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Merge pull request #47020 from dr0ptp4kt/patch-1 

Update horizontal-pod-autoscale-walkthrough.md
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Kubernetes Prow Robot 2024-06-29 02:54:47 -07:00 committed by GitHub
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@ -263,13 +263,23 @@ status:
Notice that the `targetCPUUtilizationPercentage` field has been replaced with an array called `metrics`. Notice that the `targetCPUUtilizationPercentage` field has been replaced with an array called `metrics`.
The CPU utilization metric is a *resource metric*, since it is represented as a percentage of a resource The CPU utilization metric is a *resource metric*, since it is represented as a percentage of a resource
specified on pod containers. Notice that you can specify other resource metrics besides CPU. By default, specified on pod containers. Notice that you can specify other resource metrics besides CPU. By default,
the only other supported resource metric is memory. These resources do not change names from cluster the only other supported resource metric is `memory`. These resources do not change names from cluster
to cluster, and should always be available, as long as the `metrics.k8s.io` API is available. to cluster, and should always be available, as long as the `metrics.k8s.io` API is available.
You can also specify resource metrics in terms of direct values, instead of as percentages of the You can also specify resource metrics in terms of direct values, instead of as percentages of the
requested value, by using a `target.type` of `AverageValue` instead of `Utilization`, and requested value, by using a `target.type` of `AverageValue` instead of `Utilization`, and
setting the corresponding `target.averageValue` field instead of the `target.averageUtilization`. setting the corresponding `target.averageValue` field instead of the `target.averageUtilization`.
```
metrics:
- type: Resource
resource:
name: memory
target:
type: AverageValue
averageValue: 500Mi
```
There are two other types of metrics, both of which are considered *custom metrics*: pod metrics and There are two other types of metrics, both of which are considered *custom metrics*: pod metrics and
object metrics. These metrics may have names which are cluster specific, and require a more object metrics. These metrics may have names which are cluster specific, and require a more
advanced cluster monitoring setup. advanced cluster monitoring setup.