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Autoscaling the Compute Resource of a MongoDB Sharded Database
This guide will show you how to use KubeDB to autoscale compute resources i.e. cpu and memory of a MongoDB sharded database.
Before You Begin
At first, you need to have a Kubernetes cluster, and the
kubectlcommand-line tool must be configured to communicate with your cluster.Install
KubeDBCommunity, Enterprise and Autoscaler operator in your cluster following the steps here.Install
Metrics Serverfrom hereInstall
Vertical Pod Autoscalerfrom hereYou should be familiar with the following
KubeDBconcepts:
To keep everything isolated, we are going to use a separate namespace called demo throughout this tutorial.
$ kubectl create ns demo
namespace/demo created
Note: YAML files used in this tutorial are stored in docs/examples/mongodb directory of kubedb/docs repository.
Autoscaling of Sharded Database
Here, we are going to deploy a MongoDB sharded database using a supported version by KubeDB operator. Then we are going to apply MongoDBAutoscaler to set up autoscaling.
Deploy MongoDB Sharded Database
In this section, we are going to deploy a MongoDB sharded database with version 4.2.3. Then, in the next section we will set up autoscaling for this database using MongoDBAutoscaler CRD. Below is the YAML of the MongoDB CR that we are going to create,
apiVersion: kubedb.com/v1alpha2
kind: MongoDB
metadata:
name: mg-sh
namespace: demo
spec:
version: "4.2.3"
storageType: Durable
shardTopology:
configServer:
storage:
resources:
requests:
storage: 1Gi
replicas: 3
podTemplate:
spec:
resources:
requests:
cpu: "200m"
memory: "300Mi"
mongos:
replicas: 2
podTemplate:
spec:
resources:
requests:
cpu: "200m"
memory: "300Mi"
shard:
storage:
resources:
requests:
storage: 1Gi
replicas: 3
shards: 2
podTemplate:
spec:
resources:
requests:
cpu: "200m"
memory: "300Mi"
terminationPolicy: WipeOut
Let’s create the MongoDB CRO we have shown above,
$ kubectl create -f https://github.com/kubedb/docs/raw/v2021.08.23/docs/examples/mongodb/autoscaling/compute/mg-sh.yaml
mongodb.kubedb.com/mg-sh created
Now, wait until mg-sh has status Ready. i.e,
$ kubectl get mg -n demo
NAME VERSION STATUS AGE
mg-sh 4.2.3 Ready 3m57s
Let’s check a shard Pod containers resources,
$ kubectl get pod -n demo mg-sh-shard0-0 -o json | jq '.spec.containers[].resources'
{
"limits": {
"cpu": "200m",
"memory": "300Mi"
},
"requests": {
"cpu": "200m",
"memory": "300Mi"
}
}
Let’s check the MongoDB resources,
$ kubectl get mongodb -n demo mg-sh -o json | jq '.spec.shardTopology.shard.podTemplate.spec.resources'
{
"limits": {
"cpu": "200m",
"memory": "300Mi"
},
"requests": {
"cpu": "200m",
"memory": "300Mi"
}
}
You can see from the above outputs that the resources are same as the one we have assigned while deploying the mongodb.
We are now ready to apply the MongoDBAutoscaler CRO to set up autoscaling for this database.
Compute Resource Autoscaling
Here, we are going to set up compute resource autoscaling using a MongoDBAutoscaler Object.
Create MongoDBAutoscaler Object
In order to set up compute resource autoscaling for the shard pod of the database, we have to create a MongoDBAutoscaler CRO with our desired configuration. Below is the YAML of the MongoDBAutoscaler object that we are going to create,
apiVersion: autoscaling.kubedb.com/v1alpha1
kind: MongoDBAutoscaler
metadata:
name: mg-as-sh
namespace: demo
spec:
databaseRef:
name: mg-sh
compute:
shard:
trigger: "On"
podLifeTimeThreshold: 5m
minAllowed:
cpu: 250m
memory: 350Mi
maxAllowed:
cpu: 1
memory: 1Gi
controlledResources: ["cpu", "memory"]
Here,
spec.databaseRef.namespecifies that we are performing compute resource scaling operation onmg-shdatabase.spec.compute.shard.triggerspecifies that compute autoscaling is enabled for the shard pods of this database.spec.compute.shard.podLifeTimeThresholdspecifies the minimum lifetime for at least one of the pod to initiate a vertical scaling.spec.compute.shard.minAllowedspecifies the minimum allowed resources for the database.spec.compute.shard.maxAllowedspecifies the maximum allowed resources for the database.spec.compute.shard.controlledResourcesspecifies the resources that are controlled by the autoscaler.
Note: In this demo we are only setting up the autoscaling for the shard pods, that’s why we only specified the shard section of the autoscaler. You can enable autoscaling for mongos and configServer pods in the same yaml, by specifying the
spec.mongosandspec.configServersection, similar to thespec.shardsection we have configured in this demo.
Let’s create the MongoDBAutoscaler CR we have shown above,
$ kubectl apply -f https://github.com/kubedb/docs/raw/v2021.08.23/docs/examples/mongodb/autoscaling/compute/mg-as-sh.yaml
mongodbautoscaler.autoscaling.kubedb.com/mg-as-sh created
Verify Autoscaling is set up successfully
Let’s check that the mongodbautoscaler resource is created successfully,
$ kubectl get mongodbautoscaler -n demo
NAME AGE
mg-as-sh 102s
$ kubectl describe mongodbautoscaler mg-as-sh -n demo
Name: mg-as-sh
Namespace: demo
Labels: <none>
Annotations: <none>
API Version: autoscaling.kubedb.com/v1alpha1
Kind: MongoDBAutoscaler
Metadata:
Creation Timestamp: 2021-03-07T16:49:09Z
Generation: 1
Managed Fields:
API Version: autoscaling.kubedb.com/v1alpha1
Fields Type: FieldsV1
fieldsV1:
f:metadata:
f:annotations:
.:
f:kubectl.kubernetes.io/last-applied-configuration:
f:spec:
.:
f:compute:
.:
f:shard:
.:
f:controlledResources:
f:maxAllowed:
.:
f:cpu:
f:memory:
f:minAllowed:
.:
f:cpu:
f:memory:
f:podLifeTimeThreshold:
f:trigger:
f:databaseRef:
.:
f:name:
Manager: kubectl-client-side-apply
Operation: Update
Time: 2021-03-07T16:49:09Z
API Version: autoscaling.kubedb.com/v1alpha1
Fields Type: FieldsV1
fieldsV1:
f:status:
.:
f:conditions:
Manager: kubedb-autoscaler
Operation: Update
Time: 2021-03-07T16:50:13Z
Resource Version: 879550
Self Link: /apis/autoscaling.kubedb.com/v1alpha1/namespaces/demo/mongodbautoscalers/mg-as-sh
UID: 7e6880f1-42ba-4d78-ba1c-02aa9ea522e9
Spec:
Compute:
Shard:
Controlled Resources:
cpu
memory
Max Allowed:
Cpu: 1
Memory: 1Gi
Min Allowed:
Cpu: 250m
Memory: 350Mi
Pod Life Time Threshold: 5m0s
Trigger: On
Database Ref:
Name: mg-sh
Status:
Events: <none>
So, the mongodbautoscaler resource is created successfully.
Now, lets verify that the vertical pod autoscaler (vpa) resource is created successfully,
$ kubectl get vpa -n demo
NAME AGE
vpa-mg-sh-shard0 110s
vpa-mg-sh-shard1 110s
$ kubectl describe vpa vpa-mg-sh-shard0 -n demo
Name: vpa-mg-sh-shard0
Namespace: demo
Labels: <none>
Annotations: <none>
API Version: autoscaling.k8s.io/v1
Kind: VerticalPodAutoscaler
Metadata:
Creation Timestamp: 2021-03-07T16:49:09Z
Generation: 2
Managed Fields:
API Version: autoscaling.k8s.io/v1
Fields Type: FieldsV1
fieldsV1:
f:metadata:
f:ownerReferences:
.:
k:{"uid":"7e6880f1-42ba-4d78-ba1c-02aa9ea522e9"}:
.:
f:apiVersion:
f:blockOwnerDeletion:
f:controller:
f:kind:
f:name:
f:uid:
f:spec:
.:
f:resourcePolicy:
.:
f:containerPolicies:
f:targetRef:
.:
f:apiVersion:
f:kind:
f:name:
f:updatePolicy:
.:
f:updateMode:
f:status:
Manager: kubedb-autoscaler
Operation: Update
Time: 2021-03-07T16:49:09Z
API Version: autoscaling.k8s.io/v1
Fields Type: FieldsV1
fieldsV1:
f:status:
f:conditions:
f:recommendation:
.:
f:containerRecommendations:
Manager: recommender
Operation: Update
Time: 2021-03-07T16:50:03Z
Owner References:
API Version: autoscaling.kubedb.com/v1alpha1
Block Owner Deletion: true
Controller: true
Kind: MongoDBAutoscaler
Name: mg-as-sh
UID: 7e6880f1-42ba-4d78-ba1c-02aa9ea522e9
Resource Version: 879512
Self Link: /apis/autoscaling.k8s.io/v1/namespaces/demo/verticalpodautoscalers/vpa-mg-sh-shard0
UID: e73e9920-5c4d-4e8e-887e-38b06120c9a6
Spec:
Resource Policy:
Container Policies:
Container Name: mongodb
Controlled Resources:
cpu
memory
Controlled Values: RequestsAndLimits
Max Allowed:
Cpu: 1
Memory: 1Gi
Min Allowed:
Cpu: 250m
Memory: 350Mi
Target Ref:
API Version: apps/v1
Kind: StatefulSet
Name: mg-sh-shard0
Update Policy:
Update Mode: Off
Status:
Conditions:
Last Transition Time: 2021-03-07T16:50:03Z
Status: False
Type: RecommendationProvided
Recommendation:
Events: <none>
So, we can verify from the above output that two vpa resources are created for our two shard successfully, but you can see that the RecommendationProvided condition is false and also the Recommendation section of the vpa is empty. Let’s wait some time and describe the vpa again.
$ kubectl describe vpa vpa-mg-sh-shard0 -n demo
Name: vpa-mg-sh-shard0
Namespace: demo
Labels: <none>
Annotations: <none>
API Version: autoscaling.k8s.io/v1
Kind: VerticalPodAutoscaler
Metadata:
Creation Timestamp: 2021-03-07T16:49:09Z
Generation: 2
Managed Fields:
API Version: autoscaling.k8s.io/v1
Fields Type: FieldsV1
fieldsV1:
f:metadata:
f:ownerReferences:
.:
k:{"uid":"7e6880f1-42ba-4d78-ba1c-02aa9ea522e9"}:
.:
f:apiVersion:
f:blockOwnerDeletion:
f:controller:
f:kind:
f:name:
f:uid:
f:spec:
.:
f:resourcePolicy:
.:
f:containerPolicies:
f:targetRef:
.:
f:apiVersion:
f:kind:
f:name:
f:updatePolicy:
.:
f:updateMode:
f:status:
Manager: kubedb-autoscaler
Operation: Update
Time: 2021-03-07T16:49:09Z
API Version: autoscaling.k8s.io/v1
Fields Type: FieldsV1
fieldsV1:
f:status:
f:conditions:
f:recommendation:
.:
f:containerRecommendations:
Manager: recommender
Operation: Update
Time: 2021-03-07T16:50:03Z
Owner References:
API Version: autoscaling.kubedb.com/v1alpha1
Block Owner Deletion: true
Controller: true
Kind: MongoDBAutoscaler
Name: mg-as-sh
UID: 7e6880f1-42ba-4d78-ba1c-02aa9ea522e9
Resource Version: 879512
Self Link: /apis/autoscaling.k8s.io/v1/namespaces/demo/verticalpodautoscalers/vpa-mg-sh-shard0
UID: e73e9920-5c4d-4e8e-887e-38b06120c9a6
Spec:
Resource Policy:
Container Policies:
Container Name: mongodb
Controlled Resources:
cpu
memory
Controlled Values: RequestsAndLimits
Max Allowed:
Cpu: 1
Memory: 1Gi
Min Allowed:
Cpu: 250m
Memory: 350Mi
Target Ref:
API Version: apps/v1
Kind: StatefulSet
Name: mg-sh-shard0
Update Policy:
Update Mode: Off
Status:
Conditions:
Last Transition Time: 2021-03-07T16:50:03Z
Status: True
Type: RecommendationProvided
Recommendation:
Container Recommendations:
Container Name: mongodb
Lower Bound:
Cpu: 250m
Memory: 350Mi
Target:
Cpu: 250m
Memory: 350Mi
Uncapped Target:
Cpu: 203m
Memory: 262144k
Upper Bound:
Cpu: 1
Memory: 1Gi
Events: <none>
As you can see from the output the vpa has generated a recommendation for the shard pod of the database. Our autoscaler operator continuously watches the recommendation generated and creates an mongodbopsrequest based on the recommendations, if the database pods are needed to scaled up or down.
Let’s watch the mongodbopsrequest in the demo namespace to see if any mongodbopsrequest object is created. After some time you’ll see that a mongodbopsrequest will be created based on the recommendation.
$ watch kubectl get mongodbopsrequest -n demo
Every 2.0s: kubectl get mongodbopsrequest -n demo
NAME TYPE STATUS AGE
mops-vpa-mg-sh-shard-3uqbrq VerticalScaling Progressing 19s
Let’s wait for the ops request to become successful.
$ watch kubectl get mongodbopsrequest -n demo
Every 2.0s: kubectl get mongodbopsrequest -n demo
NAME TYPE STATUS AGE
mops-vpa-mg-sh-shard-3uqbrq VerticalScaling Successful 5m8s
We can see from the above output that the MongoDBOpsRequest has succeeded. If we describe the MongoDBOpsRequest we will get an overview of the steps that were followed to scale the database.
$ kubectl describe mongodbopsrequest -n demo mops-vpa-mg-sh-shard-3uqbrq
Name: mops-vpa-mg-sh-shard-3uqbrq
Namespace: demo
Labels: app.kubernetes.io/component=database
app.kubernetes.io/instance=mg-sh
app.kubernetes.io/managed-by=kubedb.com
app.kubernetes.io/name=mongodbs.kubedb.com
Annotations: <none>
API Version: ops.kubedb.com/v1alpha1
Kind: MongoDBOpsRequest
Metadata:
Creation Timestamp: 2021-03-07T16:50:13Z
Generation: 1
Managed Fields:
API Version: ops.kubedb.com/v1alpha1
Fields Type: FieldsV1
fieldsV1:
f:metadata:
f:labels:
.:
f:app.kubernetes.io/component:
f:app.kubernetes.io/instance:
f:app.kubernetes.io/managed-by:
f:app.kubernetes.io/name:
f:ownerReferences:
f:spec:
.:
f:configuration:
f:databaseRef:
.:
f:name:
f:type:
f:verticalScaling:
.:
f:shard:
.:
f:limits:
.:
f:cpu:
f:memory:
f:requests:
.:
f:cpu:
f:memory:
Manager: kubedb-autoscaler
Operation: Update
Time: 2021-03-07T16:50:13Z
API Version: ops.kubedb.com/v1alpha1
Fields Type: FieldsV1
fieldsV1:
f:status:
.:
f:conditions:
f:observedGeneration:
f:phase:
Manager: kubedb-enterprise
Operation: Update
Time: 2021-03-07T16:50:13Z
Owner References:
API Version: autoscaling.kubedb.com/v1alpha1
Block Owner Deletion: true
Controller: true
Kind: MongoDBAutoscaler
Name: mg-as-sh
UID: 7e6880f1-42ba-4d78-ba1c-02aa9ea522e9
Resource Version: 880864
Self Link: /apis/ops.kubedb.com/v1alpha1/namespaces/demo/mongodbopsrequests/mops-vpa-mg-sh-shard-3uqbrq
UID: a9eb9a92-3a93-441c-90b9-a272cfff4e85
Spec:
Configuration:
Database Ref:
Name: mg-sh
Type: VerticalScaling
Vertical Scaling:
Shard:
Limits:
Cpu: 250m
Memory: 350Mi
Requests:
Cpu: 250m
Memory: 350Mi
Status:
Conditions:
Last Transition Time: 2021-03-07T16:50:13Z
Message: MongoDB ops request is vertically scaling database
Observed Generation: 1
Reason: VerticalScaling
Status: True
Type: VerticalScaling
Last Transition Time: 2021-03-07T16:50:13Z
Message: Successfully updated StatefulSets Resources
Observed Generation: 1
Reason: UpdateStatefulSetResources
Status: True
Type: UpdateStatefulSetResources
Last Transition Time: 2021-03-07T16:55:21Z
Message: Successfully Vertically Scaled Shard Resources
Observed Generation: 1
Reason: UpdateShardResources
Status: True
Type: UpdateShardResources
Last Transition Time: 2021-03-07T16:55:21Z
Message: Successfully Vertically Scaled Database
Observed Generation: 1
Reason: Successful
Status: True
Type: Successful
Observed Generation: 1
Phase: Successful
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal PauseDatabase 14m KubeDB Enterprise Operator Pausing MongoDB demo/mg-sh
Normal PauseDatabase 14m KubeDB Enterprise Operator Successfully paused MongoDB demo/mg-sh
Normal Starting 14m KubeDB Enterprise Operator Updating Resources of StatefulSet: mg-sh-shard0
Normal Starting 14m KubeDB Enterprise Operator Updating Resources of StatefulSet: mg-sh-shard1
Normal UpdateStatefulSetResources 14m KubeDB Enterprise Operator Successfully updated StatefulSets Resources
Normal UpdateShardResources 9m13s KubeDB Enterprise Operator Successfully Vertically Scaled Shard Resources
Normal ResumeDatabase 9m13s KubeDB Enterprise Operator Resuming MongoDB demo/mg-sh
Normal ResumeDatabase 9m13s KubeDB Enterprise Operator Successfully resumed MongoDB demo/mg-sh
Normal Successful 9m13s KubeDB Enterprise Operator Successfully Vertically Scaled Database
Now, we are going to verify from the Pod, and the MongoDB yaml whether the resources of the shard pod of the database has updated to meet up the desired state, Let’s check,
$ kubectl get pod -n demo mg-sh-shard0-0 -o json | jq '.spec.containers[].resources'
{
"limits": {
"cpu": "250m",
"memory": "350Mi"
},
"requests": {
"cpu": "250m",
"memory": "350Mi"
}
}
$ kubectl get mongodb -n demo mg-sh -o json | jq '.spec.shardTopology.shard.podTemplate.spec.resources'
{
"limits": {
"cpu": "250m",
"memory": "350Mi"
},
"requests": {
"cpu": "250m",
"memory": "350Mi"
}
}
The above output verifies that we have successfully auto scaled the resources of the MongoDB sharded database.
Cleaning Up
To clean up the Kubernetes resources created by this tutorial, run:
kubectl delete mg -n demo mg-sh
kubectl delete mongodbautoscaler -n demo mg-as-sh