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Update HPA Algorithm Docs for v1.15 (#14728)

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Also changes a link to algorithm details from initial design proposal in Github.
This commit is contained in:
Guy Templeton
2019-06-11 03:04:17 +01:00
committed by Kubernetes Prow Robot
parent 2a0f39fb41
commit d9b19701c3
2 changed files with 6 additions and 3 deletions
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content/en/docs/tasks/run-application/horizontal-pod-autoscale.md
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@@ -155,9 +155,12 @@ used.
If multiple metrics are specified in a HorizontalPodAutoscaler, this
calculation is done for each metric, and then the largest of the desired
replica counts is chosen. If any of those metrics cannot be converted
replica counts is chosen. If any of these metrics cannot be converted
into a desired replica count (e.g. due to an error fetching the metrics
from the metrics APIs), scaling is skipped.
from the metrics APIs) and a scale down is suggested by the metrics which
can be fetched, scaling is skipped. This means that the HPA is still capable
of scaling up if one or more metrics give a `desiredReplicas` greater than
the current value.
Finally, just before HPA scales the target, the scale recommendation is recorded. The
controller considers all recommendations within a configurable window choosing the