Customize a Pod#

In a Determined cluster running on Kubernetes, tasks (e.g., experiments, notebooks) are executed by launching one or more Kubernetes pods. You can customize these pods by providing custom pod specs. Common use cases include assigning pods to specific nodes, specifying additional volume mounts, and attaching permissions. Configuring pod specs is not required to use Determined on Kubernetes.

In this topic guide, we will cover:

  1. How Determined uses pod specs.

  2. The different ways to configure custom pod specs.

  3. Supported pod spec fields.

  4. How to configuring default pod specs.

  5. How to configuring per-task pods specs.

How Determined Uses Pod Specs#

All Determined tasks are launched as pods. Determined pods consists of an initContainer named determined-init-container and a container named determined-container which executes the workload. When users provide a pod spec, Determined inserts the determined-init-container and determined-container into the provided pod spec. As described below, users may also configure some of the fields for the determined-container.

Ways to Configure Pod Specs#

Determined provides two ways to configure pod specs. When Determined is installed, the system administrator can configure pod specs that are used by default for all GPU and CPU tasks. In addition, you can specify a custom pod spec for individual tasks (e.g., for an experiment by specifying environment.pod_spec in the experiment configuration). If a custom pod spec is specified for a task, it overrides the default pod spec (if any).

Supported Pod Spec Fields#

This section describes which fields users can and cannot configure when specifying custom pod specs.

Determined does not currently support configuring:

  • Pod Name - Determined automatically assigns a name for every pod that is created.

  • Pod Namespace - Determined automatically sets the pod namespace based on the resource pool the task belongs to. The mapping between resource pools and namespaces can be configured in the resourcePools section of the Helm values.yaml.

  • Host Networking - This must be configured via the master configuration.

  • Restart Policy - This is always set to Never.

As part of their pod spec, users can specify initContainers and containers. Additionally users can configure the determined-container that executes the task (e.g., training), by setting the container name in the pod spec to determined-container. For the determined-container, Determined currently supports configuring:

  • Resource requests and limits (except GPU resources).

  • Volume mounts and volumes.

Default Pod Specs#

Default pod specs must be configured when installing or upgrading Determined. The default pod specs are configured in values.yaml of the Helm Chart Configuration Reference under taskContainerDefaults.cpuPodSpec and taskContainerDefaults.gpuPodSpec. The gpuPodSpec is applied to all tasks that use GPUs (e.g., experiments, notebooks). cpuPodSpec is applied to all tasks that only use CPUs (e.g., TensorBoards, CPU-only notebooks). Fields that are not specified will remain at their default Determined values.

Example of configuring default pod specs in values.yaml:

taskContainerDefaults:
  cpuPodSpec:
    apiVersion: v1
    kind: Pod
    metadata:
      labels:
        customLabel: cpu-label
    spec:
      containers:
        # Will be applied to the container executing the task.
        - name: determined-container
          volumeMounts:
            - name: example-volume
              mountPath: /example-data
        # Custom sidecar container.
        - name: sidecar-container
          image: alpine:latest
      volumes:
        - name: example-volume
          hostPath:
            path: /data
  gpuPodSpec:
    apiVersion: v1
    kind: Pod
    metadata:
      labels:
        customLabel: gpu-label
    spec:
      containers:
        - name: determined-container
          volumeMounts:
            - name: example-volume
              mountPath: /example-data
      volumes:
        - name: example-volume
          hostPath:
            path: /data

The default pod specs can also be configured on a resource pool level. GPU jobs submitted in the resource pool will have the task spec applied. If a job is submitted in a resource pool with a matching CPU / GPU pod spec then the top level taskContainerDefaults.gpuPodSpec or taskContainerDefaults.cpuPodSpec will not be applied.

Example of configuring resource pool default pod spec in values.yaml.

resourcePools:
  - pool_name: prod_pool
    kubernetes_namespace: default
    task_container_defaults:
      gpu_pod_spec:
        apiVersion: v1
        kind: Pod
        spec:
          affinity:
            nodeAffinity:
              requiredDuringSchedulingIgnoredDuringExecution:
                nodeSelectorTerms:
                  - matchExpressions:
                      - key: topology.kubernetes.io/zone
                        operator: In
                        values:
                          - antarctica-west1

Per-task Pod Specs#

In addition to default pod specs, it is also possible to configure custom pod specs for individual tasks. Pod specs for individual tasks can be configured under the environment field in the experiment config (for experiments) or the task configuration (for other tasks).

Example of configuring a pod spec for an individual task:

environment:
  pod_spec:
    apiVersion: v1
    kind: Pod
    metadata:
      labels:
        customLabel: task-specific-label
    spec:
      # Specify a pull secret for task container image.
      imagePullSecrets:
        - name: regcred
      # Specify a service account that allows writing checkpoints to S3 (for EKS).
      serviceAccountName: <checkpoint-storage-s3-bucket>
      # Specify tolerations for scheduling on tainted nodes.
      tolerations:
        - key: "tained-nodegroup-name"
          operator: "Equal"
          value: "true"
          effect: "NoSchedule"

When a custom pod spec is provided for a task, it will merge with the default pod spec (either resourcePools.task_container_defaults or top level task_container_defaults if resourcePools.task_container_defaults is not specified) according to Kubernetes strategic merge patch. Determined does not support setting the strategic merge patch strategy, so the section titled “Use strategic merge patch to update a Deployment using the retainKeys strategy” in the linked Kubernetes docs will not work.

Some fields in pod specs are merged by values of items in lists. Volumes for example are merged by volume name. If for some reason you would want to remove a volume mount specific in the default task container you would need to override it with an empty volume of the same path.

Example values.yaml

resourcePools:
  - pool_name: prod_pool
    kubernetes_namespace: default
    task_container_defaults:
      gpu_pod_spec:
        apiVersion: v1
        kind: Pod
        spec:
          volumes:
            - name: secret-volume
              secret:
                secretName: prod-test-secret
          containers:
            - name: determined-container
              volumeMounts:
                - name: secret-volume
                  mountPath: /etc/secret-volume

Example expconf.yaml

environment:
  pod_spec:
    apiVersion: v1
    kind: Pod
    spec:
      volumes:
        - name: empty-dir-override
          emptyDir:
            sizeLimit: 100Mi
      containers:
        - name: determined-container
          volumeMounts:
            - name: empty-dir-override
              mountPath: /etc/secret-volume
resources:
  resource_pool: prod_pool