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Binding Percona Server for MongoDB components to Specific Kubernetes/OpenShift Nodes

The operator does a good job of automatically assigning new pods to nodes to achieve balanced distribution across the cluster. There are situations when you must ensure that pods land on specific nodes: for example, for the advantage of speed on an SSD-equipped machine, or reduce costs by choosing nodes in the same availability zone.

The appropriate (sub)sections (replsets, replsets.arbiter, backup, etc.) of the deploy/cr.yaml file contain the keys which can be used to do assign pods to nodes.

Node selector

The nodeSelector contains one or more key-value pairs. If the node is not labeled with each key-value pair from the Pod’s nodeSelector, the Pod will not be able to land on it.

The following example binds the Pod to any node having a self-explanatory disktype: ssd label:

  disktype: ssd

Affinity and anti-affinity

Affinity defines eligible pods that can be scheduled on the node which already has pods with specific labels. Anti-affinity defines pods that are not eligible. This approach is reduces costs by ensuring several pods with intensive data exchange occupy the same availability zone or even the same node or, on the contrary, to spread the pods on different nodes or even different availability zones for high availability and balancing purposes.

Percona Operator for MongoDB provides two approaches for doing this:

  • simple way to set anti-affinity for Pods, built-in into the Operator,
  • more advanced approach based on using standard Kubernetes constraints.

Simple approach - use antiAffinityTopologyKey of the Percona Operator for MongoDB

Percona Operator for MongoDB provides an antiAffinityTopologyKey option, which may have one of the following values:

  • - Pods will avoid residing within the same host,
  • - Pods will avoid residing within the same zone,
  • - Pods will avoid residing within the same region,
  • none - no constraints are applied.

The following example forces Percona Server for MongoDB Pods to avoid occupying the same node:

  antiAffinityTopologyKey: ""

Advanced approach - use standard Kubernetes constraints

The previous method can be used without special knowledge of the Kubernetes way of assigning Pods to specific nodes. Still, in some cases, more complex tuning may be needed. In this case, the advanced option placed in the deploy/cr.yaml file turns off the effect of the antiAffinityTopologyKey and allows the use of the standard Kubernetes affinity constraints of any complexity:

       - labelSelector:
           - key: security
             operator: In
             - S1
       - weight: 100
             - key: security
               operator: In
               - S2
         - matchExpressions:
           - key:
             operator: In
             - e2e-az1
             - e2e-az2
       - weight: 1
           - key: another-node-label-key
             operator: In
             - another-node-label-value

See explanation of the advanced affinity options in Kubernetes documentation .

Topology Spread Constraints

Topology Spread Constraints allow you to control how Pods are distributed across the cluster based on regions, zones, nodes, and other topology specifics. This can be useful for both high availability and resource efficiency.

Pod topology spread constraints are controlled by the topologySpreadConstraints subsection, which can be put into replsets, sharding.configsvrReplSet, and sharding.mongos sections of the deploy/cr.yaml configuration file as follows:

  - labelSelector:
      matchLabels: percona-server-mongodb
    maxSkew: 1
    whenUnsatisfiable: DoNotSchedule

You can see the explanation of these affinity options in Kubernetes documentation .


Tolerations allow Pods having them to be able to land onto nodes with matching taints. Toleration is expressed as a key with and operator, which is either exists or equal (the equal variant requires a corresponding value for comparison).

Toleration should have a specified effect, such as the following:

  • NoSchedule - less strict
  • PreferNoSchedule
  • NoExecute

When a taint with the NoExecute effect is assigned to a Node, any Pod configured to not tolerating this taint is removed from the node. This removal can be immediate or after the tolerationSeconds interval. The following example defines this effect and the removal interval:

- key: ""
  operator: "Exists"
  effect: "NoExecute"
  tolerationSeconds: 6000

The Kubernetes Taints and Toleratins contains more examples on this topic.

Priority Classes

Pods may belong to some priority classes. This flexibility allows the scheduler to distinguish more and less important Pods when needed, such as the situation when a higher priority Pod cannot be scheduled without evicting a lower priority one. This ability can be accomplished by adding one or more PriorityClasses in your Kubernetes cluster, and specifying the PriorityClassName in the deploy/cr.yaml file:

priorityClassName: high-priority

See the Kubernetes Pods Priority and Preemption documentation to find out how to define and use priority classes in your cluster.

Pod Disruption Budgets

Creating the Pod Disruption Budget is the Kubernetes method to limit the number of Pods of an application that can go down simultaneously due to voluntary disruptions such as the cluster administrator’s actions during a deployment update. Distribution Budgets allow large applications to retain their high availability during maintenance and other administrative activities. The maxUnavailable and minAvailable options in the deploy/cr.yaml file can be used to set these limits. The recommended variant is the following:

   maxUnavailable: 1

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Last update: 2024-06-24