def test_format_cmd():
"""Test format_cmd."""
test_cmd = "ls -l"
test_cmd_fail = 12
assert isinstance(format_cmd(test_cmd), list)
with raises(ValueError):
format_cmd(test_cmd_fail)
def _create_job_spec(self, name, command=None, image=None,
env_vars=None):
"""Instantiate a Kubernetes job.
:param name: Name of the job.
:param image: Docker image to use to run the job on.
:param command: List of commands to run on the given job.
:param env_vars: List of environment variables (dictionaries) to
inject into the workflow engine container.
"""
image = image or self._workflow_engine_image()
command = command or self._workflow_engine_command()
workflow_engine_env_vars = env_vars or self._workflow_engine_env_vars()
job_controller_env_vars = []
owner_id = str(self.workflow.owner_id)
command = format_cmd(command)
workspace_mount, _ = get_shared_volume(
self.workflow.get_workspace(), SHARED_VOLUME_PATH
)
db_mount, _ = get_shared_volume(
'db', SHARED_VOLUME_PATH
)
workflow_metadata = client.V1ObjectMeta(name=name)
job = client.V1Job()
job.api_version = 'batch/v1'
job.kind = 'Job'
job.metadata = workflow_metadata
spec = client.V1JobSpec(
template=client.V1PodTemplateSpec())
spec.template.metadata = workflow_metadata
workflow_enginge_container = client.V1Container(
name=current_app.config['WORKFLOW_ENGINE_NAME'],
image=image,
image_pull_policy='IfNotPresent',
env=[],
volume_mounts=[],
command=['/bin/bash', '-c'],
args=command)
job_controller_address = [
{
'name': 'JOB_CONTROLLER_SERVICE_PORT_HTTP',
'value':
str(current_app.config['JOB_CONTROLLER_CONTAINER_PORT'])
},
{
'name': 'JOB_CONTROLLER_SERVICE_HOST',
'value': 'localhost'}
]
workflow_engine_env_vars.extend(job_controller_address)
workflow_enginge_container.env.extend(workflow_engine_env_vars)
workflow_enginge_container.security_context = \
client.V1SecurityContext(
run_as_group=WORKFLOW_RUNTIME_USER_GID,
run_as_user=WORKFLOW_RUNTIME_USER_UID
)
workflow_enginge_container.volume_mounts = [workspace_mount]
secrets_store = REANAUserSecretsStore(owner_id)
job_controller_env_secrets = secrets_store.\
get_env_secrets_as_k8s_spec()
user = \
secrets_store.get_secret_value('HTCONDORCERN_USERNAME') or \
WORKFLOW_RUNTIME_USER_NAME
job_controller_container = client.V1Container(
name=current_app.config['JOB_CONTROLLER_NAME'],
image=current_app.config['JOB_CONTROLLER_IMAGE'],
image_pull_policy='IfNotPresent',
env=[],
volume_mounts=[],
command=['/bin/bash', '-c'],
args=self._create_job_controller_startup_cmd(user),
ports=[])
if os.getenv('FLASK_ENV') == 'development':
job_controller_env_vars.extend(
current_app.config['DEBUG_ENV_VARS'])
job_controller_env_vars.extend([
{
'name': 'REANA_USER_ID',
'value': owner_id
}, {
'name': 'CERN_USER',
'value': user
}, {
'name': 'USER', # Required by HTCondor
'value': user
}
])
job_controller_container.env.extend(job_controller_env_vars)
job_controller_container.env.extend(job_controller_env_secrets)
job_controller_container.env.extend([
{
'name': 'REANA_SQLALCHEMY_DATABASE_URI',
'value': SQLALCHEMY_DATABASE_URI
},
{
'name': 'REANA_STORAGE_BACKEND',
'value': REANA_STORAGE_BACKEND
}
])
secrets_volume_mount = \
secrets_store.get_secrets_volume_mount_as_k8s_spec()
job_controller_container.volume_mounts = [workspace_mount, db_mount]
job_controller_container.volume_mounts.append(secrets_volume_mount)
job_controller_container.ports = [{
"containerPort":
current_app.config['JOB_CONTROLLER_CONTAINER_PORT']
}]
containers = [workflow_enginge_container, job_controller_container]
spec.template.spec = client.V1PodSpec(
containers=containers)
spec.template.spec.volumes = [
KubernetesWorkflowRunManager.k8s_shared_volume
[REANA_STORAGE_BACKEND],
secrets_store.get_file_secrets_volume_as_k8s_specs(),
]
job.spec = spec
job.spec.template.spec.restart_policy = 'Never'
job.spec.ttl_seconds_after_finished = TTL_SECONDS_AFTER_FINISHED
job.spec.backoff_limit = 0
return job
def _create_job_spec(
self,
name,
command=None,
image=None,
env_vars=None,
overwrite_input_parameters=None,
overwrite_operational_options=None,
):
"""Instantiate a Kubernetes job.
:param name: Name of the job.
:param image: Docker image to use to run the job on.
:param command: List of commands to run on the given job.
:param env_vars: List of environment variables (dictionaries) to
inject into the workflow engine container.
:param interactive_session_type: One of the available interactive
session types.
: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
"""
image = image or self._workflow_engine_image()
command = command or self._workflow_engine_command(
overwrite_input_parameters=overwrite_input_parameters,
overwrite_operational_options=overwrite_operational_options,
)
workflow_engine_env_vars = env_vars or self._workflow_engine_env_vars()
job_controller_env_vars = []
owner_id = str(self.workflow.owner_id)
command = format_cmd(command)
workspace_mount, workspace_volume = get_workspace_volume(
self.workflow.workspace_path)
db_mount, shared_volume = get_shared_volume("db")
workflow_metadata = client.V1ObjectMeta(
name=name,
labels={
"reana_workflow_mode": "batch",
"reana-run-batch-workflow-uuid": str(self.workflow.id_),
},
namespace=REANA_RUNTIME_KUBERNETES_NAMESPACE,
)
secrets_store = REANAUserSecretsStore(owner_id)
kerberos = None
if self.requires_kerberos():
kerberos = get_kerberos_k8s_config(
secrets_store,
kubernetes_uid=WORKFLOW_RUNTIME_USER_UID,
)
job = client.V1Job()
job.api_version = "batch/v1"
job.kind = "Job"
job.metadata = workflow_metadata
spec = client.V1JobSpec(template=client.V1PodTemplateSpec())
spec.template.metadata = workflow_metadata
workflow_engine_container = client.V1Container(
name=current_app.config["WORKFLOW_ENGINE_NAME"],
image=image,
image_pull_policy="IfNotPresent",
env=[],
volume_mounts=[],
command=["/bin/bash", "-c"],
args=command,
)
workflow_engine_env_vars.extend([
{
"name": "REANA_JOB_CONTROLLER_SERVICE_PORT_HTTP",
"value":
str(current_app.config["JOB_CONTROLLER_CONTAINER_PORT"]),
},
{
"name": "REANA_JOB_CONTROLLER_SERVICE_HOST",
"value": "localhost"
},
{
"name": "REANA_COMPONENT_PREFIX",
"value": REANA_COMPONENT_PREFIX
},
{
"name": "REANA_COMPONENT_NAMING_SCHEME",
"value": REANA_COMPONENT_NAMING_SCHEME,
},
{
"name": "REANA_INFRASTRUCTURE_KUBERNETES_NAMESPACE",
"value": REANA_INFRASTRUCTURE_KUBERNETES_NAMESPACE,
},
{
"name": "REANA_RUNTIME_KUBERNETES_NAMESPACE",
"value": REANA_RUNTIME_KUBERNETES_NAMESPACE,
},
{
"name": "REANA_JOB_CONTROLLER_CONNECTION_CHECK_SLEEP",
"value": str(REANA_JOB_CONTROLLER_CONNECTION_CHECK_SLEEP),
},
])
workflow_engine_container.env.extend(workflow_engine_env_vars)
workflow_engine_container.security_context = client.V1SecurityContext(
run_as_group=WORKFLOW_RUNTIME_USER_GID,
run_as_user=WORKFLOW_RUNTIME_USER_UID,
)
workflow_engine_container.volume_mounts = [workspace_mount]
if kerberos:
workflow_engine_container.volume_mounts += kerberos.volume_mounts
workflow_engine_container.env += kerberos.env
job_controller_env_secrets = secrets_store.get_env_secrets_as_k8s_spec(
)
user = secrets_store.get_secret_value(
"CERN_USER") or WORKFLOW_RUNTIME_USER_NAME
job_controller_container = client.V1Container(
name=current_app.config["JOB_CONTROLLER_NAME"],
image=current_app.config["JOB_CONTROLLER_IMAGE"],
image_pull_policy="IfNotPresent",
env=[],
volume_mounts=[],
command=["/bin/bash", "-c"],
args=self._create_job_controller_startup_cmd(user),
ports=[],
)
job_controller_env_vars.extend([
{
"name": "REANA_USER_ID",
"value": owner_id
},
{
"name": "CERN_USER",
"value": user
},
{
"name": "USER",
"value": user
}, # Required by HTCondor
{
"name": "K8S_CERN_EOS_AVAILABLE",
"value": K8S_CERN_EOS_AVAILABLE
},
{
"name": "IMAGE_PULL_SECRETS",
"value": ",".join(IMAGE_PULL_SECRETS)
},
{
"name": "REANA_SQLALCHEMY_DATABASE_URI",
"value": SQLALCHEMY_DATABASE_URI,
},
{
"name": "REANA_STORAGE_BACKEND",
"value": REANA_STORAGE_BACKEND
},
{
"name": "REANA_COMPONENT_PREFIX",
"value": REANA_COMPONENT_PREFIX
},
{
"name": "REANA_COMPONENT_NAMING_SCHEME",
"value": REANA_COMPONENT_NAMING_SCHEME,
},
{
"name": "REANA_INFRASTRUCTURE_KUBERNETES_NAMESPACE",
"value": REANA_INFRASTRUCTURE_KUBERNETES_NAMESPACE,
},
{
"name": "REANA_RUNTIME_KUBERNETES_NAMESPACE",
"value": REANA_RUNTIME_KUBERNETES_NAMESPACE,
},
{
"name": "REANA_JOB_HOSTPATH_MOUNTS",
"value": json.dumps(REANA_JOB_HOSTPATH_MOUNTS),
},
{
"name":
"REANA_RUNTIME_KUBERNETES_KEEP_ALIVE_JOBS_WITH_STATUSES",
"value":
",".join(
REANA_RUNTIME_KUBERNETES_KEEP_ALIVE_JOBS_WITH_STATUSES),
},
{
"name": "REANA_KUBERNETES_JOBS_MEMORY_LIMIT",
"value": REANA_KUBERNETES_JOBS_MEMORY_LIMIT,
},
{
"name": "REANA_KUBERNETES_JOBS_MAX_USER_MEMORY_LIMIT",
"value": REANA_KUBERNETES_JOBS_MAX_USER_MEMORY_LIMIT,
},
{
"name": "REANA_KUBERNETES_JOBS_TIMEOUT_LIMIT",
"value": REANA_KUBERNETES_JOBS_TIMEOUT_LIMIT,
},
{
"name": "REANA_KUBERNETES_JOBS_MAX_USER_TIMEOUT_LIMIT",
"value": REANA_KUBERNETES_JOBS_MAX_USER_TIMEOUT_LIMIT,
},
{
"name": "WORKSPACE_PATHS",
"value": json.dumps(WORKSPACE_PATHS)
},
])
job_controller_container.env.extend(job_controller_env_vars)
job_controller_container.env.extend(job_controller_env_secrets)
if REANA_RUNTIME_JOBS_KUBERNETES_NODE_LABEL:
job_controller_container.env.append(
{
"name": "REANA_RUNTIME_JOBS_KUBERNETES_NODE_LABEL",
"value":
os.getenv("REANA_RUNTIME_JOBS_KUBERNETES_NODE_LABEL"),
}, )
secrets_volume_mount = secrets_store.get_secrets_volume_mount_as_k8s_spec(
)
job_controller_container.volume_mounts = [workspace_mount, db_mount]
job_controller_container.volume_mounts.append(secrets_volume_mount)
job_controller_container.ports = [{
"containerPort":
current_app.config["JOB_CONTROLLER_CONTAINER_PORT"]
}]
containers = [workflow_engine_container, job_controller_container]
spec.template.spec = client.V1PodSpec(
containers=containers,
node_selector=REANA_RUNTIME_BATCH_KUBERNETES_NODE_LABEL,
init_containers=[],
)
spec.template.spec.service_account_name = (
REANA_RUNTIME_KUBERNETES_SERVICEACCOUNT_NAME)
volumes = [
workspace_volume,
shared_volume,
secrets_store.get_file_secrets_volume_as_k8s_specs(),
]
if kerberos:
volumes += kerberos.volumes
spec.template.spec.init_containers.append(kerberos.init_container)
# filter out volumes with the same name
spec.template.spec.volumes = list({v["name"]: v
for v in volumes}.values())
if os.getenv("FLASK_ENV") == "development":
code_volume_name = "reana-code"
code_mount_path = "/code"
k8s_code_volume = client.V1Volume(name=code_volume_name)
k8s_code_volume.host_path = client.V1HostPathVolumeSource(
code_mount_path)
spec.template.spec.volumes.append(k8s_code_volume)
for container in spec.template.spec.containers:
container.env.extend(current_app.config["DEBUG_ENV_VARS"])
sub_path = f"reana-{container.name}"
if container.name == "workflow-engine":
sub_path += f"-{self.workflow.type_}"
container.volume_mounts.append({
"name": code_volume_name,
"mountPath": code_mount_path,
"subPath": sub_path,
})
job.spec = spec
job.spec.template.spec.restart_policy = "Never"
job.spec.backoff_limit = 0
return job
def _create_job_spec(self,
name,
command=None,
image=None,
env_vars=None,
overwrite_input_parameters=None,
overwrite_operational_options=None):
"""Instantiate a Kubernetes job.
:param name: Name of the job.
:param image: Docker image to use to run the job on.
:param command: List of commands to run on the given job.
:param env_vars: List of environment variables (dictionaries) to
inject into the workflow engine container.
:param interactive_session_type: One of the available interactive
session types.
: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
"""
image = image or self._workflow_engine_image()
command = command or self._workflow_engine_command(
overwrite_input_parameters=overwrite_input_parameters,
overwrite_operational_options=overwrite_operational_options)
workflow_engine_env_vars = env_vars or self._workflow_engine_env_vars()
job_controller_env_vars = []
owner_id = str(self.workflow.owner_id)
command = format_cmd(command)
workspace_mount, workspace_volume = \
get_shared_volume(self.workflow.workspace_path)
db_mount, _ = get_shared_volume('db')
workflow_metadata = client.V1ObjectMeta(
name=name, labels={'reana_workflow_mode': 'batch'})
job = client.V1Job()
job.api_version = 'batch/v1'
job.kind = 'Job'
job.metadata = workflow_metadata
spec = client.V1JobSpec(template=client.V1PodTemplateSpec())
spec.template.metadata = workflow_metadata
workflow_engine_container = client.V1Container(
name=current_app.config['WORKFLOW_ENGINE_NAME'],
image=image,
image_pull_policy='IfNotPresent',
env=[],
volume_mounts=[],
command=['/bin/bash', '-c'],
args=command)
job_controller_address = [{
'name':
'REANA_JOB_CONTROLLER_SERVICE_PORT_HTTP',
'value':
str(current_app.config['JOB_CONTROLLER_CONTAINER_PORT'])
}, {
'name': 'REANA_JOB_CONTROLLER_SERVICE_HOST',
'value': 'localhost'
}]
workflow_engine_env_vars.extend(job_controller_address)
workflow_engine_container.env.extend(workflow_engine_env_vars)
workflow_engine_container.security_context = \
client.V1SecurityContext(
run_as_group=WORKFLOW_RUNTIME_USER_GID,
run_as_user=WORKFLOW_RUNTIME_USER_UID
)
workflow_engine_container.volume_mounts = [workspace_mount]
secrets_store = REANAUserSecretsStore(owner_id)
job_controller_env_secrets = secrets_store.\
get_env_secrets_as_k8s_spec()
user = \
secrets_store.get_secret_value('CERN_USER') or \
WORKFLOW_RUNTIME_USER_NAME
job_controller_container = client.V1Container(
name=current_app.config['JOB_CONTROLLER_NAME'],
image=current_app.config['JOB_CONTROLLER_IMAGE'],
image_pull_policy='IfNotPresent',
env=[],
volume_mounts=[],
command=['/bin/bash', '-c'],
args=self._create_job_controller_startup_cmd(user),
ports=[])
job_controller_env_vars.extend([
{
'name': 'REANA_USER_ID',
'value': owner_id
},
{
'name': 'CERN_USER',
'value': user
},
{
'name': 'USER', # Required by HTCondor
'value': user
},
{
'name': 'K8S_CERN_EOS_AVAILABLE',
'value': K8S_CERN_EOS_AVAILABLE
},
{
'name': 'IMAGE_PULL_SECRETS',
'value': ','.join(IMAGE_PULL_SECRETS)
}
])
job_controller_container.env.extend(job_controller_env_vars)
job_controller_container.env.extend(job_controller_env_secrets)
job_controller_container.env.extend([{
'name': 'REANA_SQLALCHEMY_DATABASE_URI',
'value': SQLALCHEMY_DATABASE_URI
}, {
'name': 'REANA_STORAGE_BACKEND',
'value': REANA_STORAGE_BACKEND
}])
secrets_volume_mount = \
secrets_store.get_secrets_volume_mount_as_k8s_spec()
job_controller_container.volume_mounts = [workspace_mount, db_mount]
job_controller_container.volume_mounts.append(secrets_volume_mount)
job_controller_container.ports = [{
"containerPort":
current_app.config['JOB_CONTROLLER_CONTAINER_PORT']
}]
containers = [workflow_engine_container, job_controller_container]
spec.template.spec = client.V1PodSpec(containers=containers)
spec.template.spec.service_account_name = \
K8S_REANA_SERVICE_ACCOUNT_NAME
spec.template.spec.volumes = [
workspace_volume,
secrets_store.get_file_secrets_volume_as_k8s_specs(),
]
if os.getenv('FLASK_ENV') == 'development':
code_volume_name = 'reana-code'
code_mount_path = '/code'
k8s_code_volume = client.V1Volume(name=code_volume_name)
k8s_code_volume.host_path = client.V1HostPathVolumeSource(
code_mount_path)
spec.template.spec.volumes.append(k8s_code_volume)
for container in spec.template.spec.containers:
container.env.extend(current_app.config['DEBUG_ENV_VARS'])
sub_path = f'reana-{container.name}'
if container.name == 'workflow-engine':
sub_path += f'-{self.workflow.type_}'
container.volume_mounts.append({
'name': code_volume_name,
'mountPath': code_mount_path,
'subPath': sub_path
})
job.spec = spec
job.spec.template.spec.restart_policy = 'Never'
job.spec.ttl_seconds_after_finished = TTL_SECONDS_AFTER_FINISHED
job.spec.backoff_limit = 0
return job