mirror of
https://github.com/BerriAI/litellm.git
synced 2026-09-05 08:07:05 +00:00
fix(helm): scale the classic chart's HPA out at the documented 60 percent CPU (#35975)
* fix(helm): scale the classic chart's HPA out at the documented 60 percent CPU The litellm-helm chart shipped targetCPUUtilizationPercentage: 80, which is unexamined helm create scaffold rather than a chosen number. It arrived packaged with the stock minReplicas: 1, maxReplicas: 100, a commented-out targetMemoryUtilizationPercentage: 80, and the boilerplate "such as Minikube" comment, the same provenance as the 128Mi resource example this file just corrected. 60 is the documented recommendation. The mechanism behind it is scale-up lag: the chart's own startupProbe is failureThreshold: 30 times periodSeconds: 10, so a replica can take up to 300 seconds to become ready, and a pod added at 80 percent utilization arrives minutes after saturation. The memory target stays commented out on purpose. The prisma query engine's resident memory is a high-water mark that ratchets to the pod's worst-ever write and is never returned, so a memory-target HPA reads the largest write a pod ever did rather than what it is doing now, and replicas ratchet up without scaling back in. hpa_tests.yaml carried its second suite after a YAML document separator, and helm-unittest loads only the first document per file, so that suite never ran; an assertion planted in it still passed. Fold it into the one live suite and add coverage pinning the rendered CPU target, the absence of a memory metric by default, and that overrides still take effect. Bump the chart to 1.1.2, since rendered output changes for anyone running with autoscaling enabled. * fix(helm): bump litellm-helm to 1.1.3 after rebase onto 1.1.2 Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
This commit is contained in:
parent
6ed2cdd428
commit
de80e3afe4
3 changed files with 47 additions and 8 deletions
|
|
@ -18,7 +18,7 @@ type: application
|
|||
# This is the chart version. This version number should be incremented each time you make changes
|
||||
# to the chart and its templates, including the app version.
|
||||
# Versions are expected to follow Semantic Versioning (https://semver.org/)
|
||||
version: 1.1.2
|
||||
version: 1.1.3
|
||||
|
||||
# This is the version number of the application being deployed. This version number should be
|
||||
# incremented each time you make changes to the application. Versions are not expected to
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
suite: "hpa with behavior"
|
||||
suite: "hpa"
|
||||
templates:
|
||||
- hpa.yaml
|
||||
tests:
|
||||
|
|
@ -23,14 +23,44 @@ tests:
|
|||
- equal: { path: spec.behavior.scaleUp.stabilizationWindowSeconds, value: 60 }
|
||||
- equal: { path: spec.behavior.scaleDown.stabilizationWindowSeconds, value: 90 }
|
||||
|
||||
---
|
||||
suite: "hpa without behavior"
|
||||
templates:
|
||||
- hpa.yaml
|
||||
tests:
|
||||
- it: "does not render behavior when not set"
|
||||
set:
|
||||
autoscaling.enabled: true
|
||||
asserts:
|
||||
- isKind: { of: HorizontalPodAutoscaler }
|
||||
- isNull: { path: spec.behavior }
|
||||
|
||||
- it: "scales on cpu at the documented 60 percent by default"
|
||||
set:
|
||||
autoscaling.enabled: true
|
||||
asserts:
|
||||
- isKind: { of: HorizontalPodAutoscaler }
|
||||
- equal: { path: "spec.metrics[0].resource.name", value: cpu }
|
||||
- equal: { path: "spec.metrics[0].resource.target.type", value: Utilization }
|
||||
- equal: { path: "spec.metrics[0].resource.target.averageUtilization", value: 60 }
|
||||
|
||||
- it: "does not scale on memory by default"
|
||||
set:
|
||||
autoscaling.enabled: true
|
||||
asserts:
|
||||
- lengthEqual: { path: spec.metrics, count: 1 }
|
||||
|
||||
- it: "honours an explicit cpu target override"
|
||||
set:
|
||||
autoscaling.enabled: true
|
||||
autoscaling.targetCPUUtilizationPercentage: 75
|
||||
asserts:
|
||||
- equal: { path: "spec.metrics[0].resource.target.averageUtilization", value: 75 }
|
||||
|
||||
- it: "renders a memory metric only when a memory target is set"
|
||||
set:
|
||||
autoscaling.enabled: true
|
||||
autoscaling.targetMemoryUtilizationPercentage: 80
|
||||
asserts:
|
||||
- lengthEqual: { path: spec.metrics, count: 2 }
|
||||
- equal: { path: "spec.metrics[1].resource.name", value: memory }
|
||||
- equal: { path: "spec.metrics[1].resource.target.averageUtilization", value: 80 }
|
||||
|
||||
- it: "renders no hpa when autoscaling is disabled"
|
||||
asserts:
|
||||
- hasDocuments: { count: 0 }
|
||||
|
|
|
|||
|
|
@ -200,7 +200,16 @@ autoscaling:
|
|||
enabled: false
|
||||
minReplicas: 1
|
||||
maxReplicas: 100
|
||||
targetCPUUtilizationPercentage: 80
|
||||
# 60 is the documented recommendation. See "Recommended Machine Specifications"
|
||||
# in https://docs.litellm.ai/docs/proxy/prod. A new replica clears the startupProbe
|
||||
# above only after up to failureThreshold x periodSeconds = 300 seconds, so a target
|
||||
# high enough to trip near saturation adds capacity minutes after it was needed.
|
||||
targetCPUUtilizationPercentage: 60
|
||||
# Deliberately left unset rather than given a value. The prisma query engine's
|
||||
# resident memory is a high-water mark that ratchets to the pod's worst-ever write
|
||||
# and is never returned, so a memory target reads the largest write a pod ever did
|
||||
# rather than what it is doing now, and replicas ratchet up without scaling back in.
|
||||
# Memory is a floor to provision under 'resources', not a signal to scale on.
|
||||
# targetMemoryUtilizationPercentage: 80
|
||||
# behavior: {}
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue