That’s a good plan,

My work number is +442088242650

I’m around now, but will break for a while for lunch in an hour or so.

Cheers

From: Lakmal Warusawithana <[email protected]<mailto:[email protected]>>
Date: Friday, 13 February 2015 11:24
To: "[email protected]<mailto:[email protected]>" 
<[email protected]<mailto:[email protected]>>, Imesh Gunaratne 
<[email protected]<mailto:[email protected]>>, Michael Hall 
<[email protected]<mailto:[email protected]>>
Subject: Re: autoscale architecture

Shall we go for a call, it will be more productive.

On Fri, Feb 13, 2015 at 4:45 PM, Lakmal Warusawithana 
<[email protected]<mailto:[email protected]>> wrote:
Hi Michael

On Fri, Feb 13, 2015 at 4:14 PM, Michael Hall (michaha2) 
<[email protected]<mailto:[email protected]>> wrote:
Hi Imesh,

So ‘transistion compensated’ refers to cartridges, which are ’transistioning’ 
between SPAWNED-ACTIVE, and TERMINATING-TERMINATED.

What it really means, is that if the 'aggregated average’ (Referred to this as 
<metric>PredictedValue in scaling.drl) is compensated:

  1.  As if the ‘spawning’ cartridges are providing resouce (although they 
aren’t yet)
  2.  As if the ‘terminating’ cartridges have removed resource (although they 
haven't yet)

Such that the ‘transition compensated aggregated average', will be 
approximately what the actually aggregated average would be if those cartridges 
had become fully ‘active’ or ‘terminated’. This means the ‘transition 
compensated aggregated average’ is always in a sensible state to make a scaling 
decision.

This then allows us to make a scaling decision as often as we’d like (much 
smaller than 90 seconds, could even be every 1 second), because if you take the 
example the we’ve scaled up, the 'transition compensated aggregated average’ 
will instantly adjust to N/N+1 of it’s raw value (copied formula from previous 
email for reference below), so another scaling decision will only occur, if the 
underlying load (aggregated average) increases even further.

transistion-compensated-agg-ave = agg-ave * ( cluster-size / cluster-size +  
cluster-spawned-size - cluster–terminating-size )


 I think this is good proposal, definitely it will help to calculate more 
accurate agg-ave values. Since CEP has the topology information we can easily 
calculate this.

AFAIK, auto scaler take care of cartridge states when calculating required 
instances count for a predicted load.


I’d be more than happy to setup a webex meeting to try and explain this better? 
Or another avenue of communication at your preference?

Kind regards,

Mike

From: Imesh Gunaratne <[email protected]<mailto:[email protected]>>
Reply-To: "[email protected]<mailto:[email protected]>" 
<[email protected]<mailto:[email protected]>>
Date: Friday, 13 February 2015 01:09

To: dev <[email protected]<mailto:[email protected]>>
Subject: Re: autoscale architecture

Hi Mike,

Thanks for the detailed explanation of your question. Currently we do not have 
the capability to do this in runtime for a specific cartridge. However we could 
reduce the global scaling decision interval. This needs to be configured at 
three locations:

1. Cartridge agent statistics publishing interval (default: 15 seconds)
2. CEP execution plan/faulty member detection interval (default: 1 min)
3. Autoscaler cluster monitor interval (default: 90 seconds)

I did not clearly get what you mean by 'transition compensated'. Is there a way 
to explain it further?

Thanks


On Fri, Feb 13, 2015 at 12:26 AM, Michael Hall (michaha2) 
<[email protected]<mailto:[email protected]>> wrote:
Hi Dev,

Thanks for your response Imesh, if its ok, I’d like to skip straight to my 
(rather lengthy) question:

Does the autoscaler have, currently or plans to introduce, a means to receive 
an asynchronous event, signalling that a cartridge has gone from ‘SPAWNED’ to 
‘ACTIVE’, after it is launched from a 'scale-up’ decision, so that, scaling 
decision interval can decrease to approximately the metric update interval, and 
multiple cartridges are not spawned when only one is needed?

In more depth:

The reasons for my question being that by knowing a cartridge is in the 
‘SPAWNED’ or ’TERMINATING’ state, the aggregated metric averages can be 
’transition compensated’ I.e…
transistion-compensated-agg-ave = agg-ave * ( cluster-size / cluster-size +  
cluster-spawned-size - cluster–terminating-size )
To allow the scaling decisions to occur on a continuous (only throttled by the 
metric update frequency) basis.

It appears that currently scaling decision occurs ~minutes. If this becomes 
~seconds, it would vastly improving the maximum rate of ascent a cluster can 
scale against sudden increase in load.

It appears that there is no spawning state awareness, which also means several 
‘redundant’ instances get spawned, when instance startup time is greater than 
the scale decision interval.

Finally:

Are there difficulties in tracking ‘SPAWNED’ to ‘ACTIVE’ state on a per 
cartridge basis, how does this align (if its a valid enhancement) with other 
potential improvements that could be made to the autoscaler?

Regards,

Mike

From: Imesh Gunaratne <[email protected]<mailto:[email protected]>>
Reply-To: "[email protected]<mailto:[email protected]>" 
<[email protected]<mailto:[email protected]>>
Date: Thursday, 12 February 2015 18:16
To: dev <[email protected]<mailto:[email protected]>>
Subject: Re: autoscale architecture

Hi Michael,

Yes you can ask any questions you have on Autoscaling here.

I don't think we have documented Autoscaling feature in 4.1.0 at the moment. 
However you could find some information here [1]. Autoscaling has slightly 
changed with Composite Application Model.

[1] https://cwiki.apache.org/confluence/display/STRATOS/4.1.0+Autoscaler

Thanks

On Thu, Feb 12, 2015 at 9:33 PM, Michael Hall (michaha2) 
<[email protected]<mailto:[email protected]>> wrote:
Hi Devs,

Is there a resource or contact that can help me understand the current, and 
planned architecture of the autoscaling feature within Stratos.

Best Regards,

Mike



--
Imesh Gunaratne

Technical Lead, WSO2
Committer & PMC Member, Apache Stratos



--
Imesh Gunaratne

Technical Lead, WSO2
Committer & PMC Member, Apache Stratos



--
Lakmal Warusawithana
Vice President, Apache Stratos
Director - Cloud Architecture; WSO2 Inc.
Mobile : +94714289692<tel:%2B94714289692>
Blog : http://lakmalsview.blogspot.com/




--
Lakmal Warusawithana
Vice President, Apache Stratos
Director - Cloud Architecture; WSO2 Inc.
Mobile : +94714289692
Blog : http://lakmalsview.blogspot.com/

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