@@ -11,7 +11,7 @@ weight: 100
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<!-- overview -->
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- Horizontal Pod Autoscaler automatically scales the number of pods
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+ Horizontal Pod Autoscaler automatically scales the number of Pods
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in a replication controller, deployment, replica set or stateful set based on observed CPU utilization
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(or, with beta support, on some other, application-provided metrics).
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@@ -244,8 +244,8 @@ There are two other types of metrics, both of which are considered *custom metri
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object metrics. These metrics may have names which are cluster specific, and require a more
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advanced cluster monitoring setup.
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- The first of these alternative metric types is *pod metrics*. These metrics describe pods , and
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- are averaged together across pods and compared with a target value to determine the replica count.
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+ The first of these alternative metric types is *pod metrics*. These metrics describe Pods , and
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+ are averaged together across Pods and compared with a target value to determine the replica count.
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They work much like resource metrics, except that they *only* support a `target` type of `AverageValue`.
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Pod metrics are specified using a metric block like this :
@@ -261,11 +261,11 @@ pods:
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` ` `
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The second alternative metric type is *object metrics*. These metrics describe a different
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- object in the same namespace, instead of describing pods . The metrics are not necessarily
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+ object in the same namespace, instead of describing Pods . The metrics are not necessarily
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fetched from the object; they only describe it. Object metrics support `target` types of
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both `Value` and `AverageValue`. With `Value`, the target is compared directly to the returned
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metric from the API. With `AverageValue`, the value returned from the custom metrics API is divided
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- by the number of pods before being compared to the target. The following example is the YAML
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+ by the number of Pods before being compared to the target. The following example is the YAML
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representation of the `requests-per-second` metric.
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` ` ` yaml
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