The module lifecycle stage: Preview

ValkeyClass

The Cluster Wide ValkeyClass resource allows restricting the creation of invalid configurations and predefining some values.
Each Valkey resource must be associated with an existing ValkeyClass resource.
Before deploying the service, all configuration will be checked against the corresponding ValkeyClass.

Sizing Policies

The structure allows creating a set of sizing policies for associated Valkey resources.
This helps avoid uneven distribution of CPU and Memory resources on cluster nodes.
The determining factor for choosing a particular policy is falling within the cores interval.
Then compliance with other fields of the specific policy will be checked.

spec:
  sizingPolicies:
    - cores:
        min: 1
        max: 4
      memory:
        min: 100Mi
        max: 1Gi
        step: 1Mi
      coreFraction: [10, 30, 50]
    - cores:
        min: 5
        max: 10
      memory:
        min: 500Mi
        max: 2Gi
      coreFraction: [50, 70, 100]

Validation Rules

CEL (Common Expression Language) syntax is used to create flexible validation mechanisms.
We provide a set of predefined variables that can be used in rule:

  • configuration.maxMemory int
  • configuration.maxMemoryPolicy string
  • configuration.save string
  • configuration.appendOnly string
  • instance.memory.size int
  • instance.cpu.cores int
spec:
  validations:
    - message: "maxMemory should be less then instance.memory.size at least for 10%"
      rule: "configuration.maxMemory <= instance.memory.size - instance.memory.size / 10"

Overridable Configuration

A whitelist of configuration parameters that can be overridden in the Valkey resource.
List of all possible parameters.

spec:
  overridableConfiguration:
    - maxMemory
    - maxMemoryPolicy

Configuration

Configuration parameters that can be defined at the ValkeyClass level.
Values of these parameters will override defaults for all associated Valkey resources.
Note: Parameters that were allowed and overridden in overridableConfiguration will take priority.

spec:
  configuration:
    maxMemoryPolicy: Noeviction
    save: "360 100"
    appendOnly: "No"

Default values set by Valkey Operator follow this logic:

  • save: ""
  • appendOnly: “no”
  • maxMemory: spec.instance.memory.size * 0.9

Affinity

Standard Kubernetes mechanism for managing scheduling of deployed pods.

spec:
  nodeAffinity:
    requiredDuringSchedulingIgnoredDuringExecution:
      nodeSelectorTerms:
      - matchExpressions:
        - key: "node.deckhouse.io/group"
          operator: "In"
          values:
          - "valkey"

Tolerations

Standard Kubernetes mechanism for managing scheduling of deployed pods.

spec:
  tolerations:
  - key: primary-role
    operator: Equal
    value: valkey
    effect: NoSchedule

Node Selector

Standard Kubernetes mechanism for managing scheduling of deployed pods.

  nodeSelector:
    "node.deckhouse.io/group": "valkey"

Usage Examples

Basic Usage

apiVersion: managed-services.deckhouse.io/v1alpha1
kind: ValkeyClass
spec:
  overridableConfiguration:
    - maxMemoryPolicy
    - save
    - appendOnly
    - maxMemory

  configuration:
    maxMemoryPolicy: Noeviction
    save: "360 100"
    appendOnly: "No"

  sizingPolicies:
    - cores:
        min: 1
        max: 4
      memory:
        min: 128Mi
        max: 2Gi
        step: 128Mi
      coreFractions:
        - "25%"
        - "50%"
        - "75%"
        - "100%"
    - cores:
        min: 5
        max: 8
      memory:
        min: 2Gi
        max: 8Gi
        step: 1Gi
      coreFractions:
        - "25%"
        - "50%"
        - "75%"
        - "100%"

  validations:
    - message: "maxMemory should be less then instance.memory.size at least for 10%"
      rule: "configuration.maxMemory <= instance.memory.size - instance.memory.size / 10"