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Kfp diagnose_me pipeline #2843

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merged 13 commits into from
Jan 22, 2020

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SinaChavoshi
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@SinaChavoshi SinaChavoshi commented Jan 15, 2020

Adding a pipeline based on diagnose_me code to that helps verify credentials, enabled APIs, and cloud scope.
The pipeline runs diangose_me as a first step to make it easy for users to capture their environment configuration and share the results with support teams.


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@numerology
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/assign @numerology

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Please see the comments via ReviewNB. Its visualization compatibility with Github is not great.

@numerology
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LGTM modulo one nit issue :)
Thanks @SinaChavoshi !

@numerology
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/lgtm
/approve

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[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: numerology

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@k8s-ci-robot k8s-ci-robot merged commit b983399 into kubeflow:master Jan 22, 2020
@SinaChavoshi SinaChavoshi deleted the kfp_diagnose_me_pipeline branch January 29, 2020 19:00
Jeffwan pushed a commit to Jeffwan/pipelines that referenced this pull request Dec 9, 2020
* Making json output format easier to read

* Update sdk/python/kfp/cli/diagnose_me_cli.py

good catch  :)

Co-Authored-By: Jiaxiao Zheng <jxzheng@google.com>

* update based on feedback

* Sample env validation pipeline with diagnose_me

* removing files that I accidentally added

* update based on review feedback

* diagnose_me based validation pipeline

* updating sample based on review feedback

* updating project_id comment

* removed sequential execution

* changing comment on base image

Co-authored-by: Jiaxiao Zheng <jxzheng@google.com>
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5 participants