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 primary goal of Kubeflow Pipelines is to simplify the orchestration of complex ML workflows and enable reproducibility and collaboration.
When working with Kubeflow Pipelines, you may encounter an error message indicating an InvalidPipelineName. This error typically occurs when you attempt to create or update a pipeline with a name that does not meet the required naming conventions.
The error message might look something like this:
Error: InvalidPipelineName - The specified pipeline name is invalid or contains unsupported characters.
The InvalidPipelineName error arises when the pipeline name you provide does not adhere to the naming conventions enforced by Kubeflow Pipelines. These conventions are in place to ensure that pipeline names are valid identifiers within the Kubernetes ecosystem.
To resolve the InvalidPipelineName error, follow these steps:
Ensure that the pipeline name you are using adheres to the naming conventions. Check for any unsupported characters or incorrect formats.
If the pipeline name does not meet the conventions, modify it accordingly. For example, if your pipeline name is My_Pipeline_123, change it to my-pipeline-123.
Once you have a valid pipeline name, update your pipeline configuration with the new name. You can use the Kubeflow Pipelines UI or the command-line interface (CLI) to make these changes.
kubectl apply -f your_pipeline.yaml
For more information on Kubeflow Pipelines and naming conventions, refer to the following resources:
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