[ML] Use correct writable name for model assignment metadata in mixed cluster #100886
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
|
Pinging @elastic/ml-core (Team:ML) |
|
Hi @davidkyle, I've created a changelog YAML for you. |
davidkyle
changed the title
davidkyle
commented
Oct 16, 2023
davidkyle
commented
Oct 16, 2023
💚 Backport successful
|
davidkyle
added a commit
to davidkyle/elasticsearch
that referenced
this pull request
Oct 16, 2023
… cluster (elastic#100886) Older nodes will fail if they do not recognise the named writable
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Outdated suggestions cannot be applied.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.
TrainedModelAssignmentMetadatawas introduced in version 8.3, in a mixed cluster there are many checks to ensure that the new named writable is not used before the cluster is fully upgraded. However, there is one case where the detail about whether to use the old or new named writable is forgotten and the new one used by default. As older nodes cannot read the new writable this can cause a node failure during a rolling upgrade with the errorFor #100371