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Example 2: Intelligent Orchestration & Scheduling with OpenLava

January 7th, 2017 • Comments Off on Example 2: Intelligent Orchestration & Scheduling with OpenLava

This is the second post in a series (the first post can be found here) about how to insert smarts into a resource manager. So let’s look how a job scheduler or distributed resource management system (DRMS) — in a HPC use case — with OpenLava can be used. For the rationale behind all this check the background section of the last post.

The basic principle about this particular example is simple: each host in a cluster will report a “rank”; the rank will be used to make a decision on where to place a job. The rank could be defined as: a rank is high when the sub-systems of the hosts are heavily used; and the rank is low when none or some sub-system are utilized. How the individual sub-systems usage influences the rank value, is something that can be machine learned.

Let’s assume the OpenLava managed cluster is up and running and a couple of hosts are available. The concept of elims can be used to get the job done. The first step is, to teach the system what the rank is. This is done in the lsf.shared configuration file. The rank is defined to be a numeric value which will be updated every 10 seconds (while not increasing):

Begin Resource
   rank       Numeric 10       N           (A rank for this host.)
End Resource

Next OpenLava needs to know for which hosts this rank should be determined. This is done through a concept of ‘resource mapping’ in the lsf.cluster.* configuration file. For now the rank should be used for all hosts by default:

Begin ResourceMap
rank ([default])
End ResourceMap

Next an external load information manager (LIM) script which will report the rank to OpenLava needs to be written. OpenLava expects that the script writes to stdout with the following format: <number of resources to report on> <first resource name> <first resource value> <second resource name> <second resource value> … . So in this case it should spit out ‘1 rank 42.0‘ every 10 seconds. The following python script will do just this – place this script in the file elim in $LSF_SERVERDIR:

#!/usr/bin/python2.7 -u

import time


def _calc_rank():
    # TODO calc value here...
    return {'rank': value}

while True:
    RES = _calc_rank()
    TMP = [k + ' ' + str(v) for k, v in RES.items()]
    print(\"%s %s\" % (len(RES), ' '.join(TMP)))

Now a special job queue in the lsb.queues configuration file can be used which makes use of the rank. See the RES_REQ parameter in which it is defined that the candidate hosts for a job request are ordered by the rank:

Begin Queue
QUEUE_NAME = special
DESCRIPTION = Special queue using the rank coming from the elim.
RES_REQ = order[rank]
End Queue

Submitting a job to this queue is as easy as: bsub -q special sleep 1000. Or the rank can be passed along as a resource requirements on job submission (for any other queue): bsub -R “order[-rank]” -q special sleep 1000. By adding the ‘-‘ it is said that the submitter request the candidate hosts to be sorted for hosts with a high rank first.

Let’s assume a couple of hosts are up & running and they have different ranks (see the last column):

openlava@242e2f1f935a:/tmp$ lsload -l
HOST_NAME               status  r15s   r1m  r15m   ut    pg    io  ls    it   tmp   swp   mem   rank
45cf955541cf                ok   0.2   0.2   0.3   2%   0.0     0   0 2e+08  159G   16G   11G    9.0
b7245f8e6d0d                ok   0.2   0.2   0.3   2%   0.0     0   0 2e+08  159G   16G   11G    8.0
242e2f1f935a                ok   0.2   0.2   0.3   3%   0.0     0   0 2e+08  159G   16G   11G   98.0

When checking the earlier submitted job, the execution host (EXEC_HOST) is indeed the hosts with the lowest rank as expected:

openlava@242e2f1f935a:/tmp$ bjobs
101     openlav RUN   special    242e2f1f935 b7245f8e6d0 sleep 1000 Jan  7 10:06

The rank can also be seen in web interface like the one available for the OpenLava Mesos framework. What was described in this post is obviously just an example – other methods to integrate your smarts into the OpenLava resource manager can be realized as well.

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