Release component image version d3c4add0a95e930c70a330466d0923827784eb9a #655
Conversation
|
/assign @gaoning777 @qimingj @Ark-kun |
|
/approve |
|
Were there any notable changes? |
|
/lgtm |
|
Note that we do not have tests covering the components, yet since the current sample tests test old component images. |
|
the sample tests are green. https://gubernator.k8s.io/pr/kubeflow/pipelines/655 |
|
/approve |
|
[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: IronPan 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 |
1 similar comment
|
[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: IronPan 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 |
…low#655) * We want to auto-deploy the GCP blueprint (GoogleCloudPlatform/kubeflow-distribution#5) * We need to add logic and K8s resources to cleanup the blueprints so we don't run out of GCP quota. * Create cleanup_blueprints.py to cleanup auto_deployed blueprints. * Don't put this code in cleanup_ci.py because we want to be able to use fire and possibly python3 (not sure code in cleanup_ci is python3 compatible) * Create a CLI create_context.py to create K8s config contexts. This will be used to get credentials to talk to the cleanup cluster when running on K8s. * Create a Tekton task to run the cleanup script. This is intended as a replacement for our existing K8s job (kubeflow#654). There's a couple reasons to start using Tekton i) We are already using Tekton as part of AutoDeploy infrastructure. ii) We can leverage Tekton to handle git checkouts. iii) Tekton makes it easy to additional steps to do things like create the context. * This is a partial solution. This PR contains a Tekton pipeline that is only running cleanup for the blueprints. * To do all cleanup using Tekton we just need to a step or Task to run the existing cleanup-ci script. The only issue I forsee is that the Tekton pipeline runs in the kf-ci-v1 cluster and will need to be granted access to the kubeflow-testing cluster so we can cleanup Argo workflows in that cluster. * To run the Tekton pipeline regulary we create a cronjob that runs kubectl apply. * cnrm_clients.py is a quick hack to create a wrapper to make it easier to work with CNRM custom resources.
This change is