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From "Alex Glikson" <GLIK...@il.ibm.com>
Subject Re: Improving support for UI driven use cases
Date Sun, 02 Jul 2017 05:28:51 GMT
My main point is - interactive Web applications is certainly not the only 
case which is sensitive to latency (or throughput) under variable load. 
Think of an event that a person presses 'emergency' button in an elevator, 
and we need to respond immediately (it might be even more important than 
occasionally getting a timeout on a web page). So, ideally, the solution 
should address *any* (or as many as possible of) such applications.

Regards,
Alex



From:   Tyson Norris <tnorris@adobe.com.INVALID>
To:     "dev@openwhisk.apache.org" <dev@openwhisk.apache.org>
Date:   02/07/2017 01:35 AM
Subject:        Re: Improving support for UI driven use cases




> On Jul 1, 2017, at 2:07 PM, Alex Glikson <GLIKSON@il.ibm.com> wrote:
> 
>> a burst of users will quickly exhaust the system, which is only fine 
for 
> event handling cases, and not fine at all for UI use cases.
> 
> Can you explain why is it fine for event handling cases?
> I would assume that the key criteria would be, for example, around 
> throughput and/or latency (and their tradeoff with capacity), and not 
> necessarily the nature of the application per se.
> 
> Regards,
> Alex

Sure - with event handling, where blocking=false, or where a timeout 
response of 202 (and fetch the response later) is tolerable,  exhausting 
container resources will simply mean that the latency goes up based on the 
number of events generated after the point of saturation.  If you can only 
process 100 events at one time, an arrival of 1000 events at the same time 
means that the second 100 events will only be processed after the first 
100 (twice normal latency), third 100 events after that (3 times normal 
latency), 4th 100 events after that (4 times normal latency) etc. But if 
no user is sitting at a browser waiting for a response, it is unlikely 
they care whether the processing occurs 10ms or 10min after the triggering 
event. (This is exaggerating, but you get the point)

In the case a user is staring at a browser waiting for response, such a 
variance in latency just due to the raw number of users in the system 
directly relating to the raw number of containers in the system, will not 
be usable. Consider concurrency not as a panacea for exhausting container 
pool resources, but rather a way to dampen the graph of user traffic 
increase vs required container pool increase, making it something like 
1000:1 (1000 concurrent users requires 1 container) instead of it being a 
1:1 relationship. 

Thanks
Tyson





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