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 80A8C200BAE for ; Fri, 28 Oct 2016 18:30:22 +0200 (CEST) Received: by cust-asf.ponee.io (Postfix) id 7F3AB160AF5; Fri, 28 Oct 2016 16:30:22 +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 AF88C160ACA for ; Fri, 28 Oct 2016 18:30:18 +0200 (CEST) Received: (qmail 37763 invoked by uid 500); 28 Oct 2016 16:30:17 -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 37753 invoked by uid 99); 28 Oct 2016 16:30:17 -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; Fri, 28 Oct 2016 16:30:17 +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 609E4C16A3 for ; Fri, 28 Oct 2016 16:30:16 +0000 (UTC) X-Virus-Scanned: Debian amavisd-new at spamd1-us-west.apache.org X-Spam-Flag: NO X-Spam-Score: 2.379 X-Spam-Level: ** X-Spam-Status: No, score=2.379 tagged_above=-999 required=6.31 tests=[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 Yxg8EcUagOd0 for ; Fri, 28 Oct 2016 16:30:13 +0000 (UTC) Received: from mail-oi0-f54.google.com (mail-oi0-f54.google.com [209.85.218.54]) by mx1-lw-us.apache.org (ASF Mail Server at mx1-lw-us.apache.org) with ESMTPS id 2CE285FB5B for ; Fri, 28 Oct 2016 16:30:13 +0000 (UTC) Received: by mail-oi0-f54.google.com with SMTP id 62so9550638oif.1 for ; Fri, 28 Oct 2016 09:30:13 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20120113; h=mime-version:in-reply-to:references:from:date:message-id:subject:to; bh=pw/uV6daL0DZi83YMAmWIq555ULkX29C4d7m/fjuHgs=; b=TmPRaHwZBCu/WaWtN+t/aKShsPJGmYL5lWjNqeXQMxt/WEkdQ7qwScS2DcnVMRWdMl /fVZdcpbx9aMkMOVHiNBGwnHf1PjIqUb9BahyDcK5FJvJfzqj4pQu3Y1TzpXlK8Y2uUJ bTDF1FNtYXyApC3bT8gztlTpUVN/TKJxVOleKWHtzCjxLKejfHIAx4WrKW5Wq3++0dku qgUvPwcLDgzrSmHrf2QUr8UgjqCzyp/URuSJ+TrHQL2KFSIK8tiRlqi7iWonkrZRgcBh Vt0PW2FGUNeTn/wlD2bGjXSNFmsiiVBVoWikiVe9CPKG/XvCnZKe0JD5mujmKYdYQZXD fJxQ== X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1e100.net; s=20130820; h=x-gm-message-state:mime-version:in-reply-to:references:from:date :message-id:subject:to; bh=pw/uV6daL0DZi83YMAmWIq555ULkX29C4d7m/fjuHgs=; b=VxOp9QMg+q5dlF/WBO2XzFj4SJafWxFxyg6bcXm7vWQaPHIksfgjl5W9rWOr5JBK08 +qGnMHjygv718uyB+FU05QIULHMvHyxZVk5t7vgCp28LRj5sm2Izc5H3cPBxTNHcyZt3 akOREadefZX5JOP7lOroU7PhsLmsGjLvikfGjIJAovE+l4KFHXJTV2E+GUEGqyEAxDkg biuHKiMnFP9Mo/ZUbcw1bImLvuUtAPtk48zephj52Eu20IpDuAosedqPxhpd2gt4aSCV pQULaUdmvRogYmT4rZAO9mFOvbvj4L9UmBfWGolcDykwUJjCTCz03YhOAko64WYYX0Bs CvxQ== X-Gm-Message-State: ABUngvfYfnmPAvaJl16g7bPCaCtEphrHYUCRNQiwRaofrl1qmr1TWWvSwpVMWortOV4TDZaDWZR2DZyEs/v01g== X-Received: by 10.157.58.35 with SMTP id j32mr10797154otc.166.1477672212258; Fri, 28 Oct 2016 09:30:12 -0700 (PDT) MIME-Version: 1.0 Received: by 10.182.39.104 with HTTP; Fri, 28 Oct 2016 09:30:11 -0700 (PDT) In-Reply-To: <9416D1A7-ED33-44FC-ADA9-8D09E4F69EEE@indiana.edu> References: <679996DA-4BFD-4D74-B701-6CCE2394D663@indiana.edu> <2EAC123F-9F6A-47B9-B007-3DC0D42F77AB@indiana.edu> <9416D1A7-ED33-44FC-ADA9-8D09E4F69EEE@indiana.edu> From: Amila Jayasekara Date: Fri, 28 Oct 2016 12:30:11 -0400 Message-ID: Subject: Re: Mesos based meta-scheduling for Airavata To: dev Content-Type: multipart/related; boundary=001a114713ac4e9b3a053fef5f45 archived-at: Fri, 28 Oct 2016 16:30:22 -0000 --001a114713ac4e9b3a053fef5f45 Content-Type: multipart/alternative; boundary=001a114713ac4e9b37053fef5f44 --001a114713ac4e9b37053fef5f44 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Hi Gourav, These are excellent descriptions, but it would be useful if you can lay out your findings according to Mark's questions from the other thread. As per my understanding Mark's question is still not answered (I hope Mark will agree with me). Also, I am confused about the terminologies used in these tools. For example, what is the difference between Aurora tasks and Mesos task and what is the difference between thermos and mesos task? In fact, what is the definition of a task in this context? I assume "process" has the standard definition from OS books (a running program). In MPI we use "aprun -n 32 -N 16 ./a.out" (Suppose we request 2 nodes). Here the whole command ("aprun -n 4 -N 2 ./a.out") is the job and "-n" specifies the number of tasks and "-N" specifies the number of tasks per node (two nodes comprises (16 * 2 =3D) 32 tasks). So how do these (MPI) tas= ks related to Aurora/Mesos tasks? Further, the "-N" parameter depends on the type of nodes we are using and the number of cores a node has. For example, if the resource has 16 cores per node we will use the above command to run 32 tasks, but if a node has eight cores, then we will use a command like "aprun -n 32 -N 8 ./a.out" (in this case we have to request four nodes). So given a command like "apru= n -n 32 ./a.out", is Mesos/Aurora capable of adding "-N" parameter to the command based on the cluster and types of nodes ? Thanks -Thejaka On Mon, Oct 17, 2016 at 11:32 PM, Shenoy, Gourav Ganesh < goshenoy@indiana.edu> wrote: > Hi dev, > > > > Now that I have been able to get jobs scheduled via Aurora, I thought I > should summarize my understanding. I would also like to briefly draw out > the plan which I am working on with respect to using Mesos with Airavata. > > > > *Apache Aurora:* > > > > =C2=B7 Aurora, similar to Marathon & Chronos, is a service schedu= ler > framework for Mesos. It has been built for scheduling long running servic= es > & cron jobs on Mesos. > > =C2=B7 The advantage with Aurora (over Marathon & Chronos) is tha= t it > works well for one-off jobs as well =E2=80=93 i.e. If I want to run a job= and get > the output, Aurora is a better fit than Marathon & Chronos, since Maratho= n > will never let the job exit (and keep restarting it on slaves) & Chronos = is > ONLY for crons. > > =C2=B7 Aurora also allows fine grained control of the jobs that n= eed > to be submitted =E2=80=93 the concept of jobs, tasks, processes =E2=80=93= a job can consist > of one or more tasks, and a task can consist of one or more processes. > > =C2=B7 Aurora manages jobs that are made up of tasks; Mesos manag= es > the tasks that consist of processes; Thermos (is the Aurora executor) > manages the processes. > > =C2=B7 We can control resource utilization at task level because = of > the above job abstractions that Aurora provides. > > =C2=B7 Among many other features, a useful one is the resource-qu= ota > management for users & the ability to support multiple users to run jobs. > > > > *Current focus:* > > > > =C2=B7 I am currently working on building a Thrift based client f= or > Aurora, and have been successful in implementing one, but with limited > operations. > > =C2=B7 I will be adding support for more operations keeping them > aligned to Airavata job submission/monitoring requirements. > > =C2=B7 I am currently focusing on targeting Airavata deployment t= o > Mesos on a single cluster (eg: AWS). The flow would look like follows: > > =C2=B7 As you can see, currently there is just a single Mesos clu= ster. > The future focus would be to expand this to have multiple clusters. > > > > *Subsequent work:* > > =C2=B7 Once we are able to test Airavata deployment to single clu= ster > successfully, we can expand this to a multi-cluster environment. > > =C2=B7 Here we would multiple Mesos clusters which would somehow = need > to be managed. But, the overall flow would look like follows: > > > > =C2=B7 We can either have multiple Mesos masters (for each indivi= dual > cluster), that are connected to each other via VPN, or have a single mast= er > =E2=80=93 in which case we would need to consider all other nodes as slav= es. > > =C2=B7 This is a design issue which needs discussion, and Suresh = has > some ideas on how to do this. > > > > Thanks and Regards, > > Gourav Shenoy > > > > *From: *Suresh Marru > *Reply-To: *"dev@airavata.apache.org" > *Date: *Friday, October 7, 2016 at 11:43 PM > *To: *Airavata Dev > *Subject: *Re: Mesos based meta-scheduling for Airavata > > > > Hi Gourav, > > > > Thank you for the nice informative summaries, posts like these are always > educational. Keep=E2=80=99em coming. > > > > Suresh > > > > On Oct 7, 2016, at 10:56 PM, Shenoy, Gourav Ganesh > wrote: > > > > Hi dev, > > > > I have been exploring different frameworks for Mesos which would help our > use-case of providing Airavata the capability to run jobs in a Mesos base= d > ecosystem. In particular, I have been playing around with Marathon & > Chronos and I am now going to be working on Apache Aurora. > > > > I have summarized my understanding about Mesos, Marathon & Chronos below. > I will send out a separate email about Aurora later. > > > > *Apache Mesos:* > > > > =C2=B7 Apache Mesos is an open-source cluster manager, in the sen= se > that it helps deploy & manage different frameworks (or applications) in a > large clustered environment easily. > > =C2=B7 Mesos provides the ability to utilize underlying shared po= ol of > nodes as a single compute unit =E2=80=93 That is, it can run many applica= tions on > these nodes efficiently. > > =C2=B7 Mesos uses the concept of =E2=80=9Coffers=E2=80=9D for sch= eduling and running > jobs on the underlying nodes. When a framework (application) wants to run > computations/jobs on the cluster, Mesos will decide how many resources it > will =E2=80=9Coffer=E2=80=9D that framework based on the availability. Th= e framework will > then decide which resources to use from the offer, and subsequently run t= he > computation/job on that resource. > > =C2=B7 In a typical cluster, you will have 3 or more Mesos master= s & > multiple Mesos slaves. Multiple mesos masters help in providing high > availability =E2=80=93 if one master goes down, Mesos will reelect a new = leader > (master) =E2=80=93 using Zookeeper. > > =C2=B7 The task mentioned above of providing =E2=80=9Coffers=E2= =80=9D to frameworks is > done by a master, whereas the slaves are the ones who run these > computations. > > > > =C2=B7 Some additional points: > > o I built a Mesos cluster with 3 masters & 2 slaves on EC2. > > o Each master & slave have 1GB of RAM & 1vCPU with 20GB of disk space. > > > > *Marathon:* > > > > =C2=B7 Marathon is considered a framework that runs on top of Mes= os. > It is a container orchestration platform for Mesos and essentially acts a= s > a service scheduler. > > =C2=B7 It is named =E2=80=9Cmarathon=E2=80=9D because it is inten= ded for long running > applications. That is, Marathon makes sure that the service it is running > never stops =E2=80=93 if a service goes down or the slave on which the se= rvice is > run dies, marathon keeps re-starting it on different slaves. > > =C2=B7 In some sense Marathon is very good for ensuring high > availability of services. That is, instead of running services directly o= n > Mesos, run it in Marathon if you never want it to die. > *Note*: You can decide to run a service on multiple slave nodes and if > resources on these slaves are available, Mesos will =E2=80=9Coffer=E2=80= =9D them to > Marathon. > > =C2=B7 It is called a container orchestration platform because it > =E2=80=9Claunches=E2=80=9D these services inside a container =E2=80=93 ei= ther Docker OR Mesos > container. > > =C2=B7 In my opinion it is not a suitable =E2=80=9Cjob scheduler= =E2=80=9D for Airavata > because in Airavata we need to run a job and get the output rather than > keeping it running always. Instead, we can run other schedulers =E2=80=93 > chronos/aurora as a service in Marathon. > > > *Chronos:* > > > > =C2=B7 Chronos is a Cron scheduler for Mesos. It is good for runn= ing > scheduled jobs =E2=80=93 jobs that need to be run for a certain number of= times, > repeatedly after certain intervals. > > =C2=B7 Chronos also provides the ability to add dependencies betw= een > jobs =E2=80=93 That is, if a job1 is dependent on another job2 then it wi= ll run > job1 first and then run job2 after job1 completes. It also builds a > Directed Acyclic Graph (DAG) based on these dependencies. > > =C2=B7 Similar to Marathon, Chronos receives =E2=80=9Coffers=E2= =80=9D from Mesos > master whenever it needs to run a job on Mesos. > > =C2=B7 Again, I found that Chronos does not fit the Airavata use-= case > since I could not find a way to run one-off jobs via Chronos =E2=80=93 yo= u need to > specify interval time for Chronos, & Chronos then re-runs the job after > that interval is complete (even if you decide to specify num. of > repetitions=3D1). > > > > > > Some additional points: > > =C2=B7 Marathon & Chronos both have REST API support =E2=80=93 eg= : you can > submit jobs via APIs along with other interactions such as list jobs, etc= . > > =C2=B7 I installed Marathon & Chronos frameworks on the Mesos mas= ter > nodes. This is how their health looks like on the Mesos dashboard: > > > > > > As you can see, there are 3 active tasks running in > Chronos & 4 active tasks (long running) in Marathon. > > > > =C2=B7 I also installed Chronos as a service inside Marathon, and= this > is how it looks like in the Marathon UI: > > > > > Interestingly, Chronos (as a service in Marathon) was smart enough to > identify the jobs submitted via Chronos (as a framework on Mesos) & > vice-versa. > > > > =C2=B7 Also, Mesos dashboard lists the active tasks it is running= & > details about which slave the task is running on. It also lists Completed > tasks. The =E2=80=9CSandbox=E2=80=9D gives you access to the stdout/stder= r files for the > tasks as well as any other directories that were created as part of the > task. > > > > > > > Pardon me for this long email. Next, I will explore Apache Aurora which > seems a better fit for Airavata use-case because it provides the features > that Chronos supports, as well as can run one-off jobs. > > > > Thanks and Regards, > > Gourav Shenoy > > > > *From: *"Shenoy, Gourav Ganesh" > *Reply-To: *"dev@airavata.apache.org" > *Date: *Friday, September 23, 2016 at 4:43 PM > *To: *"dev@airavata.apache.org" > *Subject: *Mesos based meta-scheduling for Airavata > > > > Hi Dev, > > > > I am working on this project of building a Mesos based meta-scheduler for > Airavata, along with Shameera & Mangirish. Here is the jira link: > https://issues.apache.org/jira/browse/AIRAVATA-2082. > > > > =C2=B7 We have identified some tasks that would be needed for > achieving this, and at the higher level it would consist of: > > 1. Resource provisioning =E2=80=93 We need to provision resources on= cloud & > hpc infrastructures such as EC2, Jetstream, Comet, etc. > > 2. Building a cluster =E2=80=93 Deploying a Mesos cluster on set of = nodes > obtained from (1) above for task management. > > 3. Selecting a scheduler =E2=80=93 We need to investigate the schedu= ler to > use with Mesos cluster. Some of the options are Marathon, Aurora. But we > need to find one that suits our needs of running serial as well as parall= el > (MPI) jobs. > > 4. Installing & running applications on this cluster =E2=80=93 Once = the > cluster has been deployed and a scheduler choice made, we need to be able > to install and run applications on this cluster using Airavata. > > > > =C2=B7 Until now we were able to look into the following: > > o Resource provisioning: > > =C2=A7 We explored several options of provisioning resources =E2=80=93 u= sing cloud > libraries as well as via ansible scripts. > > =C2=A7 We built a OpenStack4J Java module which would provision instance= s on > OpenStack based clouds (eg: Jetstream). > > =C2=A7 We also built a CloudBridge Python module for provisioning EC2 > instances on Amazon. CloudBridge can also be used to provision instances = on > OpenStack > > =C2=A7 We wrote Ansible scripts for bringing up instances on both AWS an= d > OpenStack based clouds. > > > > =C2=A7 *Key Points*: CloudBridge, OpenStack4J are powerful libraries for > resource provisioning, but currently they do single-instance provisioning= , > and not support templated boot options such as CloudFormation (for AWS) & > Heat (for OpenStack). > > > > o Building a cluster: > > =C2=A7 We wrote Ansible script for deploying a Mesos-Marathon cluster on= a > set of nodes. This script will install necessary dependencies such as > Zookeeper. > > =C2=A7 We tested this on OpenStack based clouds & on EC2. > > =C2=A7 OpenStack Magnum provides excellent support for doing resource > provisioning & deploying mesos cluster, but we are running into some > problems while trying it. > > > > o Installing a scheduler: > > =C2=A7 Our Ansible script is currently installing Marathon as the schedu= ler > on Mesos. We haven=E2=80=99t yet submitted jobs using Marathon. > > > > =C2=B7 Although not finalized, but we are inclined towards using > Ansible approach for the above, as Ansible also provides Python APIs and > which will allow us to integrate it with Airavata via Thrift. Hence we wi= ll > be able to easily invoke the Ansible scripts from code without needing to > use the command-line interface. > > > > =C2=B7 We are also progressively working on some work-items such = as: > > o Exploring options to provision and deploy a Mesos-Marathon cluster on > HPC systems such as Comet. The challenge would be to use Ansible to > provision resources and deploy the cluster. Once we have a cluster, we ca= n > try running applications. > > o Exploring different scheduler options for running serial and parallel > (MPI) jobs on such heterogeneous clusters. > > o Exploring orchestration options such as OpenStack Heat, AWS > CloudFormation, OpenStack Magnum, etc. > > > > Any suggestions and comments are highly appreciated. > > > > Thanks and Regards, > > Gourav Shenoy > > > --001a114713ac4e9b37053fef5f44 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
Hi=C2=A0Gourav,

These are= excellent descriptions, but it would be useful if you can lay out your fin= dings according to Mark's questions from the other thread. As per my un= derstanding Mark's question is still not answered (I hope Mark will agr= ee with me).=C2=A0

Also, I am confus= ed about the terminologies used in these tools.
For exampl= e, what is the difference between Aurora tasks and Mesos task and what is t= he difference between thermos and mesos=C2=A0task? In fact,=C2=A0what is th= e definition of a task in this context? I assume "process" has th= e standard definition from OS books (a running program).
<= span style=3D"color:rgb(80,0,80);font-family:calibri;font-size:14.6667px"><= br>
In MPI we use "aprun=C2=A0-n 32 -N 16 ./a.out&quo= t; (Suppose we request 2 nodes). Here the whole command ("aprun= =C2=A0-n 4 -N 2 ./a.out") is the job and "-n" specifi= es the number of tasks and "-N" specifies the=C2=A0number of task= s per node (two nodes comprises (16 * 2 =3D) 32 tasks). So how do these (MP= I) tasks related to Aurora/Mesos tasks?

<= div>Further, the "-N" parameter depends on the type of nodes we a= re using and the number of cores a node has. For example, if the resource h= as 16 cores per node we will use the above command to run 32 tasks, but if = a node has eight cores, then we will use a command like=C2=A0=C2=A0&= quot;aprun=C2=A0-n 32 -N 8 ./a.out" (in this case we have to re= quest four nodes). So given a command like "aprun=C2=A0-n 32 ./= a.out", is Mesos/Aurora capable of adding "-N" parameter to = the command based on the cluster and types of nodes ?

=
Thanks
-Thejaka



On Mon, Oct 17, 2016 at 11:32 PM, Shenoy, Gourav Ganes= h <goshenoy@indiana.edu> wrote:

Hi dev,

=C2=A0

Now that I have been able to get jobs scheduled via Aurora, I thought I sh= ould summarize my understanding. I would also like to briefly draw out the = plan which I am working on with respect to using Mesos with Airavata.

=C2=A0

Apache Aurora:

=C2=A0

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Aurora, similar to Marathon & Chronos, is a service scheduler fra= mework for Mesos. It has been built for scheduling long running services &a= mp; cron jobs on Mesos.

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 The advantage with Aurora (over Marathon & Chronos) is that it wo= rks well for one-off jobs as well =E2=80=93 i.e. If I want to run a job and= get the output, Aurora is a better fit than Marathon & Chronos, since Marathon will never let the job exit (and ke= ep restarting it on slaves) & Chronos is ONLY for crons.<= /span>

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Aurora also allows fine grained control of the jobs that need to be s= ubmitted =E2=80=93 the concept of jobs, tasks, processes =E2=80=93 a job ca= n consist of one or more tasks, and a task can consist of one or more processes.

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Aurora manages jobs that are made up of tasks; Mesos manages the task= s that consist of processes; Thermos (is the Aurora executor) manages the p= rocesses.

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 We can control resource utilization at task level because of the abov= e job abstractions that Aurora provides.

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Among many other features, a useful one is the resource-quota managem= ent for users & the ability to support multiple users to run jobs.

=C2=A0

Current focus:

=C2=A0

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 I am currently working on building a Thrift based client for Aurora, = and have been successful in implementing one, but with limited operations.

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 I will be adding support for more operations keeping them aligned to = Airavata job submission/monitoring requirements.

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 I am currently focusing on targeting Airavata deployment to Mesos on = a single cluster (eg: AWS). The flow would look like follows:=

= <= /span>

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 As you can see, currently there is just a single Mesos cluster. The f= uture focus would be to expand this to have multiple clusters.

=C2=A0

Subsequent work:

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Once we are able to test Airavata deployment to single cluster succes= sfully, we can expand this to a multi-cluster environment.

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Here we would multiple Mesos clusters which would somehow need to be = managed. But, the overall flow would look like follows:

= <= /span>

=C2=A0

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 We can either have multiple Mesos masters (for each individual cluste= r), that are connected to each other via VPN, or have a single master =E2= =80=93 in which case we would need to consider all other nodes as slaves.

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 This is a design issue which needs discussion, and Suresh has some id= eas on how to do this.

=C2=A0

Thanks and Regards,

Gourav Shenoy

=C2=A0

F= rom: Suresh Marru <smarru@apache.org><= br> Reply-To: "dev@airavata.apache.org" <dev@airavata.apache.org>
Date: Friday, October 7, 2016 at 11:43 PM
To: Airavata Dev <dev@airavata.apache.org>
Subject: Re: Mesos based meta-scheduling for Airavata<= /span>

=C2=A0

Hi Gourav,

=C2=A0

Thank you for the nice informative summaries, posts = like these are always educational. Keep=E2=80=99em coming.=C2=A0<= /u>

=C2=A0

Suresh

=C2=A0

On Oct 7, 2016, at 10:56 PM, Shenoy, Gourav Ganesh &= lt;goshenoy@india= na.edu> wrote:

=C2=A0

Hi dev,

=C2=A0

I have been exploring different frameworks for Mesos which would help our = use-case of providing Airavata the capability to run jobs in a Mesos based = ecosystem. In particular, I have been playing around with Marathon & Chronos and I am now going to be workin= g on Apache Aurora.=C2=A0

=C2=A0

I have summarized my understanding about Mesos, Marathon & Chronos bel= ow. I will send out a separate email about Aurora later.

=C2=A0

Apache Mesos:<= /u>

=C2=A0

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= Apache Mesos is an open-source cluster manager, in the sense that it helps deploy &= manage different frameworks (or applications) in a large clustered environ= ment easily.

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= Mesos provides the ability to utilize underlying shared pool of nodes as a single compute= unit =E2=80=93 That is, it can run many applications on these nodes effici= ently.

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= Mesos uses the concept of =E2=80=9Coffers=E2=80=9D for scheduling and running jobs on= the underlying nodes. When a framework (application) wants to run computat= ions/jobs on the cluster, Mesos will decide how many resources it will =E2= =80=9Coffer=E2=80=9D that framework based on the availability. The framework will then decide which resources to use from the offer, and subs= equently run the computation/job on that resource.

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= In a typical cluster, you will have 3 or more Mesos masters & multiple Mesos slaves= . Multiple mesos masters help in providing high availability =E2=80=93 if o= ne master goes down, Mesos will reelect a new leader (master) =E2=80=93 usi= ng Zookeeper.

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= The task mentioned above of providing =E2=80=9Coffers=E2=80=9D to frameworks is done by a mas= ter, whereas the slaves are the ones who run these computations.

=C2=A0

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= Some additional points:

o=C2=A0=C2=A0=C2=A0= =C2=A0I built a Mesos cluster with 3 masters & 2 slaves on EC2.

o=C2=A0=C2=A0=C2=A0= =C2=A0Each master & slave have 1GB of RAM & 1vCPU with 20GB of disk space.

=C2=A0

Marathon:<= u>

=C2=A0

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= Marathon is considered a framework that runs on top of Mesos. It is a container orches= tration platform for Mesos and essentially acts as a service scheduler.

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= It is named =E2=80=9Cmarathon=E2=80=9D because it is intended for long running applica= tions. That is, Marathon makes sure that the service it is running never st= ops =E2=80=93 if a service goes down or the slave on which the service is r= un dies, marathon keeps re-starting it on different slaves.=C2=A0

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= In some sense Marathon is very good for ensuring high availability of services. That is,= instead of running services directly on Mesos, run it in Marathon if you n= ever want it to die.
Note: You can decide to run a service on multiple slave nodes and if= resources on these slaves are available, Mesos will =E2=80=9Coffer=E2=80= =9D them to Marathon.
<= /u>

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= It is called a container orchestration platform because it =E2=80=9Claunches=E2=80=9D t= hese services inside a container =E2=80=93 either Docker OR Mesos container= .

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= In my opinion it is not a suitable =E2=80=9Cjob scheduler=E2=80=9D for Airavata because = in Airavata we need to run a job and get the output rather than keeping it = running always. Instead, we can run other schedulers =E2=80=93 chronos/auro= ra as a service in Marathon.


Chronos:

=C2=A0

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= Chronos is a Cron scheduler for Mesos. It is good for running scheduled jobs =E2=80= =93 jobs that need to be run for a certain number of times, repeatedly afte= r certain intervals.

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= Chronos also provides the ability to add dependencies between jobs =E2=80=93 That is, i= f a job1 is dependent on another job2 then it will run job1 first and then = run job2 after job1 completes. It also builds a Directed Acyclic Graph (DAG= ) based on these dependencies.

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= Similar to Marathon, Chronos receives =E2=80=9Coffers=E2=80=9D from Mesos master when= ever it needs to run a job on Mesos.

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= Again, I found that Chronos does not fit the Airavata use-case since I could not find a w= ay to run one-off jobs via Chronos =E2=80=93 you need to specify interval t= ime for Chronos, & Chronos then re-runs the job after that interval is = complete (even if you decide to specify num. of repetitions=3D1).<= /u>

=C2=A0

=C2=A0

Some additional points:<= u>

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= Marathon & Chronos both have REST API support =E2=80=93 eg: you can submit jobs via A= PIs along with other interactions such as list jobs, etc.

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= I installed Marathon & Chronos frameworks on the Mesos master nodes. This is how t= heir health looks like on the Mesos dashboard:

=C2=A0

<image002.png= >

=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0 As you can see, there are 3 active tasks running in Chro= nos & 4 active tasks (long running) in Marathon.

=C2=A0

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= I also installed Chronos as a service inside Marathon, and this is how it looks like in the= Marathon UI:


<image004.png= >

Interestingly, Chronos (as a service in Marath= on) was smart enough to identify the jobs submitted via Chronos (as a frame= work on Mesos) & vice-versa.=

=C2=A0

= =C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0= =C2=A0=C2=A0=C2=A0=C2=A0= Also, Mesos dashboard lists the active tasks it is running & details about which s= lave the task is running on. It also lists Completed tasks. The =E2=80=9CSa= ndbox=E2=80=9D gives you access to the stdout/stderr files for the tasks as= well as any other directories that were created as part of the task.


<image005.png= >

=C2=A0

Pardon me for this long email. Next, I will explore Apache Aurora which se= ems a better fit for Airavata use-case because it provides the features tha= t Chronos supports, as well as can run one-off jobs.

=C2=A0

Thanks and Regards,

Gourav Shenoy

=C2=A0

From:=C2=A0= "Shenoy, Gourav Ganesh" <<= a href=3D"mailto:goshenoy@indiana.edu" target=3D"_blank">goshenoy@indiana.e= du>
Reply-To:=C2= =A0"dev@airavata.apache.org" <dev@airavata.apache.org>
Date:=C2=A0Friday, September 23, 2016 at 4:43 PM
To:=C2=A0"d= ev@airavata.apache.org" <dev@airavata.apache.org>
Subject:=C2= =A0Mesos based meta-scheduling for Airavata
=

=C2=A0=

Hi Dev,

=C2=A0

I am working on this project of building a Mesos based meta-scheduler for = Airavata, along with Shameera & Mangirish. Here is the jira link:https://issues.apache.org/jira/browse/A= IRAVATA-2082.<= u>

=C2=A0

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2= =A0=C2=A0= We have identif= ied some tasks that would be needed for achieving this, and at the higher level it would = consist of:=

1.=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0Resource provisioning =E2=80=93 We nee= d to provision resources on cloud & hpc infrastructures such as EC2, Jet= stream, Comet, etc.

2.=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0Building a cluster =E2=80=93 Deploying a Mesos cluster on set of nodes obtained from (1) above for task managemen= t.

3.=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0Selecting a scheduler =E2=80=93 We nee= d to investigate the scheduler to use with Mesos cluster. Some of the option= s are Marathon, Aurora. But we need to find one that suits our needs of run= ning serial as well as parallel (MPI) jobs.

4.=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0Installing & running applications on this cluster =E2=80=93 Once the cluster has been deployed and a schedul= er choice made, we need to be able to install and run applications on this = cluster using Airavata.

=C2=A0

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2= =A0=C2=A0= Until now we we= re able to look into the following:

= o=C2=A0=C2=A0=C2=A0Resource provisioning:

=C2=A7<= span style=3D"font-size:7.0pt">=C2=A0=C2=A0We explored several options of provisioning resources =E2=80=93 using cloud libraries as well as via ansible scripts.<= /span>

=C2=A7<= span style=3D"font-size:7.0pt">=C2=A0=C2=A0We built a OpenStack4J Java module which would provision instances on OpenStack based clouds (eg: Jetstream).=

=C2=A7<= span style=3D"font-size:7.0pt">=C2=A0=C2=A0We also built a CloudBridge Python module for provisioning EC2 instances on Amazon. CloudBridge can also be u= sed to provision instances on OpenStack

=C2=A7<= span style=3D"font-size:7.0pt">=C2=A0=C2=A0We wrote Ansible scripts for bringing up instances on both AWS and OpenStack based clouds.

=C2=A0

=C2=A7<= span style=3D"font-size:7.0pt">=C2=A0=C2=A0Key Points: CloudBridge, OpenStack4J are powerful libraries for resource provisioning,= but currently they do single-instance provisioning, and not support templa= ted boot options such as CloudFormation (for AWS) & Heat (for OpenStack= ).

=C2=A0

= o=C2=A0=C2=A0=C2=A0Building a cluster:

=C2=A7<= span style=3D"font-size:7.0pt">=C2=A0=C2=A0We wrote Ansible script for deploying a Mesos-Marathon cluster on a set of nodes. This script will install neces= sary dependencies such as Zookeeper.

=C2=A7<= span style=3D"font-size:7.0pt">=C2=A0=C2=A0We tested this on OpenStack based clouds & on EC2.<= /u>

=C2=A7<= span style=3D"font-size:7.0pt">=C2=A0=C2=A0OpenStack Magnum provides excellent support for doing resource provisioning & deploying mesos cluster, but= we are running into some problems while trying it.

=C2=A0

= o=C2=A0=C2=A0=C2=A0Installing a scheduler:

=C2=A7<= span style=3D"font-size:7.0pt">=C2=A0=C2=A0Our Ansible script is currently installing Marathon as the scheduler on Mesos. We haven=E2=80=99t yet subm= itted jobs using Marathon.

=C2=A0

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2= =A0=C2=A0= Although not fi= nalized, but we are inclined towards using Ansible approach for the above, as Ansible a= lso provides Python APIs and which will allow us to integrate it with Airav= ata via Thrift. Hence we will be able to easily invoke the Ansible scripts = from code without needing to use the command-line interface.<= /u>

=C2=A0

=C2=B7=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2= =A0=C2=A0= We are also pro= gressively working on some work-items such as:<= /u>

= o=C2=A0=C2=A0=C2=A0Exploring options to provision and deploy a Mesos-Marathon cluster on HPC systems such as Comet. The chal= lenge would be to use Ansible to provision resources and deploy the cluster= . Once we have a cluster, we can try running applications.

= o=C2=A0=C2=A0=C2=A0Exploring different scheduler options for running serial and parallel (MPI) jobs on such heterogeneous c= lusters.

= o=C2=A0=C2=A0=C2=A0Exploring orchestration options such as OpenStack Heat, AWS CloudFormation, OpenStack Magnum, etc.<= span style=3D"font-family:Calibri">

=C2=A0

Any suggestions and comments are highly appreciated.

=C2=A0

Thanks and Regards,

Gourav Shenoy

=C2=A0


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