Return-Path: X-Original-To: archive-asf-public-internal@cust-asf2.ponee.io Delivered-To: archive-asf-public-internal@cust-asf2.ponee.io Received: from cust-asf.ponee.io (cust-asf.ponee.io [163.172.22.183]) by cust-asf2.ponee.io (Postfix) with ESMTP id E42B6200C13 for ; Mon, 6 Feb 2017 18:15:34 +0100 (CET) Received: by cust-asf.ponee.io (Postfix) id E26FC160B53; Mon, 6 Feb 2017 17:15:34 +0000 (UTC) Delivered-To: archive-asf-public@cust-asf.ponee.io Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by cust-asf.ponee.io (Postfix) with SMTP id DAE24160B56 for ; Mon, 6 Feb 2017 18:15:31 +0100 (CET) Received: (qmail 49110 invoked by uid 500); 6 Feb 2017 17:15:31 -0000 Mailing-List: contact dev-help@airavata.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: dev@airavata.apache.org Delivered-To: mailing list dev@airavata.apache.org Received: (qmail 49098 invoked by uid 99); 6 Feb 2017 17:15:30 -0000 Received: from pnap-us-west-generic-nat.apache.org (HELO spamd1-us-west.apache.org) (209.188.14.142) by apache.org (qpsmtpd/0.29) with ESMTP; Mon, 06 Feb 2017 17:15:30 +0000 Received: from localhost (localhost [127.0.0.1]) by spamd1-us-west.apache.org (ASF Mail Server at spamd1-us-west.apache.org) with ESMTP id 11AA9C02BC for ; Mon, 6 Feb 2017 17:15:30 +0000 (UTC) X-Virus-Scanned: Debian amavisd-new at spamd1-us-west.apache.org X-Spam-Flag: NO X-Spam-Score: 2.38 X-Spam-Level: ** X-Spam-Status: No, score=2.38 tagged_above=-999 required=6.31 tests=[DC_PNG_UNO_LARGO=0.001, DKIM_SIGNED=0.1, DKIM_VALID=-0.1, DKIM_VALID_AU=-0.1, HTML_MESSAGE=2, RCVD_IN_DNSWL_NONE=-0.0001, RCVD_IN_MSPIKE_H3=-0.01, RCVD_IN_MSPIKE_WL=-0.01, RCVD_IN_SORBS_SPAM=0.5, SPF_PASS=-0.001] autolearn=disabled Authentication-Results: spamd1-us-west.apache.org (amavisd-new); dkim=pass (2048-bit key) header.d=gmail.com Received: from mx1-lw-us.apache.org ([10.40.0.8]) by localhost (spamd1-us-west.apache.org [10.40.0.7]) (amavisd-new, port 10024) with ESMTP id YTMAwTU9HHSx for ; Mon, 6 Feb 2017 17:15:26 +0000 (UTC) Received: from mail-wm0-f54.google.com (mail-wm0-f54.google.com [74.125.82.54]) by mx1-lw-us.apache.org (ASF Mail Server at mx1-lw-us.apache.org) with ESMTPS id ED28D5F644 for ; Mon, 6 Feb 2017 17:15:25 +0000 (UTC) Received: by mail-wm0-f54.google.com with SMTP id b65so129601611wmf.0 for ; Mon, 06 Feb 2017 09:15:25 -0800 (PST) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20161025; h=mime-version:in-reply-to:references:from:date:message-id:subject:to; bh=Ccij8XGUq0jlsyRAZ+xY49qjY4tBpBbnBXSW8xbDQZM=; b=k6bGVpnggxzlfigTqfdlmh3Mjn0FoLHj9SCVSIGMHZETAboRgIuM+VMWTS4GQGUQhO rhVhWrKmGX2k1ul2MkE+wk1VOgW0LjPyEgS1qaduPPsKOg8fN7IM6m8SQfjMVVOWA3FH ujIWWonO9zt3ykl1UuCESHyA7G4qaRl8U9Rxr+0b0hiSeTxPNcAu2PlREHs+/FqhnZLi 64x5132s9LR27/mBPVraz4cM+gBmHUUJ6BmjFKVeAw7SMksUCI4+OkSiu053BgX2+J2Y kRAqUkZpJqDxNfF92XmrGJtJwacEEMBjfQFO+LtfDOvphs1JrCfx3Dq6GLyFncUncveB 9UKA== X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1e100.net; s=20161025; h=x-gm-message-state:mime-version:in-reply-to:references:from:date :message-id:subject:to; bh=Ccij8XGUq0jlsyRAZ+xY49qjY4tBpBbnBXSW8xbDQZM=; b=I0Pm22F60gwHjlwX8Seo8KkEujIRA6bcZWku1BR+r3pooYxF29XQQ0QPCTO/mt1oS8 HY5wJTY0cAykYnIo03AVBE5rTURtxalcTzs1fL5uLEbQVx69slcjeJjppuqs8TmqRBF3 YjYiNy68sSbDkoiSsDMMyaPhQaJ1pt7QkIf4/4PdJ8JtBtYFYnumsS2FDmOJk6wBynPJ dizS8mTmiK3fS5QePjhNT3qu/QICKyPt59ydf5WerKqzxH7mLSBQQT8PEk2c10lx6KRN Mjm6x8rH8DZvr48/W9KdMwmxbUm8Izbkq5NbmmziJo6sTneo7PZg5K3mdf5KVEf2kCX0 5fpg== X-Gm-Message-State: AMke39nFzmz72MyWM2aNWUcyY30rTgVX3k83b9CPNSwvh/HsT+eMMOeuDdvnH9KL2ok3xOMDn+1fcpf7WXie3Q== X-Received: by 10.28.170.211 with SMTP id t202mr9977169wme.71.1486401306844; Mon, 06 Feb 2017 09:15:06 -0800 (PST) MIME-Version: 1.0 Received: by 10.28.158.14 with HTTP; Mon, 6 Feb 2017 09:15:05 -0800 (PST) In-Reply-To: <92C823ED-436F-4CAE-B9A3-6AB28E535BE1@indiana.edu> References: <5D649611-861B-46E4-ABAA-678EEE53679F@indiana.edu> <1486103917127.67213@indiana.edu> <8A299CD9-310C-4FBF-9065-04933BBE8CF3@iu.edu> <92C823ED-436F-4CAE-B9A3-6AB28E535BE1@indiana.edu> From: Supun Nakandala Date: Mon, 6 Feb 2017 12:15:05 -0500 Message-ID: Subject: Re: [#Spring17-Airavata-Courses] : Distributed Workload Management for Airavata To: dev Content-Type: multipart/related; boundary=001a114430aee38db80547dfc558 archived-at: Mon, 06 Feb 2017 17:15:35 -0000 --001a114430aee38db80547dfc558 Content-Type: multipart/alternative; boundary=001a114430aee38db40547dfc557 --001a114430aee38db40547dfc557 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Hi Gourav, It is my belief that we don't need a separate microservice to each task. I favor a single micro service which can execute all tasks (or in other words a generic task execution micro service). Of course, we can have many of them when we want to scale. WDYT? On Sun, Feb 5, 2017 at 3:07 PM, Shenoy, Gourav Ganesh wrote: > Hi dev, > > > > We were brainstorming some potential designs that might help us with this > problem. One possible option would be to have a =E2=80=9Cworkflow micro-s= ervice=E2=80=9D > which would basically be the mediator/orchestrator for deciding which > micro-service should be executed next =E2=80=93 based on the type of the = job. The > motive is to make micro-services independent of the workflow; i.e. a > micro-service implementation should be not be aware of which micro-servic= e > will be executed next and we should have a central control of deciding th= is > pattern. > > Eg: For job type X, the pattern could be A -> B -> C -> D. Whereas for jo= b > type Y, the pattern could be A -> C -> D; and so on. > > > > An initial design with this idea looks like follows: > > > > > > We would have a common messaging framework (implementation has not been > decided yet). The database associated with the workflow micro-service cou= ld > be a graph database (maybe?) =E2=80=93 again the implementation/technolog= y has not > been decided yet. > > > > This is just a proposed design, and I would love to hear your thoughts on > this and any suggestions/comments if any. If there is anything that we ar= e > missing or should consider, please do let us know. > > > > Thanks and Regards, > > Gourav Shenoy > > > > *From: *"Christie, Marcus Aaron" > *Reply-To: *"dev@airavata.apache.org" > *Date: *Friday, February 3, 2017 at 9:21 AM > > *To: *"dev@airavata.apache.org" > *Subject: *Re: [#Spring17-Airavata-Courses] : Distributed Workload > Management for Airavata > > > > Vidya, > > > > I=E2=80=99m not sure how relevant it is, but it occurs to me that a micro= service > that executes jobs on a cloud requires very little in terms of resources = to > submit and monitor that job on the cloud. It doesn=E2=80=99t really matte= r if the > job is a =E2=80=9Cbig=E2=80=9D or a =E2=80=9Csmall=E2=80=9D job. So I=E2= =80=99m not sure what heuristic makes > sense regarding distributing work to these job execution microservices. > Maybe a simple round robin approach would be sufficient. > > > > I think a job scheduling algorithm does make sense, however, for a higher > level component, some sort of metascheduler that understands what resourc= es > are available on the cloud resources on which the jobs will be running. > The metascheduler could create work for the job exection microservices to > run on particular cloud resources in a way that optimizes for some metric > (e.g., throughput). > > > > Thanks, > > > > Marcus > > > > On Feb 3, 2017, at 3:19 AM, Vidya Sagar Kalvakunta > wrote: > > > > Ajinkya, > > > > My scenario is for workload distribution among multiple instances of the > same microservice. > > > > If a message broker needs to distribute the available jobs among multiple > workers, the common approach would be to use round robin or a similar > algorithm. This approach works best when all the workers are similar and > the jobs are equal. > > > > So I think that a genetic or heuristic job scheduling algorithm, which is > also aware of each of the worker's current state (CPU, RAM, No of Jobs > processing) can more efficiently distribute the jobs. The workers can > periodically ping the message broker with their current state info. > > > > The other advantage of using a customized algorithm is that it can > be tweaked to use embedded routing, priority or other information in the > job metadata to resolve all of the concerns raised by Amrutha viz message > grouping, ordering, repeated messages, etc. > > > > We can even ensure data privacy, i.e if the workers are spread across > multiple compute clusters say AWS and IU Big Red and we want to restrict > certain sensitive jobs to be run only on Big Red. > > > > Some distributed job scheduling algorithms for cloud computing. > > - http://www.ijimai.org/journal/sites/default/files/files/ > 2013/03/ijimai20132_18_pdf_62825.pdf > > - https://arxiv.org/pdf/1404.5528.pdf > > > > > > Regards > > Vidya Sagar > > > > On Fri, Feb 3, 2017 at 1:38 AM, Kamat, Amruta Ravalnath < > arkamat@indiana.edu> wrote: > > Hello all, > > > > Adding more information to the message based approach. Messaging is a key > strategy employed in many distributed environments. Message queuing is > ideally suited to performing asynchronous operations. A sender can post a > message to a queue, but it does not have to wait while the message is > retrieved and processed. A sender and receiver do not even have to be > running concurrently. > > > > With message queuing there can be 2 possible scenarios: > > 1. =E2=80=8BSending and receiving messages using a * single message qu= eue.* > 2. =E2=80=8B*Sharing a message queue* between many senders and receive= rs > > =E2=80=8BWhen a message is retrieved, it is removed from the queue. A mes= sage > queue may also support message peeking. This mechanism can be useful if > several receivers are retrieving messages from the same queue, but each > receiver only wishes to handle specific messages. The receiver can examin= e > the message it has peeked, and decide whether to retrieve the message > (which removes it from the queue) or leave it on the queue for another > receiver to handle. > > > > A few basic message queuing patterns are: > > 1. *One-way messaging*: The sender simply posts a message to the queue > in the expectation that a receiver will retrieve it and process it at = some > point. > 2. *Request/response messaging*: In this pattern a sender posts a > message to a queue and expects a response from the receiver. The sende= r can > resend if the message is not delivered. This pattern typically require= s > some form of correlation to enable the sender to determine which respo= nse > message corresponds to which request sent to the receiver. > 3. *Broadcast messaging*: In this pattern a sender posts a message to > a queue, and multiple receivers can read a copy of the message. This > pattern depends on the message queue being able to disseminate the sam= e > message to multiple receivers. There is a queue to which the senders c= an > post messages that include metadata in the form of attributes. Each > receiver can create a subscription to the queue, specifying a filter t= hat > examines the values of message attributes. Any messages posted to the > queue with attribute values that match the filter are automatically > forwarded to that subscription. > > A solution based on asynchronous messaging might need to address a number > of concerns: > > > > *Message ordering, Message grouping: *Process messages either in the > order they are posted or in a specific order based on priority. Also, the= re > may be occasions when it is difficult to eliminate dependencies, and it m= ay > be necessary to group messages together so that they are all handled by t= he > same receiver. > *Idempotency: *Ideally the message processing logic in a receiver should > be idempotent so that, if the work performed is repeated, this repetition > does not change the state of the system. > *Repeated messages: *Some message queuing systems implement duplicate > message detection and removal based on message IDs > *Poison messages: *A poison message is a message that cannot be handled, > often because it is malformed or contains unexpected information. > *Message expiration: *A message might have a limited lifetime, and if it > is not processed within this period it might no longer be relevant and > should be discarded. > *Message scheduling: *A message might be temporarily embargoed and should > not be processed until a specific date and time. The message should not b= e > available to a receiver until this time. > > > Thanks > > Amruta Kamat > > > ------------------------------ > > *From:* Shenoy, Gourav Ganesh > *Sent:* Thursday, February 2, 2017 7:57 PM > *To:* dev@airavata.apache.org > > > *Subject:* Re: [#Spring17-Airavata-Courses] : Distributed Workload > Management for Airavata > > > > Hello all, > > > > Amila, Sagar, thank you for the response and raising those concerns; and > apologies because my email resonated the topic of workload management in > terms of how micro-services communicate. As Ajinkya rightly mentioned, > there exists some sort of correlation between micro-services communicatio= n > and it=E2=80=99s impact on how that micro-service performs the work under= those > circumstances. The goal is to make sure we have maximum independence > between micro-services, and investigate the workflow pattern in which the= se > micro-services will operate such that we can find the right balance betwe= en > availability & consistency. Again, from our preliminary analysis we can > assert that these solutions may not be generic and the specific use-case > will have a big decisive role. > > > > For starters, we are focusing on the following example =E2=80=93 and I th= ink this > will clarify the doubts on what we are exactly trying to investigate abou= t. > > > > *Our test example * > > Say we have the following 4 micro-services, which each perform a specific > task as mentioned in the box. > > > > > > > > > > *A state-full pattern to distribute work* > > > > > > Here each communication between micro-services could be via RPC or > Messaging (eg: RabbitMQ). Obvious disadvantage is that if any micro-servi= ce > is down, then the system availability is at stake. In this test example, = we > can see that Microservice-A coordinates the work and maintains the state > information. > > > > *A state-less pattern to distribute work* > > > > > > > > Another purely asynchronous approach would be to associate message-queues > with each micro-service, where each micro-service performs it=E2=80=99s t= ask, > submits a request (message on bus) to the next micro-service, and continu= es > to process more requests. This ensures more availability, and perhaps we > might need to handle corner cases for failures such as message broker dow= n, > or message loss, etc. > > > > As mentioned, these are just a few proposals that we are planning to > investigate via a prototype project. Inject corner cases/failures and try > and find ways to handle these cases. I would love to hear more > thoughts/questions/suggestions. > > > > Thanks and Regards, > > Gourav Shenoy > > > > *From: *Ajinkya Dhamnaskar > *Reply-To: *"dev@airavata.apache.org" > *Date: *Thursday, February 2, 2017 at 2:22 AM > *To: *"dev@airavata.apache.org" > *Subject: *Re: [#Spring17-Airavata-Courses] : Distributed Workload > Management for Airavata > > > > 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 a= nd > 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 th= e > 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 fr= om > 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 > 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=E2=80=9917 Advanced Science Gateway Architecture c= ourse, 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 =E2=80=93 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 =E2=80=93 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 agai= n > 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-mention= ed > points. Another debatable issue is making the micro-services implementati= on > 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 ha= ve > 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 . > > > > 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 Informatic= s > 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 <(812)%20369-5416> > > > > > > -- > > Vidya Sagar Kalvakunta | Graduate MS CS Student | IU School of Informatic= s > and Computing | Indiana University Bloomington | (812) 691-5002 > <8126915002> | vkalvaku@iu.edu > > > --=20 Thank you Supun Nakandala Dept. Computer Science and Engineering University of Moratuwa --001a114430aee38db40547dfc557 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
Hi Gourav,

It is my belief that we don&= #39;t need a separate microservice to each task. I favor a single micro ser= vice which can execute all tasks (or in other words a generic task executio= n micro service). Of course,=C2=A0we can have many of them when we want to = scale. WDYT?

On Sun, Feb 5, 2017 at 3:07 PM, Shenoy, Gourav Ganesh <goshenoy@= indiana.edu> wrote:

Hi dev,

=C2=A0

We were brainstorming some potential designs that might help us with this = problem. One possible option would be to have a =E2=80=9Cworkflow micro-ser= vice=E2=80=9D which would basically be the mediator/orchestrator for deciding which micro-service should be executed next =E2=80=93 based o= n the type of the job. The motive is to make micro-services independent of = the workflow; i.e. a micro-service implementation should be not be aware of= which micro-service will be executed next and we should have a central control of deciding this pattern. <= /u>

Eg: For job type X, the pattern could be A -> B -> C -> D. Wherea= s for job type Y, the pattern could be A -> C -> D; and so on.=

=C2=A0

An initial design with this idea looks like follows:<= /p>

=C2=A0

=C2=A0

We would have a common messaging framework (implementation has not been de= cided yet). The database associated with the workflow micro-service could b= e a graph database (maybe?) =E2=80=93 again the implementation/technology has not been decided yet.

=C2=A0

This is just a proposed design, and I would love to hear your thoughts on = this and any suggestions/comments if any. If there is anything that we are = missing or should consider, please do let us know.

=C2=A0

Thanks and Regards,

Gourav Shenoy

=C2=A0

F= rom: "Christie, Marcus = Aaron" <machri= st@iu.edu>
Reply-To: "dev@airavata.apache.org" <dev@airavata.apache.org>
Date: Friday, February 3, 2017 at 9:21 AM


To: "dev@airavata.apache.org" <dev@airavata.apache.org>
Subject: Re: [#Spring17-Airavata-Courses] : Distributed Workload Man= agement for Airavata

=C2=A0

Vidya,

=C2=A0

I=E2=80=99m not sure how relevant it is, but it occu= rs to me that a microservice that executes jobs on a cloud requires very li= ttle in terms of resources to submit and monitor that job on the cloud. It = doesn=E2=80=99t really matter if the job is a =E2=80=9Cbig=E2=80=9D or a =E2=80=9Csmall=E2=80=9D job.=C2=A0 So I=E2=80=99m not sure what heuri= stic makes sense regarding distributing work to these job execution microse= rvices.=C2=A0 Maybe a simple round robin approach would be sufficient.

=C2=A0

I think a job scheduling algorithm does make sense, = however, for a higher level component, some sort of metascheduler that unde= rstands what resources are available on the cloud resources on which the jo= bs will be running.=C2=A0 The metascheduler could create work for the job exection microservices to run on particular = cloud resources in a way that optimizes for some metric (e.g., throughput).=

=C2=A0

Thanks,

=C2=A0

Marcus

=C2=A0

On Feb 3, 2017, at 3:19 AM, Vidya Sagar Kalvakunta &= lt;vkalvaku@umai= l.iu.edu> wrote:

=C2=A0

Ajinkya,

=C2=A0

My scenario is for workload distribution among multi= ple instances of the same microservice.

=C2=A0

If a message broker needs to distribute the availabl= e jobs among multiple workers, the common approach would be to use round ro= bin or a similar algorithm. This approach works best when all the workers a= re similar and the jobs are equal.

=C2=A0

So I think that a genetic=C2=A0or heuristic job sche= duling algorithm, which is also aware of each of the worker's current s= tate (CPU, RAM, No of Jobs processing)=C2=A0can more efficiently distribute= the jobs. The workers can periodically ping the message broker with their current state info.

=C2=A0

The other advantage of using a customized algorithm = is that it can be=C2=A0tweaked to=C2=A0use embedded routing, priority or ot= her information in the job metadata to resolve all of the concerns raised b= y Amrutha viz message grouping, ordering, repeated messages, etc.

=C2=A0

We can even ensure data privacy, i.e if the workers = are spread across multiple compute clusters say AWS and IU Big Red and we w= ant to restrict certain sensitive jobs to be run only on Big Red.=

=C2=A0

Some distributed job scheduling algorithms for cloud= =C2=A0computing.

=C2=A0

=C2=A0

Regards

Vidya Sagar=C2=A0

=C2=A0

On Fri, Feb 3, 2017 at 1:38 AM, Kamat, Amruta Ravaln= ath <arkamat@in= diana.edu> wrote:

Hello all,

=C2=A0

Adding more information=C2=A0to the mes= sage based approach.=C2=A0Messaging is a key strategy employed in many dist= ributed environments.=C2=A0Message queuing is ideally suited to performing = asynchronous operations. A sender can post a message to a queue, but it does not have to wait while the message is retrieved an= d processed. A sender and receiver do not even have to be running concurren= tly.

=C2=A0

With message queuing there can be 2 pos= sible scenarios:

  1. =E2=80=8BSending and receiving messages= using a single message queue.
  2. =E2=80=8BSharing a message queue between many senders = and receivers

=E2=80=8BWhen a message is retrieved, i= t is removed from the queue. A message queue may also support message peeki= ng.=C2=A0This mechanism can be useful if several receivers are retrieving m= essages from the same queue, but each receiver only wishes to handle specific messages. The receiver can examine the mess= age it has peeked, and decide whether to retrieve the message (which remove= s it from the queue) or leave it on the queue for another receiver to handl= e.

=C2=A0

A few basic message queuing patterns ar= e:

  1. One-way messaging:=C2=A0The sender simply posts a mess= age to the queue in the expectation that a receiver will retrieve it and pr= ocess it at some point.
  2. Request/response messaging:=C2=A0In this pattern a sen= der posts a message to a queue and expects a response from the receiver. Th= e sender can resend if the message is not delivered.=C2=A0This pattern typically requires some form of correlation t= o enable the sender to determine which response message corresponds to whic= h request sent to the receiver.
  3. Broadcast messaging:=C2=A0In this pattern a sender pos= ts a message to a queue, and multiple receivers can read a copy of the mess= age. This pattern depends on the message queue being able to disseminate the same message to multiple receivers. Th= ere is a=C2=A0queue to which the senders can post messages that include met= adata in the form of attributes. Each receiver can create a subscription to= the queue, specifying a filter that examines the values of message attributes. Any messages posted to the queu= e=C2=A0with attribute values that match the filter are automatically forwar= ded to that subscription.

A solution based on asynchronous messag= ing might need to address a number of concerns:

=C2=A0

Message ordering,=C2=A0Message = grouping: Process messages either in the= order they are posted or in a specific order based on priority. Also,=C2= =A0there may be occasions when it is difficult to eliminate dependencies, a= nd it may be necessary to group messages together so that they are all handled by the same receiver.
Idempotency:=C2=A0Ideally the message processing logic in a receiver should be idempotent = so that, if the work performed is repeated, this repetition does not change= the state of the system.
Repeated messages:=C2=A0= Some message queuing systems implement duplicate message detection= and removal based on message IDs
Poison messages:=C2=A0A poison message is a message that cannot be handled, often because = it is malformed or contains unexpected information.=C2=A0
Message expiration:=C2=A0A message might have a limited lifetime, and if it is not process= ed within this period it might no longer be relevant and should be discarde= d.=C2=A0
Message scheduling:=C2=A0A message might be temporarily embargoed and should not be proces= sed until a specific date and time. The message should not be available to = a receiver until this time.


Thanks

Amruta Kamat



From: Shenoy, Gourav Ganesh= <goshenoy@ind= iana.edu>
Sent: Thursday, February 2, 2017 7:57 PM
To: dev= @airavata.apache.org


Subject: Re: [#Spring17-Airavata-Courses] : Distributed Workload Man= agement for Airavata

=C2=A0

Hello al= l,

=C2=A0

Amila, S= agar, thank you for the response and raising those concerns; and apologies = because my email resonated the topic of workload management in terms of how= micro-services communicate. As Ajinkya rightly mentioned, there exists some sort of correlation between micro-ser= vices communication and it=E2=80=99s impact on how that micro-service perfo= rms the work under those circumstances. The goal is to make sure we have ma= ximum independence between micro-services, and investigate the workflow pattern in which these micro-services will op= erate such that we can find the right balance between availability & co= nsistency. Again, from our preliminary analysis we can assert that these so= lutions may not be generic and the specific use-case will have a big decisive role.

=C2=A0

For star= ters, we are focusing on the following example =E2=80=93 and I think this w= ill clarify the doubts on what we are exactly trying to investigate about.<= /span>

=C2=A0

Our t= est example

Say we h= ave the following 4 micro-services, which each perform a specific task as m= entioned in the box.

=C2=A0

<imag= e001.png>

=C2=A0

=C2= =A0

A sta= te-full pattern to distribute work=

<imag= e002.png>

=C2=A0

Here eac= h communication between micro-services could be via RPC or Messaging (eg: R= abbitMQ). Obvious disadvantage is that if any micro-service is down, then t= he system availability is at stake. In this test example, we can see that Microservice-A coordinates the work = and maintains the state information.

=C2=A0

A sta= te-less pattern to distribute work=

=C2=A0

<imag= e003.png>

=C2=A0

Another = purely asynchronous approach would be to associate message-queues with each= micro-service, where each micro-service performs it=E2=80=99s task, submit= s a request (message on bus) to the next micro-service, and continues to process more requests. This ensures more availability, an= d perhaps we might need to handle corner cases for failures such as message= broker down, or message loss, etc.

=C2=A0

As menti= oned, these are just a few proposals that we are planning to investigate vi= a a prototype project. Inject corner cases/failures and try and find ways t= o handle these cases. I would love to hear more thoughts/questions/suggestions.

=C2=A0

Thanks a= nd Regards,

Gourav S= henoy

=C2=A0

From: Ajinkya Dhamnaskar <adhamnas@umail.iu.edu>
Reply-To: "
dev@airavata.apache.org" <dev@airavata.apache.org>
Date: Thursday, February 2, 2017 at 2:22 AM
To: "dev@airavata.apache.org" <dev@airavata.apache.org>
Subject: Re: [#Spring17-Airavata-Courses] : Distributed Workload Man= agement for Airavata

=C2=A0

Hello all,

=C2=A0

Just a heads up. Here the name Distributed wo= rkload management does not necessarily mean having different instances of a= microservice and then distributing work among these instances.=C2=A0

=C2=A0

Apparently, the problem is how to make each m= icroservice work independently with concrete distributed communication infr= astructure. 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, havin= g said that, the crux here is, none of the miscoservices need to worry abou= t other miscoservices in a pipeline.=C2=A0

=C2=A0

Vidya Sagar,

I completely second your opinion of having st= ateless miscoservices, in fact that is the key. With stateless miscroservic= es it is difficult to guarantee consistency in a system but it solves the a= vailability problem to some extent. I would be interested to understand what do you mean by "an intelligent job scheduling algo= rithm, which receives real-time updates from the microservices with their c= urrent state information".=

=C2=A0

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

=C2=A0

On Wed, Feb 1, 2017 at 2:37 PM, Amila Jayasek= ara <thejak= a.amila@gmail.com> wrote:

Hi Gourav,

=C2=A0

Sorry, I did not understand your question. Sp= ecifically I am having trouble relating "work load management" to= options you suggest (RPC, message based etc.).

So what exactly you mean by "workload ma= nagement" ?

What is work in this context ?<= /span>

=C2=A0

Also, I did not understand what you meant by = "the=C2=A0most e= fficient way". Efficient interms of what ? Are you looking at speed ?= =C2=A0

=C2=A0

As per your suggestions, it = seems you are trying to find a way to communicate between micro services. R= PC might be troublesome if you need to communicate with processes separated= from a firewall.=C2=A0<= /span>

=C2=A0

Thanks

-Thejaka

=C2=A0

=C2=A0

On Wed, Feb 1, 2017 at 12:52 PM, Shenoy, Gour= av Ganesh <gos= henoy@indiana.edu> wrote:

Hello dev, arch,

=C2=A0

As part of this Spring=E2=80= =9917 Advanced Science Gateway Architecture course, we are working on tryin= g to debate and find possible solutions to the issue of managing distribute= d workloads in Apache Airavata. This leads to the discussion of finding the most efficient way that different Airavat= a micro-services should communicate and distribute work, in such a way that= :

1.=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 W= e maintain the ability to scale these micro-services whenever needed (autos= cale perhaps?).=

2.=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 A= chieve fault tolerance.

3.=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 W= e can deploy these micro-services independently, or better in a containeriz= ed manner =E2=80=93 keeping in mind the ability to use devops for deploymen= t.

=C2=A0

As of now the options we are= exploring are:

1.=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 R= PC based communication

2.=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 M= essage based =E2=80=93 either master-worker, or work-queue, etc

3.=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 A= combination of both these approaches

=C2=A0

I am more inclined towards e= xploring 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-mentione= d points. Another debatable issue is making the micro-services implementati= on stateless, such that we do not have to pass the state information betwee= n micro-services.=

=C2=A0

I would love to hear any tho= ughts/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 t= his issue, please let me know.<= u>

=C2=A0

Thanks and Regards,

Gourav Shenoy

=C2=A0

=C2=A0

Hi Gourav,

=C2=A0

Correct me if I'm wrong, but I think this= is a case of the job shop scheduling problem, as we may have 'n' j= obs of=C2=A0vary= ing processing times and memory requirements, and we have 'm' microservices=C2=A0with=C2=A0possibly different computing= and memory capacities,=C2=A0and we are trying to minimize the=C2=A0= makespan.=C2=A0

=C2=A0

For this use-case,=C2=A0I'm in favor a hi= ghly available and consistent message broker with an intelligent job schedu= ling algorithm, which receives real-time updates from the microservices wit= h their current state information.

=C2=A0

As for the state vs stateless implementation,= I think that question depends on the functionality of a particular microse= rvice. In a broad sense, the stateless implementation should be preferred= =C2=A0as it will scale better horizontally.=C2=A0

=C2=A0

=C2=A0

Regards,

Vidya Sagar


=C2=A0

--

Vidya Sagar Kalvakunta | Grad= uate MS CS Student |=C2=A0IU School of Informatics and Computing=C2=A0| Ind= iana University Bloomington |=C2=A0(812) 691-5002= =C2=A0|=C2=A0v= kalvaku@iu.edu



=C2=A0

--

Thanks and regards,

=C2=A0

Ajinkya Dhamnaskar

Student ID : 0003469679

Masters (CS)



=C2=A0

--

Vidya Sagar Kalvakun= ta | Graduate MS CS Student |=C2=A0IU School of Informatics and Computing= =C2=A0| Indiana University Bloomington |=C2=A0(812) 691-5002=C2=A0|=C2=A0vkalvaku@iu.edu

=C2=A0




--
Thank you
Supun = Nakandala
Dept. Computer Science and Engineering
University of Moratu= wa
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