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FerretDBAutoscaler

What is FerretDBAutoscaler

FerretDBAutoscaler is a Kubernetes Custom Resource Definitions (CRD). It provides a declarative configuration for autoscaling FerretDB compute resources of FerretDB components in a Kubernetes native way.

FerretDBAutoscaler CRD Specifications

Like any official Kubernetes resource, a FerretDBAutoscaler has TypeMeta, ObjectMeta, Spec and Status sections.

Here, some sample FerretDBAutoscaler CROs for autoscaling different components of ferretdb is given below:

Sample FerretDBAutoscaler for ferretdb:

apiVersion: autoscaling.kubedb.com/v1alpha1
kind: FerretDBAutoscaler
metadata:
  name: ferretdb-auto-scale
  namespace: demo
spec:
  databaseRef:
    name: ferretdb
  compute:
    primary:
      trigger: "On"
      podLifeTimeThreshold: 24h
      minAllowed:
        cpu: 250m
        memory: 350Mi
      maxAllowed:
        cpu: 1
        memory: 1Gi
      controlledResources: ["cpu", "memory"]
      containerControlledValues: "RequestsAndLimits"
      resourceDiffPercentage: 10

Here, we are going to describe the various sections of a FerretDBAutoscaler crd.

A FerretDBAutoscaler object has the following fields in the spec section.

spec.databaseRef

spec.databaseRef is a required field that point to the FerretDB object for which the autoscaling will be performed. This field consists of the following sub-field:

• spec.databaseRef.name : specifies the name of the FerretDB object.

spec.compute

spec.compute specifies the autoscaling configuration for the compute resources i.e. cpu and memory of FerretDB components. This field consists of the following sub-field:

• primary indicates autoscaling information for ferretdb primary server.
• secondary indicates autoscaling information for ferretdb secondary server.

On each spec.compute.primary or spec.compute.secondary field, these are the sub-field:

• trigger indicates if compute autoscaling is enabled for this component of the ferretdb. If “On” then compute autoscaling is enabled. If “Off” then compute autoscaling is disabled.
• minAllowed specifies the minimal amount of resources that will be recommended, default is no minimum.
• maxAllowed specifies the maximum amount of resources that will be recommended, default is no maximum.
• controlledResources specifies which type of compute resources (cpu and memory) are allowed for autoscaling. Allowed values are “cpu” and “memory”.
• containerControlledValues specifies which resource values should be controlled. Allowed values are “RequestsAndLimits” and “RequestsOnly”.
• resourceDiffPercentage specifies the minimum resource difference between recommended value and the current value in percentage. If the difference percentage is greater than this value than autoscaling will be triggered.
• podLifeTimeThreshold specifies the minimum pod lifetime of at least one of the pods before triggering autoscaling.