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Chapter 6. Managing a cluster with multi-architecture compute machines

Managing a cluster that has nodes with multiple architectures requires you to consider node architecture as you monitor the cluster and manage your workloads. This requires you to take additional considerations into account when you schedule workloads in a multi-architecture cluster.

When you deploy workloads on a cluster with compute nodes that use different architectures, you must align pod architecture with the architecture of the underlying node. Your workload may also require additional configuration to particular resources depending on the underlying node architecture.

You can use the Multiarch Tuning Operator to enable architecture-aware scheduling of workloads on clusters with multi-architecture compute machines. The Multiarch Tuning Operator implements additional scheduler predicates in the pods specifications based on the architectures that the pods can support at creation time.

For information about the Multiarch Tuning Operator, see Managing workloads on multi-architecture clusters by using the Multiarch Tuning Operator.

Scheduling a workload to an appropriate node based on architecture works in the same way as scheduling based on any other node characteristic.

Using nodeAffinity to schedule nodes with specific architectures

You can allow a workload to be scheduled on only a set of nodes with architectures supported by its images, you can set the spec.affinity.nodeAffinity field in your pod’s template specification.

Example deployment with node affinity set

apiVersion: apps/v1
kind: Deployment
metadata: # ...
spec:
   # ...
  template:
     # ...
    spec:
      affinity:
        nodeAffinity:
          requiredDuringSchedulingIgnoredDuringExecution:
            nodeSelectorTerms:
            - matchExpressions:
              - key: kubernetes.io/arch
                operator: In
                values:
1 

                - amd64
                - arm64
Copy to Clipboard Toggle word wrap
1
Specify the supported architectures. Valid values include amd64,arm64, or both values.

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