Kubeflow Pipelines (KFP) Platform
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A Kubeflow Pipelines (KFP) Platform is a ML workflow platform within Kubeflow.
- Context:
- …
- Example(s):
- Kubeflow Pipelines, v0.3.0 [1] (~2020/03/23).
- Kubeflow Pipelines, v1.4.0 [2] (~2021/02/16)
- …
- Counter-Example(s):
- See: Argo, Argo Workflow.
References
2020
- https://www.kubeflow.org/docs/pipelines/overview/pipelines-overview/
- QUOTE: ... Kubeflow Pipelines is a platform for building and deploying portable, scalable machine learning (ML) workflows based on Docker containers. ...
… The Kubeflow Pipelines platform consists of:
- A user interface (UI) for managing and tracking experiments, jobs, and runs.
- An engine for scheduling multi-step ML workflows.
- An SDK for defining and manipulating pipelines and components.
- Notebooks for interacting with the system using the SDK.
- The following are the goals of Kubeflow Pipelines:
- End-to-end orchestration: enabling and simplifying the orchestration of machine learning pipelines.
- Easy experimentation: making it easy for you to try numerous ideas and techniques and manage your various trials/experiments.
- Easy re-use: enabling you to re-use components and pipelines to quickly create end-to-end solutions without having to rebuild each time.
- QUOTE: ... Kubeflow Pipelines is a platform for building and deploying portable, scalable machine learning (ML) workflows based on Docker containers. ...
2020
- https://towardsdatascience.com/build-your-data-pipeline-on-kubernetes-using-kubeflow-pipelines-sdk-and-argo-eef69a80237c
- QUOTE: ... One of those services is Kubeflow Pipelines (KFP), which is a platform for building and deploying portable, scalable machine learning (ML) workflows based on Docker containers. It has a user interface for managing and tracking experiments, jobs, and runs. There is a subtle distinction between Argo Workflows and KFP. Argo is the workflow engine behind KFP and KFP is meant mainly for ML- related usages.