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Updates

Note

This documentation applies to mariadb-operator version >= v0.0.29

This documentation aims to describe the supported strategies to perform updates of the MariaDB resource.

Table of contents

Update strategies

In order to provide you with flexibility for updating MariaDB reliably, this operator supports multiple update strategies:

  • ReplicasFirstPrimaryLast: Roll out replica Pods one by one, wait for each of them to become ready, and then proceed with the primary Pod.
  • RollingUpdate: Utilize the rolling update strategy from Kubernetes.
  • OnDelete: Updates are performed manually by deleting Pods.

Configuration

The update strategy can be configured in the updateStrategy field of the MariaDB resource:

apiVersion: k8s.mariadb.com/v1alpha1
kind: MariaDB
metadata:
  name: mariadb
spec:
  ...
  updateStrategy:
    type: ReplicasFirstPrimaryLast

It defaults to ReplicasFirstPrimaryLast if not provided.

Trigger updates

Updates are not limited to updating the image field in the MariaDB resource, an update will be triggered whenever any field of the Pod template is changed. This translates into making changes to MariaDB fields that map directly or indirectly to the Pod template, for instance, the CPU and memory resources:

apiVersion: k8s.mariadb.com/v1alpha1
kind: MariaDB
metadata:
  name: mariadb
spec:
  ...
- image: mariadb:10.11.7
+ image: mariadb:10.11.8
  resources:
    requests:
      cpu: 200m
      memory: 128Mi
    limits:
-     memory: 1Gi
+     memory: 2Gi

Once the update is triggered, the operator manages it differently based on the selected update strategy.

ReplicasFirstPrimaryLast

This role-aware update strategy consists in rolling out the replica Pods one by one first, waiting for each of them become ready (i.e. readiness probe passed), and then proceed with the primary Pod. This is the default update strategy, as it can potentially meet various reliability requirements and minimize the risks associated with updates:

  • Write operations won't be affected until all the replica Pods have been rolled out. If something goes wrong in the update, such as an update to an incompatible MariaDB version, this is detected early when the replicas are being rolled out and the update operation will be paused at that point.
  • Read operations impact is minimized by only rolling one replica Pod at a time.
  • Waiting for every Pod to be synced minimizes the impact in the clustering protocols and the network.

RollingUpdate

This strategy leverages the rolling update strategy from the StatefulSet resource, which, unlike ReplicasFirstPrimaryLast, does not take into account the role of the Pods(primary or replica). Instead, it rolls out the Pods one by one, from the highest to the lowest StatefulSet index.

You are able to pass extra parameters to this strategy via the rollingUpdate object:

apiVersion: k8s.mariadb.com/v1alpha1
kind: MariaDB
metadata:
  name: mariadb
spec:
  ...
  updateStrategy:
    type: RollingUpdate
    rollingUpdate:
      maxUnavailable: 1

OnDelete

This strategy aims to provide a method to update MariaDB resources manually by allowing users to restart the Pods individually.This way, the user has full control over the update process and can decide which Pods are rolled out at any given time.

Whenever an update is triggered, the MariaDB will be marked as pending to update:

kubectl get mariadbs
NAME             READY   STATUS           PRIMARY POD        AGE
mariadb-galera   True    Pending update   mariadb-galera-0   5m17s

From this point, you are able to delete the Pods to trigger the update, which will result the MariaDB marked as updating:

kubectl get mariadbs
NAME             READY   STATUS     PRIMARY POD        AGE
mariadb-galera   False   Updating   mariadb-galera-0   9m50s

Once all the Pods have been rolled out, the MariaDB resource will be back to a ready state:

kubectl get mariadbs
NAME             READY   STATUS    PRIMARY POD        AGE
mariadb-galera   True    Running   mariadb-galera-1   12m