Add HPA scaling delay docs (#5653)
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@@ -107,6 +107,32 @@ i.e. you cannot bind a Horizontal Pod Autoscaler to a replication controller and
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The reason this doesn't work is that when rolling update creates a new replication controller,
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The reason this doesn't work is that when rolling update creates a new replication controller,
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the Horizontal Pod Autoscaler will not be bound to the new replication controller.
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the Horizontal Pod Autoscaler will not be bound to the new replication controller.
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## Support for cooldown/delay
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When managing the scale of a group of replicas using the Horizontal Pod Autoscaler,
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it is possible that the number of replicas keeps fluctuating frequently due to the
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dynamic nature of the metrics evaluated. This is sometimes referred to as *thrashing*.
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Starting from v1.6, a cluster operator can mitigate this problem by tuning
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the global HPA settings exposed as flags for the `kube-controller-manager` component:
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- `--horizontal-pod-autoscaler-downscale-delay`: The value for this option is a
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duration that specifies how long the autoscaler has to wait before another
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downscale operation can be performed after the current one has completed.
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The default value is 5 minutes (`5m0s`).
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- `--horizontal-pod-autoscaler-upscale-delay`: The value for this option is a
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duration that specifies how long the autoscaler has to wait before another
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upscale operation can be performed after the current one has completed.
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The default value is 3 minutes (`3m0s`).
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**Note**: When tuning these parameter values, a cluster operator should be aware of
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the possible consequences. If the delay (cooldown) value is set too long, there
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could be complaints that the Horizontal Pod Autoscaler is not responsive to workload
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changes. However, if the delay value is set too short, the scale of the replicas set
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may keep thrashing as usual.
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{: .note}
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## Support for multiple metrics
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## Support for multiple metrics
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Kubernetes 1.6 adds support for scaling based on multiple metrics. You can use the `autoscaling/v2beta1` API
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Kubernetes 1.6 adds support for scaling based on multiple metrics. You can use the `autoscaling/v2beta1` API
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