Tweak Horizontal Pod Autoscaler documentation (#10596)
* Use consistent terms * Fix typo
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@@ -141,7 +141,7 @@ the magnitude of any potential scale.
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Furthermore, if any not-yet-ready pods were present, and we would have
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Furthermore, if any not-yet-ready pods were present, and we would have
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scaled up without factoring in missing metrics or not-yet-ready pods, we
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scaled up without factoring in missing metrics or not-yet-ready pods, we
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conservatively assume the non-yet-ready pods are consuming 0% of the
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conservatively assume the not-yet-ready pods are consuming 0% of the
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desired metric, further dampening the magnitude of a scale up.
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desired metric, further dampening the magnitude of a scale up.
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After factoring in the not-yet-ready pods and missing metrics, we
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After factoring in the not-yet-ready pods and missing metrics, we
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@@ -163,7 +163,7 @@ from the metrics APIs), scaling is skipped.
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Finally, just before HPA scales the target, the scale reccomendation is recorded. The
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Finally, just before HPA scales the target, the scale reccomendation is recorded. The
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controller considers all recommendations within a configurable window choosing the
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controller considers all recommendations within a configurable window choosing the
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highest recommendation from within that window. This value can be configured using the `--horizontal-pod-autoscaler-downscale-stabilization-window` flag, which defaults to 5 minutes.
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highest recommendation from within that window. This value can be configured using the `--horizontal-pod-autoscaler-downscale-stabilization-window` flag, which defaults to 5 minutes.
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This means that scaledowns will occur gradually, smothing out the impact of rapidly
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This means that scaledowns will occur gradually, smoothing out the impact of rapidly
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fluctuating metric values.
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fluctuating metric values.
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## API Object
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## API Object
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