Merge pull request #1139 from hyunchel/update-hpa-docs

Add missing commas, fix typos
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devin-donnelly 2016-09-09 15:17:57 -07:00 committed by GitHub
commit 0c97a1d75e
1 changed files with 7 additions and 6 deletions

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@ -120,13 +120,14 @@ all running pods. Example:
alpha/target.custom-metrics.podautoscaler.kubernetes.io: '{"items":[{"name":"qps", "value": "10"}]}'
```
In this case if there are 4 pods running and each of them reports qps metric to be equal to 15 HPA will start 2 additional pods so there will be 6 pods in total. If there are multiple metrics passed in the annotation or CPU is configured as well then HPA will use the biggest
number of replicas that comes from the calculations.
In this case, if there are four pods running and each pod reports a QPS metric of 15 or higher, horizontal pod autoscaling will start two additional pods (for a total of six pods running).
If you specify multiple metrics in your annotation or if you set a target CPU utilization, horizontal pod autoscaling will scale to according to the metric that requires the highest number of replicas.
If you do not specify a target for CPU utilization, Kubernetes defaults to an 80% utilization threshold for horizontal pod autoscaling.
If you want to ensure that horizontal pod autoscaling calculates the number of required replicas based only on custom metrics, you should set the CPU utilization target to a very large value (such as 100000%). As this level of CPU utilization isn't possible, horizontal pod autoscaling will calculate based only on the custom metrics (and min/max limits).
At this moment even if target CPU utilization is not specified a default of 80% will be used.
To calculate number of desired replicas based only on custom metrics CPU utilization
target should be set to a very large value (e.g. 100000%). Then CPU-related logic
will want only 1 replica, leaving the decision about higher replica count to cusom metrics (and min/max limits).
## Further reading