You are looking at the documentation of a prior release. To read the documentation of the latest release, please visit here.

New to KubeDB? Please start here.

This is an Enterprise-only feature. Please install KubeDB Enterprise Edition to try this feature.

Autoscaling the Compute Resource of a PerconaXtraDB Cluster Database

This guide will show you how to use KubeDB to autoscale compute resources i.e. cpu and memory of a PerconaXtraDB replicaset database.

Before You Begin

At first, you need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster.
Install KubeDB Community, Ops-Manager and Autoscaler operator in your cluster following the steps here.
Install Metrics Server from here
You should be familiar with the following KubeDB concepts:

To keep everything isolated, we are going to use a separate namespace called demo throughout this tutorial.

$ kubectl create ns demo
namespace/demo created

Autoscaling of Cluster Database

Here, we are going to deploy a PerconaXtraDB Cluster using a supported version by KubeDB operator. Then we are going to apply PerconaXtraDBAutoscaler to set up autoscaling.

Deploy PerconaXtraDB Cluster

In this section, we are going to deploy a PerconaXtraDB Cluster with version 8.0.26. Then, in the next section we will set up autoscaling for this database using PerconaXtraDBAutoscaler CRD. Below is the YAML of the PerconaXtraDB CR that we are going to create,

If you want to autoscale PerconaXtraDB Standalone, Just remove the spec.Replicas from the below yaml and rest of the steps are same.

apiVersion: kubedb.com/v1alpha2
kind: PerconaXtraDB
metadata:
  name: sample-pxc
  namespace: demo
spec:
  version: "8.0.26"
  replicas: 3
  storageType: Durable
  storage:
    storageClassName: "standard"
    accessModes:
      - ReadWriteOnce
    resources:
      requests:
        storage: 1Gi
  podTemplate:
    spec:
      resources:
        requests:
          cpu: "200m"
          memory: "300Mi"
        limits:
          cpu: "200m"
          memory: "300Mi"
  terminationPolicy: WipeOut

Let’s create the PerconaXtraDB CRO we have shown above,

$ kubectl create -f https://github.com/kubedb/docs/raw/v2023.01.17/docs/guides/percona-xtradb/autoscaler/compute/cluster/examples/sample-pxc.yaml
perconaxtradb.kubedb.com/sample-pxc created

Now, wait until sample-pxc has status Ready. i.e,

$ kubectl get perconaxtradb -n demo
NAME             VERSION   STATUS   AGE
sample-pxc       8.0.26    Ready    14m

Let’s check the Pod containers resources,

$ kubectl get pod -n demo sample-pxc-0 -o json | jq '.spec.containers[].resources'
{
  "limits": {
    "cpu": "200m",
    "memory": "300Mi"
  },
  "requests": {
    "cpu": "200m",
    "memory": "300Mi"
  }
}

Let’s check the PerconaXtraDB resources,

$ kubectl get perconaxtradb -n demo sample-pxc -o json | jq '.spec.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 perconaxtradb.

We are now ready to apply the PerconaXtraDBAutoscaler CRO to set up autoscaling for this database.

Compute Resource Autoscaling

Here, we are going to set up compute resource autoscaling using a PerconaXtraDBAutoscaler Object.

Create PerconaXtraDBAutoscaler Object

In order to set up compute resource autoscaling for this database cluster, we have to create a PerconaXtraDBAutoscaler CRO with our desired configuration. Below is the YAML of the PerconaXtraDBAutoscaler object that we are going to create,

apiVersion: autoscaling.kubedb.com/v1alpha1
kind: PerconaXtraDBAutoscaler
metadata:
  name: px-as-compute
  namespace: demo
spec:
  databaseRef:
    name: sample-pxc
  opsRequestOptions:
    timeout: 3m
    apply: IfReady
  compute:
    perconaxtradb:
      trigger: "On"
      podLifeTimeThreshold: 5m
      resourceDiffPercentage: 20
      minAllowed:
        cpu: 250m
        memory: 400Mi
      maxAllowed:
        cpu: 1
        memory: 1Gi
      containerControlledValues: "RequestsAndLimits"
      controlledResources: ["cpu", "memory"]

Here,

spec.databaseRef.name specifies that we are performing compute resource scaling operation on sample-pxc database.
spec.compute.perconaxtradb.trigger specifies that compute autoscaling is enabled for this database.
spec.compute.perconaxtradb.podLifeTimeThreshold specifies the minimum lifetime for at least one of the pod to initiate a vertical scaling.
spec.compute.perconaxtradb.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.perconaxtradb.minAllowed specifies the minimum allowed resources for the database.
spec.compute.perconaxtradb.maxAllowed specifies the maximum allowed resources for the database.
spec.compute.perconaxtradb.controlledResources specifies the resources that are controlled by the autoscaler.
spec.compute.perconaxtradb.containerControlledValues specifies which resource values should be controlled. The default is “RequestsAndLimits”.
spec.opsRequestOptions.apply has two supported value : IfReady & Always. Use IfReady if you want to process the opsReq only when the database is Ready. And use Always if you want to process the execution of opsReq irrespective of the Database state.
spec.opsRequestOptions.timeout specifies the maximum time for each step of the opsRequest(in seconds). If a step doesn’t finish within the specified timeout, the ops request will result in failure.

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

$ kubectl apply -f https://github.com/kubedb/docs/raw/v2023.01.17/docs/guides/percona-xtradb/autoscaler/compute/cluster/examples/pxas-compute.yaml
perconaxtradbautoscaler.autoscaling.kubedb.com/pxas-compute created

Verify Autoscaling is set up successfully

Let’s check that the perconaxtradbautoscaler resource is created successfully,

$ kubectl get perconaxtradbautoscaler -n demo
NAME            AGE
px-as-compute   5m56s

$ kubectl describe perconaxtradbautoscaler px-as-compute -n demo
Name:         px-as-compute
Namespace:    demo
Labels:       <none>
Annotations:  <none>
API Version:  autoscaling.kubedb.com/v1alpha1
Kind:         PerconaXtraDBAutoscaler
Metadata:
  Creation Timestamp:  2022-09-16T11:26:58Z
  Generation:          1
  Managed Fields:
  ...
  Resource Version:  846645
  UID:               44bd46c3-bbc5-4c4a-aff4-00c7f84c6f58
Spec:
  Compute:
    Mariadb:
      Container Controlled Values:  RequestsAndLimits
      Controlled Resources:
        cpu
        memory
      Max Allowed:
        Cpu:     1
        Memory:  1Gi
      Min Allowed:
        Cpu:                     250m
        Memory:                  400Mi
      Pod Life Time Threshold:   5m0s
      Resource Diff Percentage:  20
      Trigger:                   On
  Database Ref:
    Name:  sample-pxc
  Ops Request Options:
    Apply:    IfReady
    Timeout:  3m0s
Status:
  Checkpoints:
    Cpu Histogram:
      Bucket Weights:
        Index:              0
        Weight:             10000
        Index:              46
        Weight:             555
      Reference Timestamp:  2022-09-16T00:00:00Z
      Total Weight:         2.648440345821337
    First Sample Start:     2022-09-16T11:26:48Z
    Last Sample Start:      2022-09-16T11:32:52Z
    Last Update Time:       2022-09-16T11:33:02Z
    Memory Histogram:
      Bucket Weights:
        Index:              1
        Weight:             10000
      Reference Timestamp:  2022-09-17T00:00:00Z
      Total Weight:         1.391848625060675
    Ref:
      Container Name:     px-coordinator
      Vpa Object Name:    sample-pxc
    Total Samples Count:  19
    Version:              v3
    Cpu Histogram:
      Bucket Weights:
        Index:              0
        Weight:             10000
        Index:              3
        Weight:             556
      Reference Timestamp:  2022-09-16T00:00:00Z
      Total Weight:         2.648440345821337
    First Sample Start:     2022-09-16T11:26:48Z
    Last Sample Start:      2022-09-16T11:32:52Z
    Last Update Time:       2022-09-16T11:33:02Z
    Memory Histogram:
      Reference Timestamp:  2022-09-17T00:00:00Z
    Ref:
      Container Name:     perconaxtradb
      Vpa Object Name:    sample-pxc
    Total Samples Count:  19
    Version:              v3
  Conditions:
    Last Transition Time:  2022-09-16T11:27:07Z
    Message:               Successfully created mariaDBOpsRequest demo/pxops-sample-pxc-6xc1kc
    Observed Generation:   1
    Reason:                CreateOpsRequest
    Status:                True
    Type:                  CreateOpsRequest
  Vpas:
    Conditions:
      Last Transition Time:  2022-09-16T11:27:02Z
      Status:                True
      Type:                  RecommendationProvided
    Recommendation:
      Container Recommendations:
        Container Name:  perconaxtradb
        Lower Bound:
          Cpu:     250m
          Memory:  400Mi
        Target:
          Cpu:     250m
          Memory:  400Mi
        Uncapped Target:
          Cpu:     25m
          Memory:  262144k
        Upper Bound:
          Cpu:     1
          Memory:  1Gi
    Vpa Name:      sample-pxc
Events:            <none>

So, the perconaxtradbautoscaler resource is created successfully.

We can verify from the above output that status.vpas contains the RecommendationProvided condition to true. And in the same time, status.vpas.recommendation.containerRecommendations contain the actual generated recommendation.

Our autoscaler operator continuously watches the recommendation generated and creates an perconaxtradbopsrequest based on the recommendations, if the database pod resources are needed to scaled up or down.

Let’s watch the perconaxtradbopsrequest in the demo namespace to see if any perconaxtradbopsrequest object is created. After some time you’ll see that a perconaxtradbopsrequest will be created based on the recommendation.

$ kubectl get perconaxtradbopsrequest -n demo
NAME                          TYPE              STATUS       AGE
pxops-sample-pxc-6xc1kc   VerticalScaling   Progressing  7s

Let’s wait for the ops request to become successful.

$ kubectl get perconaxtradbopsrequest -n demo
NAME                              TYPE              STATUS       AGE
pxops-vpa-sample-pxc-z43wc8   VerticalScaling   Successful   3m32s

We can see from the above output that the PerconaXtraDBOpsRequest has succeeded. If we describe the PerconaXtraDBOpsRequest we will get an overview of the steps that were followed to scale the database.

$ kubectl describe perconaxtradbopsrequest -n demo pxops-vpa-sample-pxc-z43wc8
Name:         pxops-sample-pxc-6xc1kc
Namespace:    demo
Labels:       <none>
Annotations:  <none>
API Version:  ops.kubedb.com/v1alpha1
Kind:         PerconaXtraDBOpsRequest
Metadata:
  Creation Timestamp:  2022-09-16T11:27:07Z
  Generation:          1
  Managed Fields:
    API Version:  ops.kubedb.com/v1alpha1
    Fields Type:  FieldsV1
    fieldsV1:
      f:metadata:
        f:ownerReferences:
          .:
          k:{"uid":"44bd46c3-bbc5-4c4a-aff4-00c7f84c6f58"}:
      f:spec:
        .:
        f:apply:
        f:databaseRef:
          .:
          f:name:
        f:timeout:
        f:type:
        f:verticalScaling:
          .:
          f:perconaxtradb:
            .:
            f:limits:
              .:
              f:cpu:
              f:memory:
            f:requests:
              .:
              f:cpu:
              f:memory:
    Manager:      kubedb-autoscaler
    Operation:    Update
    Time:         2022-09-16T11:27:07Z
    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:         2022-09-16T11:27:07Z
  Owner References:
    API Version:           autoscaling.kubedb.com/v1alpha1
    Block Owner Deletion:  true
    Controller:            true
    Kind:                  PerconaXtraDBAutoscaler
    Name:                  px-as-compute
    UID:                   44bd46c3-bbc5-4c4a-aff4-00c7f84c6f58
  Resource Version:        846324
  UID:                     c2b30107-c6d3-44bb-adf3-135edc5d615b
Spec:
  Apply:  IfReady
  Database Ref:
    Name:   sample-pxc
  Timeout:  2m0s
  Type:     VerticalScaling
  Vertical Scaling:
    Mariadb:
      Limits:
        Cpu:     250m
        Memory:  400Mi
      Requests:
        Cpu:     250m
        Memory:  400Mi
Status:
  Conditions:
    Last Transition Time:  2022-09-16T11:27:07Z
    Message:               Controller has started to Progress the PerconaXtraDBOpsRequest: demo/pxops-sample-pxc-6xc1kc
    Observed Generation:   1
    Reason:                OpsRequestProgressingStarted
    Status:                True
    Type:                  Progressing
    Last Transition Time:  2022-09-16T11:30:42Z
    Message:               Successfully restarted PerconaXtraDB pods for PerconaXtraDBOpsRequest: demo/pxops-sample-pxc-6xc1kc
    Observed Generation:   1
    Reason:                SuccessfullyRestatedStatefulSet
    Status:                True
    Type:                  RestartStatefulSet
    Last Transition Time:  2022-09-16T11:30:47Z
    Message:               Vertical scale successful for PerconaXtraDBOpsRequest: demo/pxops-sample-pxc-6xc1kc
    Observed Generation:   1
    Reason:                SuccessfullyPerformedVerticalScaling
    Status:                True
    Type:                  VerticalScaling
    Last Transition Time:  2022-09-16T11:30:47Z
    Message:               Controller has successfully scaled the PerconaXtraDB demo/pxops-sample-pxc-6xc1kc
    Observed Generation:   1
    Reason:                OpsRequestProcessedSuccessfully
    Status:                True
    Type:                  Successful
  Observed Generation:     1
  Phase:                   Successful
Events:
  Type    Reason      Age    From                        Message
  ----    ------      ----   ----                        -------
  Normal  Starting    8m48s  KubeDB Enterprise Operator  Start processing for PerconaXtraDBOpsRequest: demo/pxops-sample-pxc-6xc1kc
  Normal  Starting    8m48s  KubeDB Enterprise Operator  Pausing PerconaXtraDB databse: demo/sample-pxc
  Normal  Successful  8m48s  KubeDB Enterprise Operator  Successfully paused PerconaXtraDB database: demo/sample-pxc for PerconaXtraDBOpsRequest: pxops-sample-pxc-6xc1kc
  Normal  Starting    8m43s  KubeDB Enterprise Operator  Restarting Pod: demo/sample-pxc-0
  Normal  Starting    7m33s  KubeDB Enterprise Operator  Restarting Pod: demo/sample-pxc-1
  Normal  Starting    6m23s  KubeDB Enterprise Operator  Restarting Pod: demo/sample-pxc-2
  Normal  Successful  5m13s  KubeDB Enterprise Operator  Successfully restarted PerconaXtraDB pods for PerconaXtraDBOpsRequest: demo/pxops-sample-pxc-6xc1kc
  Normal  Successful  5m8s   KubeDB Enterprise Operator  Vertical scale successful for PerconaXtraDBOpsRequest: demo/pxops-sample-pxc-6xc1kc
  Normal  Starting    5m8s   KubeDB Enterprise Operator  Resuming PerconaXtraDB database: demo/sample-pxc
  Normal  Successful  5m8s   KubeDB Enterprise Operator  Successfully resumed PerconaXtraDB database: demo/sample-pxc
  Normal  Successful  5m8s   KubeDB Enterprise Operator  Controller has Successfully scaled the PerconaXtraDB database: demo/sample-pxc

Now, we are going to verify from the Pod, and the PerconaXtraDB yaml whether the resources of the replicaset database has updated to meet up the desired state, Let’s check,

$ kubectl get pod -n demo sample-pxc-0 -o json | jq '.spec.containers[].resources'
{
  "limits": {
    "cpu": "250m",
    "memory": "400Mi"
  },
  "requests": {
    "cpu": "250m",
    "memory": "400Mi"
  }
}

$ kubectl get perconaxtradb -n demo sample-pxc -o json | jq '.spec.podTemplate.spec.resources'
{
  "limits": {
    "cpu": "250m",
    "memory": "400Mi"
  },
  "requests": {
    "cpu": "250m",
    "memory": "400Mi"
  }
}

The above output verifies that we have successfully autoscaled the resources of the PerconaXtraDB replicaset database.

Cleaning Up

To clean up the Kubernetes resources created by this tutorial, run:

kubectl delete perconaxtradb -n demo sample-pxc
kubectl delete perconaxtradbautoscaler -n demo px-as-compute
kubectl delete ns demo

KubeDB

Stash

KubeVault

Voyager

ConfigSyncer

Guard

RESOURCES

Druid

Elasticsearch

FerretDB

Kafka

MariaDB

Memcached

Microsoft SQL Server

MongoDB

MySQL

OpenSearch

PerconaXtraDB

PgBouncer

Pgpool

PostgreSQL

ProxySQL

RabbitMQ

Redis

SingleStore

Solr

ZooKeeper