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Autoscaling the Compute Resource of a MySQL Cluster Database
This guide will show you how to use KubeDB
to autoscale compute resources i.e. cpu and memory of a MySQL 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 hereYou 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 MySQL
Cluster using a supported version by KubeDB
operator. Then we are going to apply MySQLAutoscaler
to set up autoscaling.
Deploy MySQL Cluster
In this section, we are going to deploy a MySQL Cluster with version 10.6.16
. Then, in the next section we will set up autoscaling for this database using MySQLAutoscaler
CRD. Below is the YAML of the MySQL
CR that we are going to create,
If you want to autoscale MySQL
Standalone
, Just remove thespec.Replicas
from the below yaml and rest of the steps are same.
apiVersion: kubedb.com/v1
kind: MySQL
metadata:
name: sample-mysql
namespace: demo
spec:
version: "8.0.35"
replicas: 3
topology:
mode: GroupReplication
storageType: Durable
storage:
storageClassName: "standard"
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 1Gi
podTemplate:
spec:
containers:
- name: mysql
resources:
requests:
cpu: "200m"
memory: "300Mi"
limits:
cpu: "200m"
memory: "300Mi"
deletionPolicy: WipeOut
Let’s create the MySQL
CRO we have shown above,
$ kubectl create -f https://github.com/kubedb/docs/raw/v2024.11.18/docs/guides/mysql/autoscaler/compute/cluster/examples/sample-mysql.yaml
mysql.kubedb.com/sample-mysql created
Now, wait until sample-mysql
has status Ready
. i.e,
$ kubectl get mysql -n demo
NAME VERSION STATUS AGE
sample-mysql 8.0.35 Ready 14m
Let’s check the Pod containers resources,
$ kubectl get pod -n demo sample-mysql-0 -o json | jq '.spec.containers[].resources'
{
"limits": {
"cpu": "200m",
"memory": "300Mi"
},
"requests": {
"cpu": "200m",
"memory": "300Mi"
}
}
Let’s check the MySQL resources,
$ kubectl get mysql -n demo sample-mysql -o json | jq '.spec.podTemplate.spec.containers[] | select(.name == "mysql") | .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 mysql.
We are now ready to apply the MySQLAutoscaler
CRO to set up autoscaling for this database.
Compute Resource Autoscaling
Here, we are going to set up compute resource autoscaling using a MySQLAutoscaler Object.
Create MySQLAutoscaler Object
In order to set up compute resource autoscaling for this database cluster, we have to create a MySQLAutoscaler
CRO with our desired configuration. Below is the YAML of the MySQLAutoscaler
object that we are going to create,
apiVersion: autoscaling.kubedb.com/v1alpha1
kind: MySQLAutoscaler
metadata:
name: my-as-compute
namespace: demo
spec:
databaseRef:
name: sample-mysql
opsRequestOptions:
timeout: 3m
apply: IfReady
compute:
mysql:
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 onsample-mysql
database.spec.compute.mysql.trigger
specifies that compute autoscaling is enabled for this database.spec.compute.mysql.podLifeTimeThreshold
specifies the minimum lifetime for at least one of the pod to initiate a vertical scaling.spec.compute.mysql.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.mysql.minAllowed
specifies the minimum allowed resources for the database.spec.compute.mysql.maxAllowed
specifies the maximum allowed resources for the database.spec.compute.mysql.controlledResources
specifies the resources that are controlled by the autoscaler.spec.compute.mysql.containerControlledValues
specifies which resource values should be controlled. The default is “RequestsAndLimits”.spec.opsRequestOptions.apply
has two supported value :IfReady
&Always
. UseIfReady
if you want to process the opsReq only when the database is Ready. And useAlways
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 MySQLAutoscaler
CR we have shown above,
$ kubectl apply -f https://github.com/kubedb/docs/raw/v2024.11.18/docs/guides/mysql/autoscaler/compute/cluster/examples/my-as-compute.yaml
mysqlautoscaler.autoscaling.kubedb.com/my-as-compute created
Verify Autoscaling is set up successfully
Let’s check that the mysqlautoscaler
resource is created successfully,
$ kubectl get mysqlautoscaler -n demo
NAME AGE
my-as-compute 5m56s
$ kubectl describe mysqlautoscaler my-as-compute -n demo
Name: my-as-compute
Namespace: demo
Labels: <none>
Annotations: <none>
API Version: autoscaling.kubedb.com/v1alpha1
Kind: MySQLAutoscaler
Metadata:
Creation Timestamp: 2022-09-16T11:26:58Z
Generation: 1
Managed Fields:
...
Spec:
Compute:
MySQL:
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-mysql
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: md-coordinator
Vpa Object Name: sample-mysql
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: mysql
Vpa Object Name: sample-mysql
Total Samples Count: 19
Version: v3
Conditions:
Last Transition Time: 2022-09-16T11:27:07Z
Message: Successfully created mysqlDBOpsRequest demo/myops-sample-mysql-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: mysql
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-mysql
Events: <none>
So, the mysqlautoscaler
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 mysqlopsrequest
based on the recommendations, if the database pod resources are needed to scaled up or down.
Let’s watch the mysqlopsrequest
in the demo namespace to see if any mysqlopsrequest
object is created. After some time you’ll see that a mysqlopsrequest
will be created based on the recommendation.
$ kubectl get mysqlopsrequest -n demo
NAME TYPE STATUS AGE
myops-sample-mysql-6xc1kc VerticalScaling Progressing 7s
Let’s wait for the ops request to become successful.
$ kubectl get mysqlopsrequest -n demo
NAME TYPE STATUS AGE
myops-vpa-sample-mysql-z43wc8 VerticalScaling Successful 3m32s
We can see from the above output that the MySQLOpsRequest
has succeeded. If we describe the MySQLOpsRequest
we will get an overview of the steps that were followed to scale the database.
$ kubectl describe mysqlopsrequest -n demo myops-vpa-sample-mysql-z43wc8
Name: myops-sample-mysql-6xc1kc
Namespace: demo
Labels: <none>
Annotations: <none>
API Version: ops.kubedb.com/v1alpha1
Kind: MySQLOpsRequest
Metadata:
Creation Timestamp: 2022-09-16T11:27:07Z
Generation: 1
Managed Fields:
...
Owner References:
API Version: autoscaling.kubedb.com/v1alpha1
Block Owner Deletion: true
Controller: true
Kind: MySQLAutoscaler
Name: my-as-compute
UID: 44bd46c3-bbc5-4c4a-aff4-00c7f84c6f58
Resource Version: 846324
UID: c2b30107-c6d3-44bb-adf3-135edc5d615b
Spec:
Apply: IfReady
Database Ref:
Name: sample-mysql
Timeout: 2m0s
Type: VerticalScaling
Vertical Scaling:
MySQL:
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 MySQLOpsRequest: demo/myops-sample-mysql-6xc1kc
Observed Generation: 1
Reason: OpsRequestProgressingStarted
Status: True
Type: Progressing
Last Transition Time: 2022-09-16T11:30:42Z
Message: Successfully restarted MySQL pods for MySQLOpsRequest: demo/myops-sample-mysql-6xc1kc
Observed Generation: 1
Reason: SuccessfullyRestatedPetSet
Status: True
Type: RestartPetSet
Last Transition Time: 2022-09-16T11:30:47Z
Message: Vertical scale successful for MySQLOpsRequest: demo/myops-sample-mysql-6xc1kc
Observed Generation: 1
Reason: SuccessfullyPerformedVerticalScaling
Status: True
Type: VerticalScaling
Last Transition Time: 2022-09-16T11:30:47Z
Message: Controller has successfully scaled the MySQL demo/myops-sample-mysql-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 MySQLOpsRequest: demo/myops-sample-mysql-6xc1kc
Normal Starting 8m48s KubeDB Enterprise Operator Pausing MySQL databse: demo/sample-mysql
Normal Successful 8m48s KubeDB Enterprise Operator Successfully paused MySQL database: demo/sample-mysql for MySQLOpsRequest: myops-sample-mysql-6xc1kc
Normal Starting 8m43s KubeDB Enterprise Operator Restarting Pod: demo/sample-mysql-0
Normal Starting 7m33s KubeDB Enterprise Operator Restarting Pod: demo/sample-mysql-1
Normal Starting 6m23s KubeDB Enterprise Operator Restarting Pod: demo/sample-mysql-2
Normal Successful 5m13s KubeDB Enterprise Operator Successfully restarted MySQL pods for MySQLOpsRequest: demo/myops-sample-mysql-6xc1kc
Normal Successful 5m8s KubeDB Enterprise Operator Vertical scale successful for MySQLOpsRequest: demo/myops-sample-mysql-6xc1kc
Normal Starting 5m8s KubeDB Enterprise Operator Resuming MySQL database: demo/sample-mysql
Normal Successful 5m8s KubeDB Enterprise Operator Successfully resumed MySQL database: demo/sample-mysql
Normal Successful 5m8s KubeDB Enterprise Operator Controller has Successfully scaled the MySQL database: demo/sample-mysql
Now, we are going to verify from the Pod, and the MySQL 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-mysql-0 -o json | jq '.spec.containers[].resources'
{
"limits": {
"cpu": "250m",
"memory": "400Mi"
},
"requests": {
"cpu": "250m",
"memory": "400Mi"
}
}
$ kubectl get mysql -n demo sample-mysql -o json | jq '.spec.podTemplate.spec.containers[] | select(.name == "mysql") | .resources'
{
"limits": {
"cpu": "250m",
"memory": "400Mi"
},
"requests": {
"cpu": "250m",
"memory": "400Mi"
}
}
The above output verifies that we have successfully autoscaled the resources of the MySQL replicaset database.
Cleaning Up
To clean up the Kubernetes resources created by this tutorial, run:
kubectl delete mysql -n demo sample-mysql
kubectl delete mysqlautoscaler -n demo my-as-compute
kubectl delete mysqlopsrequest -n demo myops-vpa-sample-mysql-z43wc8
kubectl delete mysqlopsrequest -n demo myops-sample-mysql-6xc1kc
kubectl delete ns demo