Interactive Workload Parameters¶
The following is a full list of all interactive workload parameters. The text below is equivalent to running kubectl explain interactiveworkload.spec. You can also run kubectl explain interactiveworkload.spec.<parameter-name> to see the description of a specific parameter.
KIND: InteractiveWorkload
VERSION: run.ai/v2alpha1
RESOURCE: spec <Object>
DESCRIPTION:
The specifications of this InteractiveWorkload
FIELDS:
active <Object>
kubebuilder:default:={value: true} Specifies whether the workload should be
active or suspended.
allowPrivilegeEscalation <Object>
Allow the container running the workload and all launched processes to gain
additional privileges after the workload starts. For more information see
the "User Identity in Container" guide at
https://docs.run.ai/admin/runai-setup/config/non-root-containers/
annotations <Object>
Specifies annotations to be set in the container that is running the
created workload.
arguments <Object>
When set,contains the arguments sent along with the command. These override
the entry point of the image in the created workload.
autoDeletionTimeAfterCompletionSeconds <Object>
Specifies the duration after which it is possible for a finished workload
to be automatically deleted. When the workload is being deleted, its
lifecycle guarantees (e.g. finalizers) will be honored. If this field is
unset, the workload won't be automatically deleted. If this field is set to
zero, the workload becomes eligible to be deleted immediately after it
finishes.
baseWorkload <string>
Reference to another workload. When set, this workload inherits its values
from the base workload. Base workload can either reside on the same
namespace of this workload (referred to as "user" template) or can reside
in the runai namespace (referred to as a "global" template)
capabilities <Object>
The capabilities field allows adding a set of unix capabilities to the
container running the workload. Capabilities are Linux distinct privileges
traditionally associated with superuser which can be independently enabled
and disabled. For more information see
https://kubernetes.io/docs/tasks/configure-pod-container/security-context/#set-capabilities-for-a-container
command <Object>
If set, overrides the image's entry point with the supplied command.
cpu <Object>
Specifies CPU units to allocate for the created workload (0.5, 1, .etc).
The workload will receive at least this amount of CPU. Note that the
workload will not be scheduled unless the system can guarantee this amount
of CPUs to the workload.
cpuLimit <Object>
Specifies a limit on the number of CPUs consumed by the workload (0.5, 1,
.etc). The system guarantees that this workload will not be able to consume
more than this amount of CPUs.
createHomeDir <Object>
Instructs the system to create a temporary home directory for the user
within the container. Data stored in this directory will not be saved when
the container exits. When the runAsUser flag is set to true, this flag will
default to true as well.
environment <Object>
Specifies environment variables to be set in the container running the
created workload.
exposedUrls <Object>
Specifies a set of exported url (e.g. ingress) from the container running
the created workload.
extendedResources <Object>
Specifies values for extended resources. Extended resources are third-party
devices (such as high-performance NICs, FPGAs, or InfiniBand adapters) that
you want to allocate to your Job. For more information see:
https://kubernetes.io/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins/
gitSync <Object>
Specifies git repositories to mount into the container running the
workload.
gpu <Object>
Specifies the number on the number of GPUs to allocate for the created
workload. The default is no allocated GPUs. The GPU value can be an integer
or a fraction between 0 and 1.
gpuLimit <Object>
Specifies a limit on the GPUs to allocate for this workload (1G, 20M,
.etc). Intended to use for Opportunistic jobs (with the smart
node-scheduler).
gpuMemory <Object>
Specifies GPU memory to allocate for the created workload. The workload
will receive this amount of memory. Note that the workload will not be
scheduled unless the system can guarantee this amount of GPU memory to the
workload.
hostIpc <Object>
Specifies that the created workload will use the host's ipc namespace.
hostNetwork <Object>
Specifies that the created workload will use the host's network stack
inside its container. For more information see the Docker Run Reference at
https://docs.docker.com/engine/reference/run/
image <Object>
Specifies the image to use when creating the container running the
workload.
imagePullPolicy <Object>
Specifies the pull policy of the image when starting a container running
the created workload. Options are: always, ifNotPresent, or never. For more
information see: https://kubernetes.io/docs/concepts/containers/images
ingressUrl <Object>
This field is for internal use only.
jupyter <Object>
Indication if an interactive workload should run jupyter notebook
labels <Object>
Specifies labels to be set in the container running the created workload.
largeShm <Object>
Specifies a large /dev/shm device to mount into a container running the
created workload. SHM is a shared file system mounted on RAM.
memory <Object>
Specifies the amount of CPU memory to allocate for this workload (1G, 20M,
.etc). The workload will receive at least this amount of memory. Note that
the workload will not be scheduled unless the system can guarantee this
amount of memory to the workload
memoryLimit <Object>
Specifies a limit on the CPU memory to allocate for this workload (1G, 20M,
.etc). The system guarantees that this workload will not be able to consume
more than this amount of memory. The workload will receive an error when
trying to allocate more memory than this limit.
migProfile <Object>
Specifies the memory profile to be used for workload running on NVIDIA
Multi-Instance GPU (MIG) technology.
mountPropagation <Object>
Allows for sharing volumes mounted by a container to other containers in
the same pod, or even to other pods on the same node. The volume mount will
receive all subsequent mounts that are mounted to this volume or any of its
subdirectories.
mpi <Object>
This workload produces mpijob
name <Object>
The specific name of the created resource. Either name of namePrefix should
be provided, but not both.
namePrefix <Object>
A prefix used for assigning a name to the created resource. Either name of
namePrefix should be provided, but not both.
nfs <Object>
Specifies nfs volumes to mount into a container running the created
workload.
nodePool <Object>
Specifies the NodePool name to be used to schedule this job on - DEPRECATED
use NodePools instead
nodePools <Object>
Specifies the list of node pools to use for scheduling the job, ordered by
preference.
nodeType <Object>
Specifies nodes (machines) or a group of nodes on which the workload will
run. To use this feature, your Administrator will need to label nodes as
explained in the Group Nodes guide at
https://docs.run.ai/admin/researcher-setup/limit-to-node-group. This flag
can be used in conjunction with Project-based affinity. In this case, the
flag is used to refine the list of allowable node groups set in the
Project. For more information see the Projects setup guide at
https://docs.run.ai/admin/admin-ui-setup/project-setup.
notebookToken <Object>
A token for connecting to a Jupyter Notebook created for workloads of type
Jupyter. When token authentication is enabled, the notebook uses this token
to authenticate requests. For more information see:
https://jupyter-notebook.readthedocs.io/en/stable/security.html
podAffinity <Object>
Indicates whether pod affinity scheduling rules apply.
podAffinitySchedulingRule <Object>
Indicates if we want to use the Pod affinity rule as : the "hard"
(required) or the "soft" (preferred) This field can be specified only if
PodAffinity is set to true
podAffinityTopology <Object>
Specifies the Pod Affinity Topology to be used for scheduling the job This
field can be specified only if PodAffinity is set to true
ports <Object>
Specifies a set of ports exposed from the container running the created
workload. Used together with --service-type.
preemptible <Object>
Specifies that the created workload will be preemptible. Interactive
preemptible workloads can be scheduled above the guaranteed quota but may
be reclaimed at any time.
preemptionLimit <Object>
indicates the number of times the job can be preempted
processes <Object>
Number of distributed training processes that will be allocated for the
created mpijob.
pvcs <Object>
Specifies persistent volume claims to mount into a container running the
created workload.
runAsGid <Object>
Specifies the Unix group id with which the container should run. Will be
used only if runAsUser is set to true.
runAsNonRoot <Object>
Indicates that the container must run as a non-root user. If true, the
Kubelet will validate the image at runtime to ensure that it does not run
as UID 0 (root) and fail to start the container if it does. If unset or
false, no such validation will be performed.
runAsUid <Object>
Specifies the Unix user id with which the container running the created
workload should run. Will be used only if runAsUser is set to true.
runAsUser <Object>
Limits the container running the created workload to run in the context of
a specific non-root user. The user id is provided by the runAsUid field.
This would manifest itself in access to operating system resources, in the
ownership of new folders created under shared directories, etc.
Alternatively, if your cluster is connected to Run:ai via SAML, you can map
the container to use the Linux UID/GID which is stored in the
organization's directory. For more information see the User Identity guide
at https://docs.run.ai/admin/runai-setup/config/non-root-containers/
s3 <Object>
Specifies S3 buckets to mount into the container running the workload
seccompProfileType <Object>
Indicates which kind of seccomp profile will be applied to the container.
Valid options are: RuntimeDefault - the container runtime default profile
should be used. Unconfined - no profile should be applied. Localhost is not
yet supported by Run:ai.
serviceType <Object>
Specifies the default service exposure method for ports. The default shall
be used for ports which do not specify service type. Options are:
LoadBalancer, NodePort or ClusterIP. For more information see the External
Access to Containers guide on
https://docs.run.ai/admin/runai-setup/config/allow-external-access-to-containers/
slotsPerWorker <Object>
Number of slots to allocate per worker in the created mpijob.
stdin <Object>
Instructs the system to keep stdin open for the container(s) running the
created workload, even if nothing is attached.
supplementalGroups <Object>
';' separated list of supplemental group IDs. Will be added to the security
context of the container running the created workload.
tensorboard <Object>
Indicates that this interactive workload should also run a TensorBoard
dashboard
tensorboardLogdir <Object>
The TensorBoard Logs directory
terminateAfterPreemption <Object>
Indicates whether the job should be terminated, by the system, after it has
been preempted. Default to false.
tolerations <Object>
Toleration rules which apply to the pods running the workload. Toleration
rules guide (but do not require) the system to which node each pod can be
scheduled to or evicted from, based on matching between those rules and the
set of taints defined for each Kubernetes node.
tty <Object>
Instructs the system to allocate a pseudo-TTY for the created workload.
usage <string>
The intended usage of this workload. possible values are "Template": this
workload is used as the base for other workloads. "Submit": this workload
is used for submitting a job and/or other Kubernetes resources.
userId <Object>
The user ID ("Subject" in the jwt-token) of the authenticated user who owns
the workload. The data might be used for authentication or authorization
purposes.
username <Object>
Display-only field describing the user who owns the workload. The data is
not used for authentication or authorization purposes.
volumes <Object>
Specifies volumes to mount into a container running the created workload.
workingDir <Object>
Specifies a directory that will be used as the current directory when the
container running the created workload starts.