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From Ajinkya Dhamnaskar <adham...@umail.iu.edu>
Subject Re: [#Spring17-Airavata-Courses] : Distributed Workload Management for Airavata
Date Thu, 02 Feb 2017 07:22:51 GMT
Hello all,

Just a heads up. Here the name Distributed workload management does not
necessarily mean having different instances of a microservice and then
distributing work among these instances.

Apparently, the problem is how to make each microservice work independently
with concrete distributed communication infrastructure. So, think of it as
a workflow where each microservice does its part of work and communicates
(how? yet to be decided) output. The next underlying microservice
identifies and picks up that output and takes it further towards the final
outcome, having said that, the crux here is, none of the miscoservices need
to worry about other miscoservices in a pipeline.

Vidya Sagar,
I completely second your opinion of having stateless miscoservices, in fact
that is the key. With stateless miscroservices it is difficult to guarantee
consistency in a system but it solves the availability problem to some
extent. I would be interested to understand what do you mean by "an
intelligent job scheduling algorithm, which receives real-time updates from
the microservices with their current state information".

On Wed, Feb 1, 2017 at 11:48 PM, Vidya Sagar Kalvakunta <
vkalvaku@umail.iu.edu> wrote:

>
> On Wed, Feb 1, 2017 at 2:37 PM, Amila Jayasekara <thejaka.amila@gmail.com>
> wrote:
>
>> Hi Gourav,
>>
>> Sorry, I did not understand your question. Specifically I am having
>> trouble relating "work load management" to options you suggest (RPC,
>> message based etc.).
>> So what exactly you mean by "workload management" ?
>> What is work in this context ?
>>
>> Also, I did not understand what you meant by "the most efficient way".
>> Efficient interms of what ? Are you looking at speed ?
>>
>> As per your suggestions, it seems you are trying to find a way to
>> communicate between micro services. RPC might be troublesome if you need to
>> communicate with processes separated from a firewall.
>>
>> Thanks
>> -Thejaka
>>
>>
>> On Wed, Feb 1, 2017 at 12:52 PM, Shenoy, Gourav Ganesh <
>> goshenoy@indiana.edu> wrote:
>>
>>> Hello dev, arch,
>>>
>>>
>>>
>>> As part of this Spring’17 Advanced Science Gateway Architecture course,
>>> we are working on trying to debate and find possible solutions to the issue
>>> of managing distributed workloads in Apache Airavata. This leads to the
>>> discussion of finding the most efficient way that different Airavata
>>> micro-services should communicate and distribute work, in such a way that:
>>>
>>> 1.       We maintain the ability to scale these micro-services whenever
>>> needed (autoscale perhaps?).
>>>
>>> 2.       Achieve fault tolerance.
>>>
>>> 3.       We can deploy these micro-services independently, or better in
>>> a containerized manner – keeping in mind the ability to use devops for
>>> deployment.
>>>
>>>
>>>
>>> As of now the options we are exploring are:
>>>
>>> 1.       RPC based communication
>>>
>>> 2.       Message based – either master-worker, or work-queue, etc
>>>
>>> 3.       A combination of both these approaches
>>>
>>>
>>>
>>> I am more inclined towards exploring the message based approach, but
>>> again there arises the possibility of handling limitations/corner cases of
>>> message broker such as downtimes (may be more). In my opinion, having
>>> asynchronous communication will help us achieve most of the above-mentioned
>>> points. Another debatable issue is making the micro-services implementation
>>> stateless, such that we do not have to pass the state information between
>>> micro-services.
>>>
>>>
>>>
>>> I would love to hear any thoughts/suggestions/comments on this topic and
>>> open up a discussion via this mail thread. If there is anything that I have
>>> missed which is relevant to this issue, please let me know.
>>>
>>>
>>>
>>> Thanks and Regards,
>>>
>>> Gourav Shenoy
>>>
>>
>>
> Hi Gourav,
>
> Correct me if I'm wrong, but I think this is a case of the job shop
> scheduling problem, as we may have 'n' jobs of varying processing times
> and memory requirements, and we have 'm' microservices with possibly
> different computing and memory capacities, and we are trying to minimize
> the makespan <https://en.wikipedia.org/wiki/Makespan>.
>
> For this use-case, I'm in favor a highly available and consistent message
> broker with an intelligent job scheduling algorithm, which receives
> real-time updates from the microservices with their current state
> information.
>
> As for the state vs stateless implementation, I think that question
> depends on the functionality of a particular microservice. In a broad
> sense, the stateless implementation should be preferred as it will scale
> better horizontally.
>
>
> Regards,
> Vidya Sagar
>
>
> --
> Vidya Sagar Kalvakunta | Graduate MS CS Student | IU School of
> Informatics and Computing | Indiana University Bloomington | (812)
> 691-5002 <8126915002> | vkalvaku@iu.edu
>



-- 
Thanks and regards,

Ajinkya Dhamnaskar
Student ID : 0003469679
Masters (CS)
+1 (812) 369- 5416

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