Prior to this commit, there was a workflow template added for every unique
retryStrategy setting. This is now consolidates to a single retryStrategy
template.
Signed-off-by: agoins <alyssacgoins@gmail.com>
* feat(backend/sdk): enable dsl.Collected for params & artifacts
Signed-off-by: zazulam <m.zazula@gmail.com>
* feat(backend): collect through loops & dags
Signed-off-by: zazulam <m.zazula@gmail.com>
To enable users to use loops similar to subdags, the initial collecting
implementation went only 1 layer deep of loops/subdags. This
implementation serves to handle multifacted approaches of pipelines that
users can generate.
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Signed-off-by: zazulam <m.zazula@gmail.com>
* add backend support for k8s platform inputs
This change adds driver support for input parameter support for the
kubernetes platform spec. Input resolution change is extracted and made
more generic so it may be re-used when building out the container spec
for the k8s config.
Also add unit tests for constant & runtime input parameters.
TaskOutput parameter support are omitted due to a lack of appropriate
mlmd mock framework.
Signed-off-by: Humair Khan <HumairAK@users.noreply.github.com>
* add sdk implementation for k8s params inputs
Signed-off-by: Humair Khan <HumairAK@users.noreply.github.com>
* add tests for k8s input params
Signed-off-by: Humair Khan <HumairAK@users.noreply.github.com>
* add setup/teardown of prereqs and secret tests
and update/re-enable secret env tests
Signed-off-by: Humair Khan <HumairAK@users.noreply.github.com>
* have kfp sample tests use local python pkgs
Signed-off-by: Humair Khan <HumairAK@users.noreply.github.com>
* use a better configmap k8s name input...
Add support for multiple input types for pull secrets.
Clarify toleration docstring
Remove unnecessary resolve function
Signed-off-by: Humair Khan <HumairAK@users.noreply.github.com>
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Signed-off-by: Humair Khan <HumairAK@users.noreply.github.com>
This allows dsl.import to leverage Modelcar container images in an OCI
repository. This works by having an init container prepull the image and
then adding a sidecar container when the launcher container is running.
The Modelcar container adds a symlink to its /models directory in an
emptyDir volume that is accessible by the launcher container. Once the
launcher is done running the user code, it stops the Modelcar
containers.
This approach has the benefit of leveraging image pull secrets
configured on the Kubernetes cluster rather than require separate
credentials for importing the artifact. Additionally, no data is copied
to the emptyDir volume, so the storage cost is just pulling the Modelcar
container image on the Kubernetes worker node.
Note that once Kubernetes supports OCI images as volume mounts for
several releases, consider replacing the init container with that
approach.
This also adds a new environment variable of PIPELINE_RUN_AS_USER to
set the runAsUser on all Pods created by Argo Workflows.
Resolves:
https://github.com/kubeflow/pipelines/issues/11584
Signed-off-by: mprahl <mprahl@users.noreply.github.com>
This adds support for the following placeholders in the KFP backend:
- dsl.PIPELINE_JOB_NAME_PLACEHOLDER
- dsl.PIPELINE_JOB_RESOURCE_NAME_PLACEHOLDER
- dsl.PIPELINE_JOB_ID_PLACEHOLDER
- dsl.PIPELINE_TASK_NAME_PLACEHOLDER
- dsl.PIPELINE_TASK_ID_PLACEHOLDER
Resolves:
https://github.com/kubeflow/pipelines/issues/10453
Signed-off-by: mprahl <mprahl@users.noreply.github.com>
Alyssa Goins
Michael
Humair Khan
Matt Prahl
Alex
Helber Belmiro