Correctly ignore src/apis when building frontend #654
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
/lgtm |
|
[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: rileyjbauer 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: rileyjbauer 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 |
Linchin
pushed a commit
to Linchin/pipelines
that referenced
this pull request
Apr 11, 2023
…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.
HumairAK
pushed a commit
to red-hat-data-services/data-science-pipelines
that referenced
this pull request
Mar 11, 2024
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Right now, the build fails if the generated Typescript definitions don't build according to our tsconfig file.
/area front-end
/assign @rileyjbauer
This change is