couler-proj/couler

Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.

44
/ 100
Emerging

This system helps machine learning engineers and data scientists build and manage complex ML workflows in the cloud more easily. It takes your ML pipeline code and generates optimized workflows for execution on systems like Argo Workflows, handling tasks like caching, parallelization, and hyperparameter tuning. The result is a streamlined, efficient, and standardized way to run your ML experiments and models.

943 stars. No commits in the last 6 months.

Use this if you are a machine learning engineer or data scientist struggling with the complexity and varying interfaces of different cloud workflow engines for your ML pipelines.

Not ideal if you need a solution that currently supports multiple workflow engines beyond Argo Workflows, or if you require full access to all features of a specific engine like Airflow.

machine-learning-operations cloud-ml workflow-orchestration data-pipeline-management ml-experiment-tracking
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 18 / 25

How are scores calculated?

Stars

943

Forks

88

Language

Python

License

Apache-2.0

Last pushed

Oct 08, 2024

Commits (30d)

0

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