Kubeflow Pipelines is a platform for building and deploying portable, scalable machine learning (ML) workflows based on Docker containers. It provides a set of tools to compose, deploy, and manage ML workflows on Kubernetes. The platform is designed to enable rapid and reliable experimentation, and it supports end-to-end orchestration of ML pipelines.
When working with Kubeflow Pipelines, you might encounter an error message stating InvalidPipelineVersion. This error typically appears when you attempt to execute a pipeline run with a version that the system cannot recognize or locate.
The error message might look something like this:
Error: InvalidPipelineVersion - The specified pipeline version is invalid or does not exist.
The InvalidPipelineVersion error occurs when the pipeline version specified in your request does not match any existing versions in the Kubeflow Pipelines system. This can happen due to a typo, a deleted version, or a version that was never created.
To resolve the InvalidPipelineVersion error, follow these steps:
Ensure that the pipeline version you are trying to use exists. You can list all available pipeline versions using the Kubeflow Pipelines UI or the command line interface (CLI).
kubectl get pipelines -n kubeflow
Check the list of versions and confirm that the version you are using is present.
If you find a typo or incorrect reference, update your code or configuration to use the correct version. Double-check the spelling and format of the version string.
If the version does not exist, you may need to create it. You can do this by uploading the pipeline again and specifying the desired version.
dsl-compile --py my_pipeline.py --output my_pipeline.yaml
kubectl apply -f my_pipeline.yaml -n kubeflow
For more information on managing pipeline versions, refer to the Kubeflow Pipelines SDK documentation. You can also explore the Kubeflow Pipelines GitHub repository for examples and community support.
(Perfect for DevOps & SREs)
(Perfect for DevOps & SREs)
