def start_batch_workflow_run(self,
overwrite_input_params=None,
overwrite_operational_options=None):
"""Start a batch workflow run.
:param overwrite_input_params: Dictionary with parameters to be
overwritten or added to the current workflow run.
:param type: Dict
:param overwrite_operational_options: Dictionary with operational
options to be overwritten or added to the current workflow run.
:param type: Dict
"""
workflow_run_name = self._workflow_run_name_generator('batch')
job = self._create_job_spec(
workflow_run_name,
overwrite_input_parameters=overwrite_input_params,
overwrite_operational_options=overwrite_operational_options)
try:
current_k8s_batchv1_api_client.create_namespaced_job(
namespace=KubernetesWorkflowRunManager.default_namespace,
body=job)
except ApiException as e:
msg = 'Workflow engine/job controller pod ' \
'creation failed {}'.format(e)
logging.error(msg, exc_info=True)
raise e
def start_batch_workflow_run(self,
overwrite_input_params=None,
overwrite_operational_options=None):
"""Start a batch workflow run.
:param overwrite_input_params: Dictionary with parameters to be
overwritten or added to the current workflow run.
:param type: Dict
:param overwrite_operational_options: Dictionary with operational
options to be overwritten or added to the current workflow run.
:param type: Dict
"""
workflow_run_name = self._workflow_run_name_generator("batch")
job = self._create_job_spec(
workflow_run_name,
overwrite_input_parameters=overwrite_input_params,
overwrite_operational_options=overwrite_operational_options,
)
try:
current_k8s_batchv1_api_client.create_namespaced_job(
namespace=REANA_RUNTIME_KUBERNETES_NAMESPACE, body=job)
except ApiException as e:
msg = "Workflow engine/job controller pod " "creation failed {}".format(
e)
logging.error(msg, exc_info=True)
raise e
def start_batch_workflow_run(self):
"""Start a batch workflow run."""
workflow_run_name = self._workflow_run_name_generator('batch')
job = self._create_job_spec(workflow_run_name)
current_k8s_batchv1_api_client.create_namespaced_job(
namespace=KubernetesWorkflowRunManager.default_namespace,
body=job)
def _submit(self):
"""Submit job and return its backend id."""
try:
current_k8s_batchv1_api_client.create_namespaced_job(
namespace=REANA_RUNTIME_KUBERNETES_NAMESPACE, body=self.job
)
return self.job["metadata"]["name"]
except ApiException as e:
logging.error("Error while connecting to Kubernetes" " API: {}".format(e))
except Exception as e:
logging.error(traceback.format_exc())
logging.debug("Unexpected error: {}".format(e))
def start_batch_workflow_run(self):
"""Start a batch workflow run."""
workflow_run_name = self._workflow_run_name_generator('batch')
job = self._create_job_spec(workflow_run_name)
try:
current_k8s_batchv1_api_client.create_namespaced_job(
namespace=KubernetesWorkflowRunManager.default_namespace,
body=job)
except ApiException as e:
msg = 'Workflow engine/job controller pod ' \
'creation failed {}'.format(e)
logging.error(msg, exc_info=True)
raise REANAWorkflowControllerError(e)
def _submit(self):
"""Submit job and return its backend id."""
try:
api_response = \
current_k8s_batchv1_api_client.create_namespaced_job(
namespace=K8S_DEFAULT_NAMESPACE,
body=self.job)
return self.job['metadata']['name']
except ApiException as e:
logging.error("Error while connecting to Kubernetes"
" API: {}".format(e))
except Exception as e:
logging.error(traceback.format_exc())
logging.debug("Unexpected error: {}".format(e))
def execute(self):
"""Execute a job in Kubernetes."""
backend_job_id = str(uuid.uuid4())
job = {
'kind': 'Job',
'apiVersion': 'batch/v1',
'metadata': {
'name': backend_job_id,
'namespace': K8S_DEFAULT_NAMESPACE
},
'spec': {
'backoffLimit': MAX_JOB_RESTARTS,
'autoSelector': True,
'template': {
'metadata': {
'name': backend_job_id
},
'spec': {
'containers': [
{
'image': self.docker_img,
'command': self.cmd,
'name': backend_job_id,
'env': [],
'volumeMounts': []
},
],
'volumes': [],
'restartPolicy':
'Never'
}
}
}
}
if self.env_vars:
for var, value in self.env_vars.items():
job['spec']['template']['spec']['containers'][0]['env'].append(
{
'name': var,
'value': value
})
if self.shared_file_system:
self.add_shared_volume(job)
if self.cvmfs_mounts != 'false':
cvmfs_map = {}
for cvmfs_mount_path in ast.literal_eval(self.cvmfs_mounts):
if cvmfs_mount_path in CVMFS_REPOSITORIES:
cvmfs_map[
CVMFS_REPOSITORIES[cvmfs_mount_path]] = \
cvmfs_mount_path
for repository, mount_path in cvmfs_map.items():
volume = get_k8s_cvmfs_volume(repository)
(job['spec']['template']['spec']['containers'][0]
['volumeMounts'].append({
'name':
volume['name'],
'mountPath':
'/cvmfs/{}'.format(mount_path)
}))
job['spec']['template']['spec']['volumes'].append(volume)
# add better handling
try:
api_response = \
current_k8s_batchv1_api_client.create_namespaced_job(
namespace=K8S_DEFAULT_NAMESPACE, body=job)
return backend_job_id
except ApiException as e:
logging.debug("Error while connecting to Kubernetes"
" API: {}".format(e))
except Exception as e:
logging.error(traceback.format_exc())
logging.debug("Unexpected error: {}".format(e))
def k8s_instantiate_job(job_id,
workflow_workspace,
docker_img,
cmd,
cvmfs_mounts,
env_vars,
shared_file_system,
job_type,
namespace='default'):
"""Create Kubernetes job.
:param job_id: Job uuid.
:param workflow_workspace: Absolute path to the job's workflow workspace.
:param docker_img: Docker image to run the job.
:param cmd: Command provided to the docker container.
:param cvmfs_mounts: List of CVMFS volumes to mount in job pod.
:param env_vars: Dictionary representing environment variables
as {'var_name': 'var_value'}.
:param namespace: Job's namespace.
:shared_file_system: Boolean which represents whether the job
should have a shared file system mounted.
:returns: A :class:`kubernetes.client.models.v1_job.V1Job` corresponding
to the created job, None if the creation could not take place.
"""
job = {
'kind': 'Job',
'apiVersion': 'batch/v1',
'metadata': {
'name': job_id,
'namespace': namespace
},
'spec': {
'backoffLimit': app.config['MAX_JOB_RESTARTS'],
'autoSelector': True,
'template': {
'metadata': {
'name': job_id
},
'spec': {
'containers': [
{
'name': job_id,
'image': docker_img,
'env': [],
'volumeMounts': []
},
],
'volumes': [],
'restartPolicy':
'Never'
}
}
}
}
if cmd:
import shlex
(job['spec']['template']['spec']['containers'][0]['command']
) = shlex.split(cmd)
if env_vars:
for var, value in env_vars.items():
job['spec']['template']['spec']['containers'][0]['env'].append({
'name':
var,
'value':
value
})
if shared_file_system:
add_shared_volume(job, workflow_workspace)
if cvmfs_mounts != 'false':
cvmfs_map = {}
for cvmfs_mount_path in ast.literal_eval(cvmfs_mounts):
if cvmfs_mount_path in CVMFS_REPOSITORIES:
cvmfs_map[
CVMFS_REPOSITORIES[cvmfs_mount_path]] = cvmfs_mount_path
for repository, mount_path in cvmfs_map.items():
volume = get_k8s_cvmfs_volume(repository)
(job['spec']['template']['spec']['containers'][0]
['volumeMounts'].append({
'name':
volume['name'],
'mountPath':
'/cvmfs/{}'.format(mount_path)
}))
job['spec']['template']['spec']['volumes'].append(volume)
# add better handling
try:
api_response = \
current_k8s_batchv1_api_client.create_namespaced_job(
namespace=namespace, body=job)
return api_response
except client.rest.ApiException as e:
logging.debug("Error while connecting to Kubernetes API: {}".format(e))
except Exception as e:
logging.error(traceback.format_exc())
logging.debug("Unexpected error: {}".format(e))
