ReplicaSet)

The output from the above command confirms the creation of volumes that are backing MongoDB database instance.

Failing over MongoDB pod on Kubernetes

Populating sample data

Let’s populate the database with some sample data.

We will first find the pod that’s running MongoDB to access the shell.

$ POD=`kubectl get pods -l app=mongo | grep Running | grep 1/1 | awk '{print $1}'`

$ kubectl exec -it $POD mongo
MongoDB shell version v4.0.0
connecting to: mongodb://127.0.0.1:27017
MongoDB server version: 4.0.0
Welcome to the MongoDB shell.
…..

Now that we are inside the shell, we can populate a collection.

db.ships.insert({name:'USS Enterprise-D',operator:'Starfleet',type:'Explorer',class:'Galaxy',crew:750,codes:[10,11,12]})
db.ships.insert({name:'USS Prometheus',operator:'Starfleet',class:'Prometheus',crew:4,codes:[1,14,17]})
db.ships.insert({name:'USS Defiant',operator:'Starfleet',class:'Defiant',crew:50,codes:[10,17,19]})
db.ships.insert({name:'IKS Buruk',operator:' Klingon Empire',class:'Warship',crew:40,codes:[100,110,120]})
db.ships.insert({name:'IKS Somraw',operator:' Klingon Empire',class:'Raptor',crew:50,codes:[101,111,120]})
db.ships.insert({name:'Scimitar',operator:'Romulan Star Empire',type:'Warbird',class:'Warbird',crew:25,codes:[201,211,220]})
db.ships.insert({name:'Narada',operator:'Romulan Star Empire',type:'Warbird',class:'Warbird',crew:65,codes:[251,251,220]})

Let’s run a few queries on the Mongo collection.

Find one arbitrary document:

db.ships.findOne()
{
	"_id" : ObjectId("5b5c16221108c314d4c000cd"),
	"name" : "USS Enterprise-D",
	"operator" : "Starfleet",
	"type" : "Explorer",
	"class" : "Galaxy",
	"crew" : 750,
	"codes" : [
		10,
		11,
		12
	]
}

Find all documents and using nice formatting:

db.ships.find().pretty()
…..
{
	"_id" : ObjectId("5b5c16221108c314d4c000d1"),
	"name" : "IKS Somraw",
	"operator" : " Klingon Empire",
	"class" : "Raptor",
	"crew" : 50,
	"codes" : [
		101,
		111,
		120
	]
}
{
	"_id" : ObjectId("5b5c16221108c314d4c000d2"),
	"name" : "Scimitar",
	"operator" : "Romulan Star Empire",
	"type" : "Warbird",
	"class" : "Warbird",
	"crew" : 25,
	"codes" : [
		201,
		211,
		220
	]
}
…..

Shows only the names of the ships:

db.ships.find({}, {name:true, _id:false})
{ "name" : "USS Enterprise-D" }
{ "name" : "USS Prometheus" }
{ "name" : "USS Defiant" }
{ "name" : "IKS Buruk" }
{ "name" : "IKS Somraw" }
{ "name" : "Scimitar" }
{ "name" : "Narada" }

Finds one document by attribute:

db.ships.findOne({'name':'USS Defiant'})
{
	"_id" : ObjectId("5b5c16221108c314d4c000cf"),
	"name" : "USS Defiant",
	"operator" : "Starfleet",
	"class" : "Defiant",
	"crew" : 50,
	"codes" : [
		10,
		17,
		19
	]
}

Exit from the client shell to return to the host.

Simulating node failure

Now, let’s simulate the node failure by cordoning off the node on which MongoDB is running.

$ NODE=`kubectl get pods -l app=mongo -o wide | grep -v NAME | awk '{print $7}'`

$ kubectl cordon ${NODE}
node/10.185.22.29 cordoned

The above command disabled scheduling on one of the nodes.

$ kubectl get nodes
NAME           STATUS                     ROLES    AGE     VERSION
10.177.26.18   Ready                         8d      v1.13.2+IKS
10.185.22.14   Ready                         8d      v1.13.2+IKS
10.185.22.29   Ready,SchedulingDisabled      7h29m   v1.13.2+IKS
10.73.90.131   Ready                         8d      v1.13.2+IKS

Now, let’s go ahead and delete the MongoDB pod.

$ POD=`kubectl get pods -l app=mongo -o wide | grep -v NAME | awk '{print $1}'`
$ kubectl delete pod ${POD}
pod "mongo-6bfc8ccbdc-jcwgg" deleted

As soon as the pod is deleted, it is relocated to the node with the replicated data. STorage ORchestrator for Kubernetes (STORK), a Portworx-contributed open source storage scheduler, co-locates the pod on the exact node where the data is stored. It ensures that an appropriate node is selected for scheduling the pod.

Let’s verify this by running the below command. We will notice that a new pod has been created and scheduled in a different node.

$ kubectl get pods -l app=mongo -o wide
NAME                     READY   STATUS    RESTARTS   AGE   IP             NODE           NOMINATED NODE   READINESS GATES
mongo-6bfc8ccbdc-cl8nw   1/1     Running   0          13s   172.30.59.94   10.177.26.18              

Let’s uncordon the node to bring it back to action.

$ kubectl uncordon ${NODE}
node/10.185.22.29 uncordoned

Finally, let’s verify that the data is still available.

Verifying that the data is intact

Let’s find the pod name and run the ‘exec’ command, and then access the Mongo shell.

$ POD=`kubectl get pods -l app=mongo | grep Running | grep 1/1 | awk '{print $1}'`
$ kubectl exec -it $POD mongo
MongoDB shell version v4.0.0
connecting to: mongodb://127.0.0.1:27017
MongoDB server version: 4.0.0
Welcome to the MongoDB shell.
…..

We will query the collection to verify that the data is intact.

Find one arbitrary document:

db.ships.findOne()
{
	"_id" : ObjectId("5b5c16221108c314d4c000cd"),
	"name" : "USS Enterprise-D",
	"operator" : "Starfleet",
	"type" : "Explorer",
	"class" : "Galaxy",
	"crew" : 750,
	"codes" : [
		10,
		11,
		12
	]
}

Find all documents and using nice formatting:

db.ships.find().pretty()
…..
{
	"_id" : ObjectId("5b5c16221108c314d4c000d1"),
	"name" : "IKS Somraw",
	"operator" : " Klingon Empire",
	"class" : "Raptor",
	"crew" : 50,
	"codes" : [
		101,
		111,
		120
	]
}
{
	"_id" : ObjectId("5b5c16221108c314d4c000d2"),
	"name" : "Scimitar",
	"operator" : "Romulan Star Empire",
	"type" : "Warbird",
	"class" : "Warbird",
	"crew" : 25,
	"codes" : [
		201,
		211,
		220
	]
}
…..

Shows only the names of the ships:

db.ships.find({}, {name:true, _id:false})
{ "name" : "USS Enterprise-D" }
{ "name" : "USS Prometheus" }
{ "name" : "USS Defiant" }
{ "name" : "IKS Buruk" }
{ "name" : "IKS Somraw" }
{ "name" : "Scimitar" }
{ "name" : "Narada" }

Finds one document by attribute:

db.ships.findOne({'name':Narada'})
{
	"_id" : ObjectId("5b5c16221108c314d4c000d3"),
	"name" : "Narada",
	"operator" : "Romulan Star Empire",
	"type" : "Warbird",
	"class" : "Warbird",
	"crew" : 65,
	"codes" : [
		251,
		251,
		220
	]
}

Observe that the MongoDB collection is still there and all the content is intact! Exit from the client shell to return to the host.

Performing Storage Operations on MongoDB

After testing end-to-end failover of the database, let’s perform StorageOps on our IKS cluster.

Expanding the Kubernetes Volume with no downtime

Currently, the Portworx volume that we created at the beginning is of 1Gib size. We will now expand it to double the storage capacity.

First, let’s get the volume name and inspect it through the pxctl tool.

$ VOL=`kubectl get pvc | grep px-mongo-pvc | awk '{print $3}'`
$ PX_POD=$(kubectl get pods -l name=portworx -n kube-system -o jsonpath='{.items[0].metadata.name}')
$ kubectl exec -it $PX_POD -n kube-system -- /opt/pwx/bin/pxctl volume inspect ${VOL}
Volume	:  378818971230765330
	Name            	 :  pvc-96a2ff1c-31a9-11e9-930d-4e511e6b17c9
	Size            	 :  1.0 GiB
	Format          	 :  ext4
	HA              	 :  3
	IO Priority     	 :  LOW
	Creation time   	 :  Feb 16 05:13:26 UTC 2019
	Shared          	 :  no
	Status          	 :  up
	State           	 :  Attached: d7f53ebb-0d02-4ba4-b689-2f335e8f9379 (10.177.26.18)
	Device Path     	 :  /dev/pxd/pxd378818971230765330
	Labels          	 :  namespace=default,pvc=px-mongo-pvc
	Reads           	 :  50
	Reads MS        	 :  84
	Bytes Read      	 :  303104
	Writes          	 :  486
	Writes MS       	 :  3352
	Bytes Written   	 :  316612608
	IOs in progress 	 :  0
	Bytes used      	 :  3.5 MiB
	Replica sets on nodes:
		Set 0
		  Node 		 : 10.73.90.131 (Pool 0)
		  Node 		 : 10.177.26.18 (Pool 0)
		  Node 		 : 10.185.22.29 (Pool 0)
	Replication Status	 :  Up
	Volume consumers	 :
		- Name           : mongo-6bfc8ccbdc-cl8nw (5da69447-31aa-11e9-930d-4e511e6b17c9) (Pod)
		  Namespace      : default
		  Running on     : 10.177.26.18
		  Controlled by  : mongo-6bfc8ccbdc (ReplicaSet)

Notice the current Portworx volume. It is 1GiB. Let’s expand it to 2GiB.

$ kubectl exec -it $PX_POD -n kube-system -- /opt/pwx/bin/pxctl volume update $VOL --size=2
Update Volume: Volume update successful for volume pvc-96a2ff1c-31a9-11e9-930d-4e511e6b17c9

Check the new volume size. It is expanded to 2GiB.

$ kubectl exec -it $PX_POD -n kube-system -- /opt/pwx/bin/pxctl volume inspect ${VOL}
Volume	:  378818971230765330
	Name            	 :  pvc-96a2ff1c-31a9-11e9-930d-4e511e6b17c9
	Size            	 :  2.0 GiB
	Format          	 :  ext4
	HA              	 :  3
	IO Priority     	 :  LOW
	Creation time   	 :  Feb 16 05:13:26 UTC 2019
	Shared          	 :  no
	Status          	 :  up
	State           	 :  Attached: d7f53ebb-0d02-4ba4-b689-2f335e8f9379 (10.177.26.18)
	Device Path     	 :  /dev/pxd/pxd378818971230765330
	Labels          	 :  namespace=default,pvc=px-mongo-pvc
	Reads           	 :  109
	Reads MS        	 :  252
	Bytes Read      	 :  577536
	Writes          	 :  571
	Writes MS       	 :  3740
	Bytes Written   	 :  318443520
	IOs in progress 	 :  0
	Bytes used      	 :  3.5 MiB
	Replica sets on nodes:
		Set 0
		  Node 		 : 10.73.90.131 (Pool 0)
		  Node 		 : 10.177.26.18 (Pool 0)
		  Node 		 : 10.185.22.29 (Pool 0)
	Replication Status	 :  Up
	Volume consumers	 :
		- Name           : mongo-6bfc8ccbdc-cl8nw (5da69447-31aa-11e9-930d-4e511e6b17c9) (Pod)
		  Namespace      : default
		  Running on     : 10.177.26.18
		  Controlled by  : mongo-6bfc8ccbdc (ReplicaSet)

Taking Snapshots of a Kubernetes volume and restoring the database

Portworx supports creating snapshots for Kubernetes PVCs.

Let’s create a snapshot of the PVC we created for MongoDB.

cat > px-mongo-snap.yaml << EOF
apiVersion: volumesnapshot.external-storage.k8s.io/v1
kind: VolumeSnapshot
metadata:
  name: px-mongo-snapshot
  namespace: default
spec:
  persistentVolumeClaimName: px-mongo-pvc
EOF

$ kubectl create -f px-mongo-snap.yaml
volumesnapshot.volumesnapshot.external-storage.k8s.io/px-mongo-snapshot created

Verify the creation of volume snapshot.

$ kubectl get volumesnapshot
NAME                AGE
px-mongo-snapshot   11s

$ kubectl get volumesnapshotdatas
NAME                                                       AGE
k8s-volume-snapshot-51c09f48-31ab-11e9-993d-eaa7125cd4d9   23s

With the snapshot in place, let’s go ahead and delete the database.

$ POD=`kubectl get pods -l app=mongo | grep Running | grep 1/1 | awk '{print $1}'`
$ kubectl exec -it $POD mongo

db.ships.drop()

Since snapshots are just like volumes, we can use it to start a new instance of MongoDB. Let’s create a new instance of MongoDB by restoring the snapshot data.

$ cat > px-mongo-snap-pvc << EOF
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: px-mongo-snap-clone
  annotations:
    snapshot.alpha.kubernetes.io/snapshot: px-mongo-snapshot
spec:
  accessModes:
     - ReadWriteOnce
  storageClassName: stork-snapshot-sc
  resources:
    requests:
      storage: 2Gi
EOF

$ kubectl create -f px-mongo-snap-pvc.yaml
persistentvolumeclaim "px-mongo-snap-clone" created

From the new PVC, we will create a MongoDB pod.

cat < px-mongo-snap-restore.yaml >> EOF
apiVersion: apps/v1
kind: Deployment
metadata:
  name: mongo-snap
spec:
  strategy:
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 1
    type: RollingUpdate
  replicas: 1
  selector:
    matchLabels:
      app: mongo-snap
  template:
    metadata:
      labels:
        app: mongo-snap
    spec:
      affinity:
        nodeAffinity:
          requiredDuringSchedulingIgnoredDuringExecution:
            nodeSelectorTerms:
            - matchExpressions:
              - key: px/running
                operator: NotIn
                values:
                - "false"
              - key: px/enabled
                operator: NotIn
                values:
                - "false"
    spec:
      containers:
      - name: mongo
        image: mongo
        imagePullPolicy: "Always"
        ports:
        - containerPort: 27017
        volumeMounts:
        - mountPath: /data/db
          name: mongodb
      volumes:
      - name: mongodb
        persistentVolumeClaim:
          claimName: px-mongo-snap-clone
EOF

$ kubectl create -f px-mongo-snap-restore.yaml
deployment.extensions/mongo-snap created

Verify that the new pod is in the Running state.

$ kubectl get pods -l app=mongo-snap
NAME                         READY     STATUS    RESTARTS   AGE
mongo-snap-6b885ddb9b-tf7zc   1/1       Running   0          5m

Finally, let’s access the sample data created earlier in the walk-through.

$ POD=`kubectl get pods -l app=mongo-snap | grep Running | grep 1/1 | awk '{print $1}'`
$ kubectl exec -it $POD mongo
MongoDB shell version v4.0.0
connecting to: mongodb://127.0.0.1:27017
MongoDB server version: 4.0.0
Welcome to the MongoDB shell.
…..
sdb.ships.find({}, {name:true, _id:false})
{ "name" : "USS Enterprise-D" }
{ "name" : "USS Prometheus" }
{ "name" : "USS Defiant" }
{ "name" : "IKS Buruk" }
{ "name" : "IKS Somraw" }
{ "name" : "Scimitar" }
{ "name" : "Narada" }

Notice that the collection is still there with the data intact. We can also push the snapshot to an Amazon S3-compatible object storage service if we want to create a disaster recovery backup in another region or location. Since Portworx snapshots work with any S3 compatible object storage, the backup can go to a different cloud or even an on-premises data center.

Summary

Portworx can be easily deployed on IBM Cloud Kubernetes Service to run stateful workloads in production. Through the integration of STORK, DevOps and StorageOps teams can seamlessly run highly available database clusters in IKS. They can perform traditional operations such as volume expansion, backup, and recovery for the cloud native applications in an automated and efficient manner.