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Source code for galaxy.jobs.runners.kubernetes
"""
Offload jobs to a Kubernetes cluster.
"""
import logging
import re
from os import environ as os_environ
from six import text_type
from galaxy import model
from galaxy.jobs.runners import (
AsynchronousJobRunner,
AsynchronousJobState,
JobState
)
# pykube imports:
try:
from pykube.config import KubeConfig
from pykube.http import HTTPClient
from pykube.objects import (
Job,
Pod
)
except ImportError as exc:
KubeConfig = None
K8S_IMPORT_MESSAGE = ('The Python pykube package is required to use '
'this feature, please install it or correct the '
'following error:\nImportError %s' % str(exc))
log = logging.getLogger(__name__)
__all__ = ('KubernetesJobRunner', )
[docs]class KubernetesJobRunner(AsynchronousJobRunner):
"""
Job runner backed by a finite pool of worker threads. FIFO scheduling
"""
runner_name = "KubernetesRunner"
[docs] def __init__(self, app, nworkers, **kwargs):
# Check if pykube was importable, fail if not
assert KubeConfig is not None, K8S_IMPORT_MESSAGE
runner_param_specs = dict(
k8s_config_path=dict(map=str, default=os_environ.get('KUBECONFIG', None)),
k8s_use_service_account=dict(map=bool, default=False),
k8s_persistent_volume_claim_name=dict(map=str),
k8s_persistent_volume_claim_mount_path=dict(map=str),
k8s_namespace=dict(map=str, default="default"),
k8s_job_api_version=dict(map=str, default="batch/v1"),
k8s_supplemental_group_id=dict(map=str),
k8s_pull_policy=dict(map=str, default="Default"),
k8s_fs_group_id=dict(map=int),
k8s_default_requests_cpu=dict(map=str, default=None),
k8s_default_requests_memory=dict(map=str, default=None),
k8s_default_limits_cpu=dict(map=str, default=None),
k8s_default_limits_memory=dict(map=str, default=None),
k8s_pod_retrials=dict(map=int, valid=lambda x: int > 0, default=3))
if 'runner_param_specs' not in kwargs:
kwargs['runner_param_specs'] = dict()
kwargs['runner_param_specs'].update(runner_param_specs)
"""Start the job runner parent object """
super(KubernetesJobRunner, self).__init__(app, nworkers, **kwargs)
# self.cli_interface = CliInterface()
if "k8s_use_service_account" in self.runner_params and self.runner_params["k8s_use_service_account"]:
self._pykube_api = HTTPClient(KubeConfig.from_service_account())
else:
self._pykube_api = HTTPClient(KubeConfig.from_file(self.runner_params["k8s_config_path"]))
self._galaxy_vol_name = "pvc-galaxy" # TODO this needs to be read from params!!
self._supplemental_group = self.__get_supplemental_group()
self._fs_group = self.__get_fs_group()
self._default_pull_policy = self.__get_pull_policy()
self._init_monitor_thread()
self._init_worker_threads()
[docs] def queue_job(self, job_wrapper):
"""Create job script and submit it to Kubernetes cluster"""
# prepare the job
# We currently don't need to include_metadata or include_work_dir_outputs, as working directory is the same
# were galaxy will expect results.
log.debug("Starting queue_job for job " + job_wrapper.get_id_tag())
if not self.prepare_job(job_wrapper, include_metadata=False, modify_command_for_container=False):
return
job_destination = job_wrapper.job_destination
# Construction of the Kubernetes Job object follows: http://kubernetes.io/docs/user-guide/persistent-volumes/
k8s_job_name = self.__produce_unique_k8s_job_name(job_wrapper.get_id_tag())
k8s_job_obj = {
"apiVersion": self.runner_params['k8s_job_api_version'],
"kind": "Job",
"metadata": {
# metadata.name is the name of the pod resource created, and must be unique
# http://kubernetes.io/docs/user-guide/configuring-containers/
"name": k8s_job_name,
"namespace": "default", # TODO this should be set
"labels": {"app": k8s_job_name}
},
"spec": self.__get_k8s_job_spec(job_wrapper)
}
# Checks if job exists
job = Job(self._pykube_api, k8s_job_obj)
if job.exists():
job.delete()
# Creates the Kubernetes Job
# TODO if a job with that ID exists, what should we do?
# TODO do we trust that this is the same job and use that?
# TODO or create a new job as we cannot make sure
Job(self._pykube_api, k8s_job_obj).create()
# define job attributes in the AsyncronousJobState for follow-up
ajs = AsynchronousJobState(files_dir=job_wrapper.working_directory, job_wrapper=job_wrapper,
job_id=k8s_job_name, job_destination=job_destination)
self.monitor_queue.put(ajs)
# external_runJob_script can be None, in which case it's not used.
external_runjob_script = None
return external_runjob_script
def __get_pull_policy(self):
if "k8s_pull_policy" in self.runner_params:
if self.runner_params['k8s_pull_policy'] in ["Always", "IfNotPresent", "Never"]:
return self.runner_params['k8s_pull_policy']
return None
def __get_supplemental_group(self):
if "k8s_supplemental_group_id" in self.runner_params:
try:
return int(self.runner_params["k8s_supplemental_group_id"])
except Exception:
log.warning("Supplemental group passed for Kubernetes runner needs to be an integer, value "
+ self.runner_params["k8s_supplemental_group_id"] + " passed is invalid")
return None
return None
def __get_fs_group(self):
if "k8s_fs_group_id" in self.runner_params:
try:
return int(self.runner_params["k8s_fs_group_id"])
except Exception:
log.warning("FS group passed for Kubernetes runner needs to be an integer, value "
+ self.runner_params["k8s_fs_group_id"] + " passed is invalid")
return None
return None
def __produce_unique_k8s_job_name(self, galaxy_internal_job_id):
# wrapper.get_id_tag() instead of job_id for compatibility with TaskWrappers.
return "galaxy-" + galaxy_internal_job_id
def __get_k8s_job_spec(self, job_wrapper):
"""Creates the k8s Job spec. For a Job spec, the only requirement is to have a .spec.template."""
k8s_job_spec = {"template": self.__get_k8s_job_spec_template(job_wrapper)}
return k8s_job_spec
def __get_k8s_job_spec_template(self, job_wrapper):
"""The k8s spec template is nothing but a Pod spec, except that it is nested and does not have an apiversion
nor kind. In addition to required fields for a Pod, a pod template in a job must specify appropriate labels
(see pod selector) and an appropriate restart policy."""
k8s_spec_template = {
"metadata": {
"labels": {"app": self.__produce_unique_k8s_job_name(job_wrapper.get_id_tag())}
},
"spec": {
"volumes": self.__get_k8s_mountable_volumes(job_wrapper),
"restartPolicy": self.__get_k8s_restart_policy(job_wrapper),
"containers": self.__get_k8s_containers(job_wrapper)
}
}
# TODO include other relevant elements that people might want to use from
# TODO http://kubernetes.io/docs/api-reference/v1/definitions/#_v1_podspec
if self._supplemental_group and self._supplemental_group > 0:
k8s_spec_template["spec"]["securityContext"] = dict(supplementalGroups=[self._supplemental_group])
if self._fs_group and self._fs_group > 0:
if "securityContext" in k8s_spec_template["spec"]:
k8s_spec_template["spec"]["securityContext"]["fsGroup"] = self._fs_group
else:
k8s_spec_template["spec"]["securityContext"] = dict(fsGroup=self._fs_group)
return k8s_spec_template
def __get_k8s_restart_policy(self, job_wrapper):
"""The default Kubernetes restart policy for Jobs"""
return "Never"
def __get_k8s_mountable_volumes(self, job_wrapper):
"""Provides the required volumes that the containers in the pod should be able to mount. This should be using
the new persistent volumes and persistent volumes claim objects. This requires that both a PersistentVolume and
a PersistentVolumeClaim are created before starting galaxy (starting a k8s job).
"""
# TODO on this initial version we only support a single volume to be mounted.
k8s_mountable_volume = {
"name": self._galaxy_vol_name,
"persistentVolumeClaim": {
"claimName": self.runner_params['k8s_persistent_volume_claim_name']
}
}
return [k8s_mountable_volume]
def __get_k8s_containers(self, job_wrapper):
"""Fills in all required for setting up the docker containers to be used, including setting a pull policy if
this has been set.
"""
k8s_container = {
"name": self.__get_k8s_container_name(job_wrapper),
"image": self._find_container(job_wrapper).container_id,
# this form of command overrides the entrypoint and allows multi command
# command line execution, separated by ;, which is what Galaxy does
# to assemble the command.
# TODO possibly shell needs to be set by job_wrapper
"command": ["/bin/bash", "-c", job_wrapper.runner_command_line],
"workingDir": job_wrapper.working_directory,
"volumeMounts": [{
"mountPath": self.runner_params['k8s_persistent_volume_claim_mount_path'],
"name": self._galaxy_vol_name
}]
}
resources = self.__get_resources(job_wrapper)
if resources:
k8s_container['resources'] = resources
if self._default_pull_policy:
k8s_container["imagePullPolicy"] = self._default_pull_policy
# if self.__requires_ports(job_wrapper):
# k8s_container['ports'] = self.__get_k8s_containers_ports(job_wrapper)
return [k8s_container]
# def __get_k8s_containers_ports(self, job_wrapper):
# for k,v self.runner_params:
# if k.startswith("container_port_"):
def __get_resources(self, job_wrapper):
mem_request = self.__get_memory_request(job_wrapper)
cpu_request = self.__get_cpu_request(job_wrapper)
mem_limit = self.__get_memory_limit(job_wrapper)
cpu_limit = self.__get_cpu_limit(job_wrapper)
requests = {}
limits = {}
if mem_request:
requests['memory'] = mem_request
if cpu_request:
requests['cpu'] = cpu_request
if mem_limit:
limits['memory'] = mem_limit
if cpu_limit:
limits['cpu'] = cpu_limit
resources = {}
if requests:
resources['requests'] = requests
if limits:
resources['limits'] = limits
return resources
def __get_memory_request(self, job_wrapper):
"""Obtains memory requests for job, checking if available on the destination, otherwise using the default"""
job_destinantion = job_wrapper.job_destination
if 'requests_memory' in job_destinantion.params:
return self.__transform_memory_value(job_destinantion.params['requests_memory'])
return None
def __get_memory_limit(self, job_wrapper):
"""Obtains memory limits for job, checking if available on the destination, otherwise using the default"""
job_destinantion = job_wrapper.job_destination
if 'limits_memory' in job_destinantion.params:
return self.__transform_memory_value(job_destinantion.params['limits_memory'])
return None
def __get_cpu_request(self, job_wrapper):
"""Obtains cpu requests for job, checking if available on the destination, otherwise using the default"""
job_destinantion = job_wrapper.job_destination
if 'requests_cpu' in job_destinantion.params:
return self.__transform_cpu_value(job_destinantion.params['requests_cpu'])
return None
def __get_cpu_limit(self, job_wrapper):
"""Obtains cpu requests for job, checking if available on the destination, otherwise using the default"""
job_destinantion = job_wrapper.job_destination
if 'limits_cpu' in job_destinantion.params:
return self.__transform_cpu_value(job_destinantion.params['limits_cpu'])
return None
def __transform_cpu_value(self, cpu_value):
"""Transforms cpu value
If the value is 0 and not a string, then None is returned.
If the value is a float, then it is multiplied by 1000 and expressed as mili cpus.
If the value is an integer, then it is and expressed as CPUs (no unit).
If it is an already formatted string, it is returned as it was.
"""
if not isinstance(cpu_value, str) and float(cpu_value) == 0:
return None
if isinstance(cpu_value, float):
return str(int(cpu_value * 1000)) + "m"
elif isinstance(cpu_value, int):
return str(cpu_value)
return cpu_value
def __transform_memory_value(self, mem_value):
"""Transforms memory value
If the value is 0 and not a string, then None is returned.
If the value has a decimal part, then it is multiplied by 1000 and expressed as Megabytes.
If the value is an integer, then it is truncated and expressed as Gigabytes.
If it is an already formatted string, it is returned as it was.
"""
if not isinstance(mem_value, str) and float(mem_value) == 0:
return None
if isinstance(mem_value, float):
return str(int(mem_value * 1000)) + "M"
elif isinstance(mem_value, int):
return str(mem_value) + "G"
return mem_value
def __assemble_k8s_container_image_name(self, job_wrapper):
"""Assembles the container image name as repo/owner/image:tag, where repo, owner and tag are optional"""
job_destination = job_wrapper.job_destination
# Determine the job's Kubernetes destination (context, namespace) and options from the job destination
# definition
repo = ""
owner = ""
if 'repo' in job_destination.params:
repo = job_destination.params['repo'] + "/"
if 'owner' in job_destination.params:
owner = job_destination.params['owner'] + "/"
k8s_cont_image = repo + owner + job_destination.params['image']
if 'tag' in job_destination.params:
k8s_cont_image += ":" + job_destination.params['tag']
return k8s_cont_image
def __get_k8s_container_name(self, job_wrapper):
# These must follow a specific regex for Kubernetes.
raw_id = job_wrapper.job_destination.id
if isinstance(raw_id, str):
cleaned_id = re.sub("[^-a-z0-9]", "-", raw_id)
if cleaned_id.startswith("-") or cleaned_id.endswith("-"):
cleaned_id = "x%sx" % cleaned_id
return cleaned_id
return "job-container"
[docs] def check_watched_item(self, job_state):
"""Checks the state of a job already submitted on k8s. Job state is a AsynchronousJobState"""
jobs = Job.objects(self._pykube_api).filter(selector="app=" + job_state.job_id)
if len(jobs.response['items']) == 1:
job = Job(self._pykube_api, jobs.response['items'][0])
job_destination = job_state.job_wrapper.job_destination
succeeded = 0
active = 0
failed = 0
max_pod_retrials = 1
if 'k8s_pod_retrials' in self.runner_params:
max_pod_retrials = int(self.runner_params['k8s_pod_retrials'])
if 'max_pod_retrials' in job_destination.params:
max_pod_retrials = int(job_destination.params['max_pod_retrials'])
if 'succeeded' in job.obj['status']:
succeeded = job.obj['status']['succeeded']
if 'active' in job.obj['status']:
active = job.obj['status']['active']
if 'failed' in job.obj['status']:
failed = job.obj['status']['failed']
# This assumes jobs dependent on a single pod, single container
if succeeded > 0:
self.__produce_log_file(job_state)
error_file = open(job_state.error_file, 'w')
error_file.write("")
error_file.close()
job_state.running = False
self.mark_as_finished(job_state)
return None
elif failed > 0 and self.__job_failed_due_to_low_memory(job_state):
return self._handle_job_failure(job, job_state, reason="OOM")
elif active > 0 and failed <= max_pod_retrials:
job_state.running = True
return job_state
elif failed > max_pod_retrials:
return self._handle_job_failure(job, job_state)
# We should not get here
log.debug(
"Reaching unexpected point for Kubernetes job, where it is not classified as succ., active nor failed.")
return job_state
elif len(jobs.response['items']) == 0:
# there is no job responding to this job_id, it is either lost or something happened.
log.error("No Jobs are available under expected selector app=" + job_state.job_id)
error_file = open(job_state.error_file, 'w')
error_file.write("No Kubernetes Jobs are available under expected selector app=" + job_state.job_id + "\n")
error_file.close()
self.mark_as_failed(job_state)
return job_state
else:
# there is more than one job associated to the expected unique job id used as selector.
log.error("There is more than one Kubernetes Job associated to job id " + job_state.job_id)
self.__produce_log_file(job_state)
error_file = open(job_state.error_file, 'w')
error_file.write("There is more than one Kubernetes Job associated to job id " + job_state.job_id + "\n")
error_file.close()
self.mark_as_failed(job_state)
return job_state
def _handle_job_failure(self, job, job_state, reason=None):
self.__produce_log_file(job_state)
error_file = open(job_state.error_file, 'w')
if reason == "OOM":
error_file.write("Job killed after running out of memory. Try with more memory.\n")
job_state.fail_message = "Tool failed due to insufficient memory. Try with more memory."
job_state.runner_state = JobState.runner_states.MEMORY_LIMIT_REACHED
else:
error_file.write("Exceeded max number of Kubernetes pod retrials allowed for job\n")
job_state.fail_message = "More pods failed than allowed. See stdout for pods details."
error_file.close()
job_state.running = False
self.mark_as_failed(job_state)
job.scale(replicas=0)
return None
def __job_failed_due_to_low_memory(self, job_state):
"""
checks the state of the pod to see if it was killed
for being out of memory (pod status OOMKilled). If that is the case
marks the job for resubmission (resubmit logic is part of destinations).
"""
pods = Pod.objects(self._pykube_api).filter(selector="app=" + job_state.job_id)
pod = Pod(self._pykube_api, pods.response['items'][0])
if pod.obj['status']['phase'] == "Failed" and \
pod.obj['status']['containerStatuses'][0]['state']['terminated']['reason'] == "OOMKilled":
return True
return False
[docs] def fail_job(self, job_state):
"""
Kubernetes runner overrides fail_job (called by mark_as_failed) to rescue the pod's log files which are left as
stdout (pods logs are the natural stdout and stderr of the running processes inside the pods) and are
deleted in the parent implementation as part of the failing the job process.
:param job_state:
:return:
"""
# First we rescue the pods logs
with open(job_state.output_file, 'r') as outfile:
stdout_content = outfile.read()
if getattr(job_state, 'stop_job', True):
self.stop_job(self.sa_session.query(self.app.model.Job).get(job_state.job_wrapper.job_id))
self._handle_runner_state('failure', job_state)
# Not convinced this is the best way to indicate this state, but
# something necessary
if not job_state.runner_state_handled:
job_state.job_wrapper.fail(
message=getattr(job_state, 'fail_message', 'Job failed'),
stdout=stdout_content, stderr='See stdout for pod\'s stderr.'
)
if job_state.job_wrapper.cleanup_job == "always":
job_state.cleanup()
def __produce_log_file(self, job_state):
pod_r = Pod.objects(self._pykube_api).filter(selector="app=" + job_state.job_id)
logs = ""
for pod_obj in pod_r.response['items']:
try:
pod = Pod(self._pykube_api, pod_obj)
logs += "\n\n==== Pod " + pod.name + " log start ====\n\n"
logs += pod.logs(timestamps=True)
logs += "\n\n==== Pod " + pod.name + " log end ===="
except Exception as detail:
log.info("Could not write pod\'s " + pod_obj['metadata']['name'] +
" log file due to HTTPError " + str(detail))
logs_file_path = job_state.output_file
logs_file = open(logs_file_path, mode="w")
if isinstance(logs, text_type):
logs = logs.encode('utf8')
logs_file.write(logs)
logs_file.close()
return logs_file_path
[docs] def stop_job(self, job):
"""Attempts to delete a dispatched job to the k8s cluster"""
try:
jobs = Job.objects(self._pykube_api).filter(selector="app=" +
self.__produce_unique_k8s_job_name(job.get_id_tag()))
if len(jobs.response['items']) >= 0:
job_to_delete = Job(self._pykube_api, jobs.response['items'][0])
job_to_delete.scale(replicas=0)
# TODO assert whether job parallelism == 0
# assert not job_to_delete.exists(), "Could not delete job,"+job.job_runner_external_id+" it still exists"
log.debug("(%s/%s) Terminated at user's request" % (job.id, job.job_runner_external_id))
except Exception as e:
log.debug("(%s/%s) User killed running job, but error encountered during termination: %s" % (
job.id, job.job_runner_external_id, e))
[docs] def recover(self, job, job_wrapper):
"""Recovers jobs stuck in the queued/running state when Galaxy started"""
# TODO this needs to be implemented to override unimplemented base method
job_id = job.get_job_runner_external_id()
if job_id is None:
self.put(job_wrapper)
return
ajs = AsynchronousJobState(files_dir=job_wrapper.working_directory, job_wrapper=job_wrapper)
ajs.job_id = str(job_id)
ajs.command_line = job.command_line
ajs.job_wrapper = job_wrapper
ajs.job_destination = job_wrapper.job_destination
if job.state == model.Job.states.RUNNING:
log.debug("(%s/%s) is still in running state, adding to the runner monitor queue" % (
job.id, job.job_runner_external_id))
ajs.old_state = model.Job.states.RUNNING
ajs.running = True
self.monitor_queue.put(ajs)
elif job.state == model.Job.states.QUEUED:
log.debug("(%s/%s) is still in queued state, adding to the runner monitor queue" % (
job.id, job.job_runner_external_id))
ajs.old_state = model.Job.states.QUEUED
ajs.running = False
self.monitor_queue.put(ajs)