nopaque/app/swarm.py

import docker
import time


class Swarm:
    def __init__(self):
        self.docker = docker.from_env()

    '''
    ' Swarm mode is intendet to run containers which serve a non terminating
    ' service like a webserver. For processing an occuring job it is necessary
    ' to use a one-shot container, which stops after the wrapped job process is
    ' completly executed. In order to run these one-shot containers in Swarm
    ' mode, the following run method is implemented analog to the presented
    ' implementation in Alex Ellis' blog post "One-shot containers on Docker
    ' Swarm"¹.
    '
    ' ¹ https://blog.alexellis.io/containers-on-swarm/
    '''

    def run(self, job):
        # Prepare argument values needed for the service creation.
        _command = 'ocr' \
                  + ' -i /files/{}'.format(job['id']) \
                  + ' -l {}'.format(job['service_args']['lang']) \
                  + ' -o /files/{}/output'.format(job['id']) \
                  + ' --keep-intermediates' \
                  + ' --nCores {}'.format(job['requested_cpus'])
        _constraints = ['node.role==worker']
        _image = 'gitlab.ub.uni-bielefeld.de:4567/sfb1288inf/{}:{}'.format(
            job['service'],
            job['service_args']['version']
        )
        _labels = {'service': 'ocr'}
        _mounts = [
            '/home/compute/mnt/opaque/jobs:/files:rw',
        ]
        _name = job['id']
        '''
        ' The Docker SDK for Python expects the cpu_reservation value to be
        ' scaled to nanos (10^9). Because the job object contains unscaled
        ' (10^0) values, it must be conveted.
        '
        ' While the cpu_reservation value has to be in nanos, the
        ' mem_reservation value must be presented in an unscaled form
        ' (intuitive right?). Bacause the job object provides the memory value
        ' in megabytes, it is also necessary to convert the value.
        '''
        _resources = docker.types.Resources(
            cpu_reservation=job['requested_cpus'] * (10 ** 9),
            mem_reservation=job['requested_memory'] * (10 ** 6)
        )
        _restart_policy = docker.types.RestartPolicy(condition='none')
        '''
        ' Create the service with the prepared values.
        '
        ' Note: A service reserves hardware ressources. In case no worker node
        '       has the required ressources available (not reserved), the
        '       service gets queued by the Docker engine until a node is able
        '       to meet the requirements.
        '
        ' TODO: The name argument should be used with the prepared value
        '       (name=_name). Because there is no id generator for now, it is
        '       not set, so that the Docker engine assigns a random name.
        '''
        service = self.docker.services.create(
            _image,
            command=_command,
            constraints=_constraints,
            labels=_labels,
            mounts=_mounts,
            resources=_resources,
            restart_policy=_restart_policy
        )
        '''
        ' Poll the service until the job is completly executed.
        '
        ' Note: Because it takes some time until all data in the service object
        '       is initialized (especcially the task list returned by the tasks
        '       method) the poll loop also checks if the task list is empy (The
        '       not service.tasks() condition implements this).
        '''
        while not service.tasks() or \
                service.tasks()[0].get('Status').get('State') != 'complete':
            time.sleep(1)
            service.reload()
        # Remove the service from the swarm.
        service.remove()

        return