Server Configuration
By default, you can use Kubeflow Pipelines deployment manifests as provided, which aim to offer a standard configuration for most use cases. At the meantime, customizations are available for more advanced usage.
When deploying Kubeflow Pipelines servers, you can pass various environment variables to customize the behavior of servers.
Frontend Server
When deploying frontend server called ml-pipeline-ui
, you can pass various environment
variables to customize the server behavior for your namespace. Some examples are shown
in the ml-pipeline-ui-deployment.yaml.
Artifact storage endpoint allowlist
You can configure ALLOWED_ARTIFACT_DOMAIN_REGEX
to allowlist object storage endpoint
that your frontend server will fetch artifacts from. If the domain that frontend server
tries to fetch does not match the regular expression defined in
ALLOWED_ARTIFACT_DOMAIN_REGEX
, it will return error to users that the requested domain
is not allowed.
Standalone Kubeflow Pipelines deployment
By default, the value for ALLOWED_ARTIFACT_DOMAIN_REGEX
is "^.*$"
. You can customize
this value for your users, for example: ^.*.yourdomain$
in the
ml-pipeline-ui-deployment.yaml.
Full fledged Kubeflow deployment
For full fledged Kubeflow, each namespace corresponds to a project with the same name.
To configure the ALLOWED_ARTIFACT_DOMAIN_REGEX
value for user namespace, add an entry in ml-pipeline-ui-artifact
just like this example in sync.py for ALLOWED_ARTIFACT_DOMAIN_REGEX
environment variable,
the entry is identical to the environment variable instruction in Standalone Kubeflow Pipelines
deployment.
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