kubeflow / kubeflow/katib

A metrics collector for Kubeflow Pipeline Metrics artifacts

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#2,019 13 comments 3 reactions 0 assignees View on GitHub
kind/feature lifecycle/frozen
Dominant language
Python
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Description

/kind feature

**Describe the solution you'd like**
Currently a aim is to do parameter tuning over pipelines in katib (#1914, #1993).

Kubeflow pipelines allow for dedicated metrics artifacts:
https://kubeflow-pipelines.readthedocs.io/en/master/source/dsl.html?h=metrics#kfp.dsl.Metrics
https://www.kubeflow.org/docs/components/pipelines/v1/sdk/pipelines-metrics/

Having a dedicated[ Katib sidecar metrics collector](https://www.kubeflow.org/docs/components/katib/experiment/#metrics-collector) that collects the metrics from this artifacts, would make pipelines and katib work together quite nicely.

The current workaround is to use the stdout collector, but this causes issues with the complex commands in pipeline components (#1914, will add dedicated issue soon).

**Anything else you would like to add:**
-

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Contributor guide

Open the contributing guide

Research direction

Read the linked Kubeflow Pipelines Metrics and Katib metrics collector documentation first, then locate the existing Katib sidecar collector entry point. Determine how the collector should consume pipeline Metrics artifacts; done means Katib can use those artifacts for pipeline parameter tuning.

Written by the indexing model from the issue text.

Assessment

Tech stack
kubernetes
Domain
infrastructure, machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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