Hi Imesh,

Interesting stuff. Maybe we can compare this with the autoscaling
functionality of Stratos. We need to decide on the approach we recommend to
users with Kubernetes + Stratos.

Thanks.

On Sun, Sep 13, 2015 at 12:51 PM, Imesh Gunaratne <im...@apache.org> wrote:

> Hi Devs,
>
> Kubernetes community is now working on implementing $subject. According to
> [1] scaling can be done based on Traffic, Predictive Analysis and Arbitrary
> Data.
>
> Autoscaling policies can be defined to configure min/max values. Compared
> to the Autoscaling policy we have in Stratos this has been designed in a
> generic way to be able to use with different scaling factors [2].
>
> Autoscaling algorithm is as follows:
>
>
> *The autoscaler will be implemented as a control loop. It will
> periodically (e.g.: every 1 minute) query pods described by
> Status.PodSelector of Scale subresource, and check their average CPU or
> memory usage from the last 1 minute (there will be API on master for this
> purpose, see #11951. Then, it will compare the current CPU or memory
> consumption with the Target, and adjust the count of the Scale if needed to
> match the target (preserving condition: MinCount <= Count <= MaxCount).*
>
> *The target number of pods will be calculated from the following formula:*
> *TargetNumOfPods =ceil(sum(CurrentPodsConsumption) / Target)*
>
>
> Read following links for more information:
>
> [1]
> https://github.com/kubernetes/kubernetes/blob/master/docs/proposals/autoscaling.md
> [2]
> https://github.com/kubernetes/kubernetes/blob/master/docs/proposals/horizontal-pod-autoscaler.md
>
> Thanks
>
> --
> Imesh Gunaratne
>
> Senior Technical Lead, WSO2
> Committer & PMC Member, Apache Stratos
>



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Lahiru Sandaruwan
Committer and PMC member, Apache Stratos,
Senior Software Engineer,
WSO2 Inc., http://wso2.com
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