Spread singleton workloads across Kubernetes nodes - #188
Open
import-pandas-as-numpy wants to merge 1 commit into
Open
Spread singleton workloads across Kubernetes nodes#188import-pandas-as-numpy wants to merge 1 commit into
import-pandas-as-numpy wants to merge 1 commit into
Conversation
This file contains hidden or 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
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
Summary
Background
The staging cluster placed Discord and Mainframe on the same 2 GiB node. They
currently consume about 293 MiB and 277 MiB respectively, contributing to node
usage above Kubernetes allocatable memory while the second node remains less
loaded.
Kubernetes does not continuously rebalance running pods, and neither deployment
currently expresses a placement preference. These pod-template changes cause a
rolling replacement when applied and make each workload prefer a hostname that
does not contain the other workload.
Scope
These are shared application manifests, so the preference applies wherever the
manifests are subsequently deployed, including staging and production. This PR
does not deploy or modify either cluster.
Resource requests and limits are intentionally excluded. Choosing accurate
values requires additional measurement, and the current system-pod reservations
on the 2 GiB nodes make that a separate capacity-planning change.
Validation
kubectl apply --dry-run=client --validate=strictfor both deployments/home/rem/github/vipyrsec/.tools/bin/prek-workspace run --all-filesgit diff --cached --check