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SDK/Components - Renamed DockerContainer spec to to Container #323

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Ark-kun
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@Ark-kun Ark-kun commented Nov 20, 2018

No need for the longer name.


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@Ark-kun Ark-kun requested a review from qimingj November 20, 2018 01:36
@Ark-kun Ark-kun requested review from gaoning777 and removed request for gaoning777 November 20, 2018 01:36
@Ark-kun Ark-kun force-pushed the avolkov/SDK/Components---Renamed-DockerContainer-spec-to-to-Container branch from 0233065 to 486af9a Compare November 20, 2018 01:37
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qimingj commented Nov 20, 2018

/lgtm

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Ark-kun commented Nov 20, 2018

/approve

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[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: Ark-kun

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[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: Ark-kun

The full list of commands accepted by this bot can be found here.

The pull request process is described here

Needs approval from an approver in each of these files:

Approvers can indicate their approval by writing /approve in a comment
Approvers can cancel approval by writing /approve cancel in a comment

@k8s-ci-robot k8s-ci-robot merged commit dd0bd45 into master Nov 20, 2018
@Ark-kun Ark-kun deleted the avolkov/SDK/Components---Renamed-DockerContainer-spec-to-to-Container branch November 28, 2018 17:36
Linchin pushed a commit to Linchin/pipelines that referenced this pull request Apr 11, 2023
…beflow#323)

* Improve auto_deploy to support changing zone and testing changes.

* Explicitly delete the storage deployment; the delete script won't delete it
  by design because we don't want to destroy data.

* Instead of depending on a dummy kubeconfig file call generate/apply for
  platform and then for k8s.

* For repos take them in the form ${ORG}/${NAME}@Branch. This matches
  what the other test script does. It also allows us to check out the
  repos from people's forks which makes testing changes easier.

* Move logic in checkout-snapshot.sh into repo_clone_snapshot.py
  This is cleaner then having the python script shell out to a shell script.

* Move the logic in deployment-workflow.sh into create_kf_instance.py

  * Add an option in create_kf_instance.py to read and parse the snapshot.json
    file rather than doing it in bash.

* Change the arg name to be datadir instead of nfs_mount because nfs is
  an assumption of how it is run on K8s.

* Check out the source into NFS to make it easier to debug.

* Add a bash script to set the images using YQ
* Add a wait operation for deletes and use it to wait for deletion of storage.

* Rename init.sh to auto_deploy.sh to make it more descriptive.

* Also modify auto_deploy.sh so we can run it locally.

* Use the existing worker ci image as a base image to deduplicate the
  Dockerfile.

* Attach labels to the deployment not the cluster
  * We want to use deployments not cluster to decide what to recycle
  * Deloyments are global but clusters are zonal and we want to
    be able to move to different zones to deal with issues like stockouts.

* The GCP API does return labels on deployments.

* We can figure out which deployment to recycle just by looking at the
  insertTime; we don't need to depend on deployment labels.

* Add retries to deal with kubeflow/kubeflow#1933

* Fix lint.

* * With K8s 1.11 we need to set volumeName otherwise we get storage class not found.
Related to kubeflow/kubeflow#2475

* Fix lint.

* * Change cron job to run every 12 hours.
  * This should be the current schedule but it looks like it was never checked
    in
  * We want to leave clusters up long enough to facilitate debugging.
HumairAK pushed a commit to red-hat-data-services/data-science-pipelines that referenced this pull request Mar 11, 2024
* add s3 endpoint instructions for admin use case

* Update kfp-admin-guide.md

* Apply suggestions from code review

Co-authored-by: Animesh Singh <singhan@us.ibm.com>

* Align with new suggestions

Co-authored-by: Animesh Singh <singhan@us.ibm.com>
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3 participants