Overview
KubeDB is the Kubernetes Native Database Management Solution which simplifies and automates routine database tasks such as Provisioning, Monitoring, Upgrading, Patching, Scaling, Volume Expansion, Backup, Recovery, Failure detection, and Repair for various popular databases on private and public clouds. The databases that KubeDB supports are MongoDB, Elasticsearch, MySQL, MariaDB, Kafka, Redis, PostgreSQL, ProxySQL, Percona XtraDB, Memcached and PgBouncer. You can find the guides to all the supported databases in KubeDB . In this tutorial we will deploy and manage MongoDB sharded cluster in Google Kubernetes Engine (GKE). We will cover the following steps:
- Install KubeDB
- Deploy MongoDB Sharded Cluster
- Horizontal Scaling of MongoDB Sharded Cluster
- Vertical Scaling of MongoDB Sharded Cluster
Get Cluster ID
We need the cluster ID to get the KubeDB License. To get cluster ID, we can run the following command:
$ kubectl get ns kube-system -o jsonpath='{.metadata.uid}'
fc435a61-c74b-9243-83a5-f1110ef2462c
Get License
Go to Appscode License Server to get the license.txt file. For this tutorial we will use KubeDB Enterprise Edition.
Install KubeDB
We will use helm to install KubeDB. Please install helm here
if it is not already installed.
Now, let’s install KubeDB.
$ helm repo add appscode https://charts.appscode.com/stable/
$ helm repo update
$ helm search repo appscode/kubedb
NAME CHART VERSION APP VERSION DESCRIPTION
appscode/kubedb v2023.04.10 v2023.04.10 KubeDB by AppsCode - Production ready databases...
appscode/kubedb-autoscaler v0.18.0 v0.18.1 KubeDB Autoscaler by AppsCode - Autoscale KubeD...
appscode/kubedb-catalog v2023.04.10 v2023.04.10 KubeDB Catalog by AppsCode - Catalog for databa...
appscode/kubedb-community v0.24.2 v0.24.2 KubeDB Community by AppsCode - Community featur...
appscode/kubedb-crds v2023.04.10 v2023.04.10 KubeDB Custom Resource Definitions
appscode/kubedb-dashboard v0.9.0 v0.9.1 KubeDB Dashboard by AppsCode
appscode/kubedb-enterprise v0.11.2 v0.11.2 KubeDB Enterprise by AppsCode - Enterprise feat...
appscode/kubedb-grafana-dashboards v2023.04.10 v2023.04.10 A Helm chart for kubedb-grafana-dashboards by A...
appscode/kubedb-metrics v2023.04.10 v2023.04.10 KubeDB State Metrics
appscode/kubedb-one v2023.04.10 v2023.04.10 KubeDB and Stash by AppsCode - Production ready...
appscode/kubedb-ops-manager v0.20.0 v0.20.1 KubeDB Ops Manager by AppsCode - Enterprise fea...
appscode/kubedb-opscenter v2023.04.10 v2023.04.10 KubeDB Opscenter by AppsCode
appscode/kubedb-provisioner v0.33.0 v0.33.1 KubeDB Provisioner by AppsCode - Community feat...
appscode/kubedb-schema-manager v0.9.0 v0.9.1 KubeDB Schema Manager by AppsCode
appscode/kubedb-ui v2023.03.23 0.3.28 A Helm chart for Kubernetes
appscode/kubedb-ui-server v2021.12.21 v2021.12.21 A Helm chart for kubedb-ui-server by AppsCode
appscode/kubedb-webhook-server v0.9.0 v0.9.1 KubeDB Webhook Server by AppsCode
# Install KubeDB Enterprise operator chart
$ helm install kubedb appscode/kubedb \
--version v2023.04.10 \
--namespace kubedb --create-namespace \
--set kubedb-provisioner.enabled=true \
--set kubedb-ops-manager.enabled=true \
--set kubedb-autoscaler.enabled=true \
--set kubedb-dashboard.enabled=true \
--set kubedb-schema-manager.enabled=true \
--set-file global.license=/path/to/the/license.txt
Let’s verify the installation:
$ kubectl get pods --all-namespaces -l "app.kubernetes.io/instance=kubedb"
NAMESPACE NAME READY STATUS RESTARTS AGE
kubedb kubedb-kubedb-autoscaler-85895f47cb-rzv6s 1/1 Running 0 65s
kubedb kubedb-kubedb-dashboard-5f87f84766-xth6m 1/1 Running 0 65s
kubedb kubedb-kubedb-ops-manager-59fd4d55b4-npfvk 1/1 Running 0 65s
kubedb kubedb-kubedb-provisioner-77888c5899-x48kp 1/1 Running 0 65s
kubedb kubedb-kubedb-schema-manager-8547689c5-4mzxl 1/1 Running 0 65s
kubedb kubedb-kubedb-webhook-server-57c7fbdd5d-cprrc 1/1 Running 0 65s
We can list the CRD Groups that have been registered by the operator by running the following command:
$ kubectl get crd -l app.kubernetes.io/name=kubedb
NAME CREATED AT
elasticsearchautoscalers.autoscaling.kubedb.com 2023-06-07T05:41:17Z
elasticsearchdashboards.dashboard.kubedb.com 2023-06-07T05:41:19Z
elasticsearches.kubedb.com 2023-06-07T05:41:15Z
elasticsearchopsrequests.ops.kubedb.com 2023-06-07T05:41:16Z
elasticsearchversions.catalog.kubedb.com 2023-06-07T05:38:36Z
etcds.kubedb.com 2023-06-07T05:41:17Z
etcdversions.catalog.kubedb.com 2023-06-07T05:38:36Z
kafkas.kubedb.com 2023-06-07T05:41:20Z
kafkaversions.catalog.kubedb.com 2023-06-07T05:38:37Z
mariadbautoscalers.autoscaling.kubedb.com 2023-06-07T05:41:17Z
mariadbdatabases.schema.kubedb.com 2023-06-07T05:41:14Z
mariadbopsrequests.ops.kubedb.com 2023-06-07T05:41:30Z
mariadbs.kubedb.com 2023-06-07T05:41:14Z
mariadbversions.catalog.kubedb.com 2023-06-07T05:38:37Z
memcacheds.kubedb.com 2023-06-07T05:41:17Z
memcachedversions.catalog.kubedb.com 2023-06-07T05:38:37Z
mongodbautoscalers.autoscaling.kubedb.com 2023-06-07T05:41:17Z
mongodbdatabases.schema.kubedb.com 2023-06-07T05:41:14Z
mongodbopsrequests.ops.kubedb.com 2023-06-07T05:41:19Z
mongodbs.kubedb.com 2023-06-07T05:41:14Z
mongodbversions.catalog.kubedb.com 2023-06-07T05:38:37Z
mysqlautoscalers.autoscaling.kubedb.com 2023-06-07T05:41:17Z
mysqldatabases.schema.kubedb.com 2023-06-07T05:41:13Z
mysqlopsrequests.ops.kubedb.com 2023-06-07T05:41:27Z
mysqls.kubedb.com 2023-06-07T05:41:13Z
mysqlversions.catalog.kubedb.com 2023-06-07T05:38:38Z
perconaxtradbautoscalers.autoscaling.kubedb.com 2023-06-07T05:41:17Z
perconaxtradbopsrequests.ops.kubedb.com 2023-06-07T05:41:44Z
perconaxtradbs.kubedb.com 2023-06-07T05:41:19Z
perconaxtradbversions.catalog.kubedb.com 2023-06-07T05:38:38Z
pgbouncers.kubedb.com 2023-06-07T05:41:19Z
pgbouncerversions.catalog.kubedb.com 2023-06-07T05:38:38Z
postgresautoscalers.autoscaling.kubedb.com 2023-06-07T05:41:17Z
postgresdatabases.schema.kubedb.com 2023-06-07T05:41:14Z
postgreses.kubedb.com 2023-06-07T05:41:14Z
postgresopsrequests.ops.kubedb.com 2023-06-07T05:41:37Z
postgresversions.catalog.kubedb.com 2023-06-07T05:38:39Z
proxysqlautoscalers.autoscaling.kubedb.com 2023-06-07T05:41:17Z
proxysqlopsrequests.ops.kubedb.com 2023-06-07T05:41:41Z
proxysqls.kubedb.com 2023-06-07T05:41:20Z
proxysqlversions.catalog.kubedb.com 2023-06-07T05:38:39Z
publishers.postgres.kubedb.com 2023-06-07T05:41:54Z
redisautoscalers.autoscaling.kubedb.com 2023-06-07T05:41:17Z
redises.kubedb.com 2023-06-07T05:41:20Z
redisopsrequests.ops.kubedb.com 2023-06-07T05:41:34Z
redissentinelautoscalers.autoscaling.kubedb.com 2023-06-07T05:41:17Z
redissentinelopsrequests.ops.kubedb.com 2023-06-07T05:41:47Z
redissentinels.kubedb.com 2023-06-07T05:41:20Z
redisversions.catalog.kubedb.com 2023-06-07T05:38:39Z
subscribers.postgres.kubedb.com 2023-06-07T05:41:57Z
Deploy MongoDB Sharded Cluster
We are going to Deploy MongoDB Sharded Cluster by using KubeDB. First, let’s create a Namespace in which we will deploy the database.
$ kubectl create namespace demo
namespace/demo created
Here is the yaml of the MongoDB CRO we are going to use:
apiVersion: kubedb.com/v1alpha2
kind: MongoDB
metadata:
name: mongodb-shard
namespace: demo
spec:
version: 6.0.5
shardTopology:
configServer:
replicas: 3
storage:
resources:
requests:
storage: 512Mi
storageClassName: standard
mongos:
replicas: 2
shard:
replicas: 3
shards: 2
storage:
resources:
requests:
storage: 512Mi
storageClassName: standard
terminationPolicy: WipeOut
Let’s save this yaml configuration into mongodb-shard.yaml
Then create the above MongoDB CRO
$ kubectl apply -f mongodb-shard.yaml
mongodb.kubedb.com/mongodb-shard created
In this yaml,
- In this yaml we can see in the
spec.versionfield specifies the version of MongoDB. Here, we are using MongoDBversion 6.0.5. You can list the KubeDB supported versions of MongoDB by running$ kubectl get mongodbversionscommand. spec.shardTopologyrepresents the topology configuration for sharding.spec.shardTopology.configServerdefines configuration for ConfigServer component of mongodb.spec.shardTopology.configServer.replicasrepresents number of replicas for configServer replicaset.spec.shardTopology.mongosdefines configuration for Mongos component of mongodb. Mongos instances run as stateless components (deployment).spec.shardTopology.mongos.replicasspecifies number of replicas of Mongos instance. Here, Mongos is not deployed as replicaset.spec.storage.storageClassNameis the name of the StorageClass used to provision PVCs.spec.terminationPolicyfield is Wipeout means that the database will be deleted without restrictions. It can also be “Halt”, “Delete” and “DoNotTerminate”. Learn More about these checkout Termination Policy .
Once these are handled correctly and the MongoDB object is deployed, you will see that the following objects are created:
$ kubectl get all -n demo
NAME READY STATUS RESTARTS AGE
pod/mongodb-shard-configsvr-0 1/1 Running 0 4m51s
pod/mongodb-shard-configsvr-1 1/1 Running 0 3m56s
pod/mongodb-shard-configsvr-2 1/1 Running 0 3m11s
pod/mongodb-shard-mongos-0 1/1 Running 0 89s
pod/mongodb-shard-mongos-1 1/1 Running 0 67s
pod/mongodb-shard-shard0-0 1/1 Running 0 4m51s
pod/mongodb-shard-shard0-1 1/1 Running 0 3m55s
pod/mongodb-shard-shard0-2 1/1 Running 0 2m32s
pod/mongodb-shard-shard1-0 1/1 Running 0 4m51s
pod/mongodb-shard-shard1-1 1/1 Running 0 3m53s
pod/mongodb-shard-shard1-2 1/1 Running 0 2m19s
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/mongodb-shard ClusterIP 10.0.162.224 <none> 27017/TCP 4m52s
service/mongodb-shard-configsvr-pods ClusterIP None <none> 27017/TCP 4m52s
service/mongodb-shard-mongos-pods ClusterIP None <none> 27017/TCP 4m52s
service/mongodb-shard-shard0-pods ClusterIP None <none> 27017/TCP 4m52s
service/mongodb-shard-shard1-pods ClusterIP None <none> 27017/TCP 4m52s
NAME READY AGE
statefulset.apps/mongodb-shard-configsvr 3/3 4m52s
statefulset.apps/mongodb-shard-mongos 2/2 90s
statefulset.apps/mongodb-shard-shard0 3/3 4m52s
statefulset.apps/mongodb-shard-shard1 3/3 4m52s
NAME TYPE VERSION AGE
appbinding.appcatalog.appscode.com/mongodb-shard kubedb.com/mongodb 6.0.5 49s
NAME VERSION STATUS AGE
mongodb.kubedb.com/mongodb-shard 6.0.5 Ready 5m2s
Let’s check if the database is ready to use,
$ kubectl get mongodb -n demo mongodb-shard
NAME VERSION STATUS AGE
mongodb-shard 6.0.5 Ready 5m38s
We have successfully deployed MongoDB shard in GKE. Now we can exec into the container to use the database.
Accessing Database Through CLI
To access the database through CLI, we have to get the credentials to access. Let’s export the credentials as environment variable to our current shell :
Export the Credentials
KubeDB will create Secret and Service for the database mongodb-shard that we have deployed. Let’s check them using the following commands,
$ kubectl get secret -n demo -l=app.kubernetes.io/instance=mongodb-shard
NAME TYPE DATA AGE
mongodb-shard-auth kubernetes.io/basic-auth 2 6m27s
mongodb-shard-key Opaque 1 6m27s
$ kubectl get service -n demo -l=app.kubernetes.io/instance=mongodb-shard
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
mongodb-shard ClusterIP 10.0.162.224 <none> 27017/TCP 7m6s
mongodb-shard-configsvr-pods ClusterIP None <none> 27017/TCP 7m6s
mongodb-shard-mongos-pods ClusterIP None <none> 27017/TCP 7m6s
mongodb-shard-shard0-pods ClusterIP None <none> 27017/TCP 7m6s
mongodb-shard-shard1-pods ClusterIP None <none> 27017/TCP 7m6s
Now, we are going to use mongodb-shard-auth to export credentials.
Let’s export the USER and PASSWORD as environment variables to make further commands re-usable.
$ export USER=$(kubectl get secrets -n demo mongodb-shard-auth -o jsonpath='{.data.\username}' | base64 -d)
$ export PASSWORD=$(kubectl get secrets -n demo mongodb-shard-auth -o jsonpath='{.data.\password}' | base64 -d)
Insert Sample Data
In this section, we are going to login into our MongoDB shard pod and insert some sample data.
$ kubectl exec -it -n demo mongodb-shard-shard0-0 -- mongosh admin -u $USER -p $PASSWORD
Defaulted container "mongodb" out of: mongodb, copy-config (init)
Using MongoDB: 6.0.5
Using Mongosh: 1.8.2
shard0 [direct: primary] admin> show dbs
admin 132.00 KiB
config 1.52 MiB
kubedb-system 60.00 KiB
local 796.00 KiB
shard0 [direct: primary] admin> use musicdb
switched to db musicdb
shard0 [direct: primary] musicdb> db.songs.insert({"name":"Annie's Song"});
DeprecationWarning: Collection.insert() is deprecated. Use insertOne, insertMany, or bulkWrite.
{
acknowledged: true,
insertedIds: { '0': ObjectId("64801d42029dd4780b0e573b") }
}
shard0 [direct: primary] musicdb> db.songs.find().pretty()
[ { _id: ObjectId("64801d42029dd4780b0e573b"), name: "Annie's Song" } ]
shard0 [direct: primary] musicdb> exit
We’ve successfully inserted some sample data to our database. More information about Run & Manage MongoDB on Kubernetes can be found HERE
Horizontal Scaling of MongoDB Sharded Cluster
Horizontal Scale Up
Here, we are going to scale up the number of MongoDB shard and also their replicas to meet the desired number of replicas. Before applying Horizontal Scaling, let’s check the current number of MongoDB shard and their replicas,
$ kubectl get mongodb -n demo mongodb-shard -o json | jq '.spec.shardTopology.shard.shards'
2
$ kubectl get mongodb -n demo mongodb-shard -o json | jq '.spec.shardTopology.shard.replicas'
3
Create MongoDBOpsRequest
In order to scale up, we have to create a MongoDBOpsRequest CR with our desired replicas. Let’s create it using this following yaml,
apiVersion: ops.kubedb.com/v1alpha1
kind: MongoDBOpsRequest
metadata:
name: horizontal-scale-up
namespace: demo
spec:
type: HorizontalScaling
databaseRef:
name: mongodb-shard
horizontalScaling:
shard:
shards: 3
replicas: 4
In this yaml,
spec.databaseRef.namespecifies that we are performing horizontal scaling operation onmongodb-sharddatabase.spec.typespecifies that we are performingHorizontalScalingon our database.spec.horizontalScaling.shard.shardsspecifies the desired number of shards after scaling.spec.horizontalScaling.shard.replicasspecifies the desired number of shard replicas after scaling.
Let’s save this yaml configuration into horizontal-scale-up.yaml and apply it,
$ kubectl apply -f horizontal-scale-up.yaml
mongodbopsrequest.ops.kubedb.com/horizontal-scale-up created
Let’s wait for MongoDBOpsRequest STATUS to be Successful. Run the following command to watch MongoDBOpsRequest CR,
$ watch kubectl get mongodbopsrequest -n demo
NAME TYPE STATUS AGE
horizontal-scale-up HorizontalScaling Successful 2m29s
From the above output we can see that the MongoDBOpsRequest has succeeded. Now, we are going to verify the number of shard and their replicas,
$ kubectl get mongodb -n demo mongodb-shard -o json | jq '.spec.shardTopology.shard.shards'
3
$ kubectl get mongodb -n demo mongodb-shard -o json | jq '.spec.shardTopology.shard.replicas'
4
From all the above outputs we can see that the number of shards is now increased to 3 and also, their replicas increased to 4. That means we have successfully scaled up the number of shards and their replicas.
Horizontal Scale Down
Now, we are going to scale down the number of MongoDB shard and also their replicas to meet the desired number of replicas.
Create MongoDBOpsRequest
In order to scale down, again we need to create a MongoDBOpsRequest CR with our desired replicas. Let’s create it using this following yaml,
apiVersion: ops.kubedb.com/v1alpha1
kind: MongoDBOpsRequest
metadata:
name: horizontal-scale-down
namespace: demo
spec:
type: HorizontalScaling
databaseRef:
name: mongodb-shard
horizontalScaling:
shard:
shards: 2
replicas: 3
In this yaml,
spec.databaseRef.namespecifies that we are performing horizontal scaling operation onmongodb-sharddatabase.spec.typespecifies that we are performingHorizontalScalingon our database.spec.horizontalScaling.shard.shardsspecifies the desired number of shards after scaling.spec.horizontalScaling.shard.replicasspecifies the desired number of shard replicas after scaling.
Let’s save this yaml configuration into horizontal-scale-down.yaml and apply it,
$ kubectl apply -f horizontal-scale-down.yaml
mongodbopsrequest.ops.kubedb.com/horizontal-scale-down created
Let’s wait for MongoDBOpsRequest STATUS to be Successful. Run the following command to watch MongoDBOpsRequest CR,
$ watch kubectl get mongodbopsrequest -n demo
NAME TYPE STATUS AGE
horizontal-scale-down HorizontalScaling Successful 2m37s
From the above output we can see that the MongoDBOpsRequest has succeeded. Now, we are going to verify the number of shard and their replicas,
$ kubectl get mongodb -n demo mongodb-shard -o json | jq '.spec.shardTopology.shard.shards'
2
$ kubectl get mongodb -n demo mongodb-shard -o json | jq '.spec.shardTopology.shard.replicas'
3
From all the above outputs we can see that the number of shards is now decreased to 2 and also, their replicas decreased to 3. That means we have successfully scaled down the number of shards and their replicas.
Vetical Scaling of MongoDB Sharded Cluster
We are going to scale up the current cpu resource of the MongoDB sharded cluster by applying Vertical Scaling. Before applying it, let’s check the current resources,
$ kubectl get pod -n demo mongodb-shard-shard0-0 -o json | jq '.spec.containers[].resources'
{
"limits": {
"memory": "1Gi"
},
"requests": {
"cpu": "500m",
"memory": "1Gi"
}
}
Vertical Scale Up
Create MongoDBOpsRequest
In order to update the resources of the cluster, we have to create a MongoDBOpsRequest CR with our desired resources. Let’s create it using this following yaml,
apiVersion: ops.kubedb.com/v1alpha1
kind: MongoDBOpsRequest
metadata:
name: vertical-scale-up
namespace: demo
spec:
type: VerticalScaling
databaseRef:
name: mongodb-shard
verticalScaling:
shard:
requests:
memory: "1100Mi"
cpu: "0.55"
limits:
memory: "1100Mi"
cpu: "0.55"
In this yaml,
spec.databaseRef.namespecifies that we are performing vertical scaling operation onmongodb-sharddatabase.spec.typespecifies that we are performingVerticalScalingon our database.spec.verticalScaling.shardspecifies the desired resources after scaling.
Let’s save this yaml configuration into vertical-scale-up.yaml and apply it,
$ kubectl apply -f vertical-scale-up.yaml
mongodbopsrequest.ops.kubedb.com/vertical-scale-up created
Let’s wait for MongoDBOpsRequest STATUS to be Successful. Run the following command to watch MongoDBOpsRequest CR,
$ kubectl get mongodbopsrequest -n demo
NAME TYPE STATUS AGE
vertical-scale-up VerticalScaling Successful 3m49s
We can see from the above output that the MongoDBOpsRequest has succeeded. Now, we are going to verify from one of the Pod yaml whether the resources of the database has updated to meet up the desired state. Let’s check with the following command,
$ kubectl get pod -n demo mongodb-shard-shard0-0 -o json | jq '.spec.containers[].resources'
{
"limits": {
"cpu": "550m",
"memory": "1100Mi"
},
"requests": {
"cpu": "550m",
"memory": "1100Mi"
}
}
The above output verifies that we have successfully scaled up the resources of the MongoDB sharded cluster.
Vertical Scale Down
Create MongoDBOpsRequest
In order to update the resources of the database, we have to create a MongoDBOpsRequest CR with our desired resources. Let’s create it using this following yaml,
apiVersion: ops.kubedb.com/v1alpha1
kind: MongoDBOpsRequest
metadata:
name: vertical-scale-down
namespace: demo
spec:
type: VerticalScaling
databaseRef:
name: mongodb-shard
verticalScaling:
shard:
requests:
memory: "1Gi"
cpu: "0.5"
limits:
memory: "1Gi"
cpu: "0.5"
In this yaml,
spec.databaseRef.namespecifies that we are performing vertical scaling operation onmongodb-sharddatabase.spec.typespecifies that we are performingVerticalScalingon our database.spec.verticalScaling.shardspecifies the desired resources after scaling.
Let’s save this yaml configuration into vertical-scale-down.yaml and apply it,
$ kubectl apply -f vertical-scale-down.yaml
mongodbopsrequest.ops.kubedb.com/vertical-scale-down created
Let’s wait for MongoDBOpsRequest STATUS to be Successful. Run the following command to watch MongoDBOpsRequest CR,
$ kubectl get mongodbopsrequest -n demo
NAME TYPE STATUS AGE
vertical-scale-down VerticalScaling Successful 3m21s
We can see from the above output that the MongoDBOpsRequest has succeeded. Now, we are going to verify from one of the Pod yaml whether the resources of the database has updated to meet up the desired state. Let’s check with the following command,
$ kubectl get pod -n demo mongodb-shard-shard0-0 -o json | jq '.spec.containers[].resources'
{
"limits": {
"cpu": "500m",
"memory": "1Gi"
},
"requests": {
"cpu": "500m",
"memory": "1Gi"
}
}
The above output verifies that we have successfully scaled down the resources of the MongoDB sharded cluster.
Access Sample Data
Now, we are going to login into our MongoDB shard pod to verify the data if it’s available or not,
$ kubectl exec -it -n demo mongodb-shard-shard0-0 -- mongosh admin -u $USER -p $PASSWORD
Defaulted container "mongodb" out of: mongodb, copy-config (init)
Using MongoDB: 6.0.5
Using Mongosh: 1.8.2
shard0 [direct: primary] admin> show dbs
admin 132.00 KiB
config 2.98 MiB
kubedb-system 108.00 KiB
local 2.53 MiB
musicdb 40.00 KiB
shard0 [direct: primary] admin> use musicdb
switched to db musicdb
shard0 [direct: primary] musicdb> db.songs.find().pretty()
[ { _id: ObjectId("64801d42029dd4780b0e573b"), name: "Annie's Song" } ]
shard0 [direct: primary] musicdb> exit
So, we’ve successfully access our sample data through the MongoDB shard.
If you want to learn more about Production-Grade MongoDB you can have a look into that playlist below:
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