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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

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/v2023.01.17/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
  opsRequestOptions:
    timeout: 3m
    apply: IfReady
  compute:
    shard:
      trigger: "On"
      podLifeTimeThreshold: 5m
      resourceDiffPercentage: 20
      minAllowed:
        cpu: 400m
        memory: 400Mi
      maxAllowed:
        cpu: 1
        memory: 1Gi
      controlledResources: ["cpu", "memory"]
      containerControlledValues: "RequestsAndLimits"

Here,

  • spec.databaseRef.name specifies that we are performing compute resource scaling operation on mg-sh database.
  • spec.compute.shard.trigger specifies that compute autoscaling is enabled for the shard pods of this database.
  • spec.compute.shard.podLifeTimeThreshold specifies the minimum lifetime for at least one of the pod to initiate a vertical scaling.
  • spec.compute.replicaset.resourceDiffPercentage specifies the minimum resource difference in percentage. The default is 10%. If the difference between current & recommended resource is less than ResourceDiffPercentage, Autoscaler Operator will ignore the updating.
  • spec.compute.shard.minAllowed specifies the minimum allowed resources for the database.
  • spec.compute.shard.maxAllowed specifies the maximum allowed resources for the database.
  • spec.compute.shard.controlledResources specifies the resources that are controlled by the autoscaler.
  • spec.compute.shard.containerControlledValues specifies which resource values should be controlled. The default is “RequestsAndLimits”.
  • spec.opsRequestOptions contains the options to pass to the created OpsRequest. It has 3 fields. Know more about them here : readinessCriteria, timeout, apply.

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.compute.mongos and spec.compute.configServer section, similar to the spec.comput.shard section we have configured in this demo.

If it was an InMemory database, we could also autoscaler the inMemory resources using MongoDB compute autoscaler, like below.

Autoscale inMemory database

To autoscale inMemory databases, you need to specify the spec.compute.shard.inMemoryStorage section.

  ...
  inMemoryStorage:
    usageThresholdPercentage: 80
    scalingFactorPercentage: 30
  ...

It has two fields inside it.

  • usageThresholdPercentage. If db uses more than usageThresholdPercentage of the total memory, memoryStorage should be increased. Default usage threshold is 70%.
  • scalingFactorPercentage. If db uses more than usageThresholdPercentage of the total memory, memoryStorage should be increased by this given scaling percentage. Default scaling percentage is 50%.

Note: To inform you, We use db.serverStatus().inMemory.cache["bytes currently in the cache"] & db.serverStatus().inMemory.cache["maximum bytes configured"] to calculate the used & maximum inMemory storage respectively.

Let’s create the MongoDBAutoscaler CR we have shown above,

$ kubectl apply -f https://github.com/kubedb/docs/raw/v2023.01.17/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:  2022-10-27T09:46:48Z
  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:containerControlledValues:
            f:controlledResources:
            f:maxAllowed:
              .:
              f:cpu:
              f:memory:
            f:minAllowed:
              .:
              f:cpu:
              f:memory:
            f:podLifeTimeThreshold:
            f:resourceDiffPercentage:
            f:trigger:
        f:databaseRef:
        f:opsRequestOptions:
          .:
          f:apply:
          f:timeout:
    Manager:      kubectl-client-side-apply
    Operation:    Update
    Time:         2022-10-27T09:46:48Z
    API Version:  autoscaling.kubedb.com/v1alpha1
    Fields Type:  FieldsV1
    fieldsV1:
      f:status:
        .:
        f:checkpoints:
        f:conditions:
        f:vpas:
    Manager:         kubedb-autoscaler
    Operation:       Update
    Subresource:     status
    Time:            2022-10-27T09:47:08Z
  Resource Version:  654853
  UID:               36878e8e-f100-409e-aa76-e6f46569df76
Spec:
  Compute:
    Shard:
      Container Controlled Values:  RequestsAndLimits
      Controlled Resources:
        cpu
        memory
      Max Allowed:
        Cpu:     1
        Memory:  1Gi
      Min Allowed:
        Cpu:                     400m
        Memory:                  400Mi
      Pod Life Time Threshold:   5m0s
      Resource Diff Percentage:  20
      Trigger:                   On
  Database Ref:
    Name:  mg-sh
  Ops Request Options:
    Apply:    IfReady
    Timeout:  3m0s
Status:
  Checkpoints:
    Cpu Histogram:
      Bucket Weights:
        Index:              1
        Weight:             5001
        Index:              2
        Weight:             10000
      Reference Timestamp:  2022-10-27T00:00:00Z
      Total Weight:         0.397915611757652
    First Sample Start:     2022-10-27T09:46:43Z
    Last Sample Start:      2022-10-27T09:46:57Z
    Last Update Time:       2022-10-27T09:47:06Z
    Memory Histogram:
      Reference Timestamp:  2022-10-28T00:00:00Z
    Ref:
      Container Name:     mongodb
      Vpa Object Name:    mg-sh-shard0
    Total Samples Count:  3
    Version:              v3
    Cpu Histogram:
      Bucket Weights:
        Index:              1
        Weight:             10000
      Reference Timestamp:  2022-10-27T00:00:00Z
      Total Weight:         0.39793263724156597
    First Sample Start:     2022-10-27T09:46:50Z
    Last Sample Start:      2022-10-27T09:46:56Z
    Last Update Time:       2022-10-27T09:47:06Z
    Memory Histogram:
      Reference Timestamp:  2022-10-28T00:00:00Z
    Ref:
      Container Name:     mongodb
      Vpa Object Name:    mg-sh-shard1
    Total Samples Count:  3
    Version:              v3
  Conditions:
    Last Transition Time:  2022-10-27T09:47:08Z
    Message:               Successfully created mongoDBOpsRequest demo/mops-vpa-mg-sh-shard-ml75qi
    Observed Generation:   1
    Reason:                CreateOpsRequest
    Status:                True
    Type:                  CreateOpsRequest
  Vpas:
    Conditions:
      Last Transition Time:  2022-10-27T09:47:06Z
      Status:                True
      Type:                  RecommendationProvided
    Recommendation:
      Container Recommendations:
        Container Name:  mongodb
        Lower Bound:
          Cpu:     400m
          Memory:  400Mi
        Target:
          Cpu:     400m
          Memory:  400Mi
        Uncapped Target:
          Cpu:     35m
          Memory:  262144k
        Upper Bound:
          Cpu:     1
          Memory:  1Gi
    Vpa Name:      mg-sh-shard0
    Conditions:
      Last Transition Time:  2022-10-27T09:47:06Z
      Status:                True
      Type:                  RecommendationProvided
    Recommendation:
      Container Recommendations:
        Container Name:  mongodb
        Lower Bound:
          Cpu:     400m
          Memory:  400Mi
        Target:
          Cpu:     400m
          Memory:  400Mi
        Uncapped Target:
          Cpu:     25m
          Memory:  262144k
        Upper Bound:
          Cpu:     1
          Memory:  1Gi
    Vpa Name:      mg-sh-shard1
Events:            <none>

So, the mongodbautoscaler resource is created successfully.

you can see in the Status.VPAs.Recommendation section, that recommendation has been generated for our 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-ml75qi   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-ml75qi     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-ml75qi
Name:         mops-vpa-mg-sh-shard-ml75qi
Namespace:    demo
Labels:       <none>
Annotations:  <none>
API Version:  ops.kubedb.com/v1alpha1
Kind:         MongoDBOpsRequest
Metadata:
  Creation Timestamp:  2022-10-27T09:47:08Z
  Generation:          1
  Managed Fields:
    API Version:  ops.kubedb.com/v1alpha1
    Fields Type:  FieldsV1
    fieldsV1:
      f:metadata:
        f:ownerReferences:
          .:
          k:{"uid":"36878e8e-f100-409e-aa76-e6f46569df76"}:
      f:spec:
        .:
        f:apply:
        f:databaseRef:
        f:timeout:
        f:type:
        f:verticalScaling:
          .:
          f:shard:
            .:
            f:limits:
              .:
              f:memory:
            f:requests:
              .:
              f:cpu:
              f:memory:
    Manager:      kubedb-autoscaler
    Operation:    Update
    Time:         2022-10-27T09:47:08Z
    API Version:  ops.kubedb.com/v1alpha1
    Fields Type:  FieldsV1
    fieldsV1:
      f:status:
        .:
        f:conditions:
        f:observedGeneration:
        f:phase:
    Manager:      kubedb-ops-manager
    Operation:    Update
    Subresource:  status
    Time:         2022-10-27T09:49:49Z
  Owner References:
    API Version:           autoscaling.kubedb.com/v1alpha1
    Block Owner Deletion:  true
    Controller:            true
    Kind:                  MongoDBAutoscaler
    Name:                  mg-as-sh
    UID:                   36878e8e-f100-409e-aa76-e6f46569df76
  Resource Version:        655347
  UID:                     c44fbd53-40f9-42ca-9b4c-823d8e998d01
Spec:
  Apply:  IfReady
  Database Ref:
    Name:   mg-sh
  Timeout:  3m0s
  Type:     VerticalScaling
  Vertical Scaling:
    Shard:
      Limits:
        Memory:  400Mi
      Requests:
        Cpu:     400m
        Memory:  400Mi
Status:
  Conditions:
    Last Transition Time:  2022-10-27T09:47:08Z
    Message:               MongoDB ops request is vertically scaling database
    Observed Generation:   1
    Reason:                VerticalScaling
    Status:                True
    Type:                  VerticalScaling
    Last Transition Time:  2022-10-27T09:49:49Z
    Message:               Successfully Vertically Scaled Shard Resources
    Observed Generation:   1
    Reason:                UpdateShardResources
    Status:                True
    Type:                  UpdateShardResources
    Last Transition Time:  2022-10-27T09:49:49Z
    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         3m27s  KubeDB Ops-manager Operator  Pausing MongoDB demo/mg-sh
  Normal  PauseDatabase         3m27s  KubeDB Ops-manager Operator  Successfully paused MongoDB demo/mg-sh
  Normal  Starting              3m27s  KubeDB Ops-manager Operator  Updating Resources of StatefulSet: mg-sh-shard0
  Normal  Starting              3m27s  KubeDB Ops-manager Operator  Updating Resources of StatefulSet: mg-sh-shard1
  Normal  UpdateShardResources  3m27s  KubeDB Ops-manager Operator  Successfully updated Shard Resources
  Normal  Starting              3m27s  KubeDB Ops-manager Operator  Updating Resources of StatefulSet: mg-sh-shard0
  Normal  Starting              3m27s  KubeDB Ops-manager Operator  Updating Resources of StatefulSet: mg-sh-shard1
  Normal  UpdateShardResources  3m27s  KubeDB Ops-manager Operator  Successfully updated Shard Resources
  Normal  UpdateShardResources  46s    KubeDB Ops-manager Operator  Successfully Vertically Scaled Shard Resources
  Normal  ResumeDatabase        46s    KubeDB Ops-manager Operator  Resuming MongoDB demo/mg-sh
  Normal  ResumeDatabase        46s    KubeDB Ops-manager Operator  Successfully resumed MongoDB demo/mg-sh
  Normal  Successful            46s    KubeDB Ops-manager 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": {
    "memory": "400Mi"
  },
  "requests": {
    "cpu": "400m",
    "memory": "400Mi"
  }
}


$ kubectl get mongodb -n demo mg-sh -o json | jq '.spec.shardTopology.shard.podTemplate.spec.resources'
{
  "limits": {
    "memory": "400Mi"
  },
  "requests": {
    "cpu": "400m",
    "memory": "400Mi"
  }
}

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