Implementing new cloud provider method for node deletion detection #1
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
…cting whether nodes are fully deleted or are not-autoscaled. Updated cloud providers to provide initial implementation of new method that will return an ErrNotImplemented to maintain existing taint-based deletion clusterstate calculation.
fookenc
pushed a commit
that referenced
this pull request
Jun 26, 2024
Update CA_with_AWS_IAM_OIDC.md
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Outdated suggestions cannot be applied.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.
Supports the autoscaler to determine the difference between nodes that have been terminated in the cloud provider, instead of those nodes that are not-autoscaled. Stub implementations for each cloud provider have been provided, which will return an ErrNotImplemented error until it is fully supported. In those cases, the cluster state readiness calculation logic will fall back to taint-based node deletion detection.