Skip to main content

Deploy the KFP ML Pipeline from CLI.

Project description

kfp-deployer

Deploy your ml-pipeline with kfp-deploy from cli.

How to use

kfp-deploy https://your-kubeflow-host/ "pipeline-name" ./pipeline_file.yaml

for more detail, see kfp-deploy -h.

what the difference from kfp pipeline upload?

Kubeflow Pipelines requires the all pipelines must have unique names. Otherwise you have to use update the version instead of upload the pipeline. Furthermore, you have to use unique name when uploading the new version of pipeline.

This command does everything required in the upload process for you. This command will communicate with kfp host and automatically determine whether update or upload is required and perform it. Furthermore, the version string is automatically generated based on the upload timestamp.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

kfp-deployer-0.1.2.tar.gz (7.2 kB view hashes)

Uploaded Source

Built Distribution

kfp_deployer-0.1.2-py3-none-any.whl (7.6 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page