def _create_deployment_environment(self, deployment, deployment_plan, now):
deployment_env_creation_task_id = str(uuid.uuid4())
wf_id = 'create_deployment_environment'
deployment_env_creation_task_name = \
'cloudify_system_workflows.deployment_environment.create'
context = self._build_context_from_deployment(
deployment, deployment_env_creation_task_id, wf_id,
deployment_env_creation_task_name)
kwargs = {
DEPLOYMENT_PLUGINS_TO_INSTALL: deployment_plan[
DEPLOYMENT_PLUGINS_TO_INSTALL],
'workflow_plugins_to_install': deployment_plan[
'workflow_plugins_to_install'],
'policy_configuration': {
'policy_types': deployment_plan['policy_types'],
'policy_triggers': deployment_plan['policy_triggers'],
'groups': deployment_plan['groups'],
},
'__cloudify_context': context
}
new_execution = models.Execution(
id=deployment_env_creation_task_id,
status=models.Execution.PENDING,
created_at=now,
blueprint_id=deployment.blueprint_id,
workflow_id=wf_id,
deployment_id=deployment.id,
error='',
parameters=self._get_only_user_execution_parameters(kwargs))
get_storage_manager().put_execution(new_execution.id, new_execution)
celery_client().execute_task(
deployment_env_creation_task_name,
'cloudify.management',
deployment_env_creation_task_id,
kwargs=kwargs)
def _create_deployment_environment(self, deployment, deployment_plan, now):
deployment_env_creation_task_id = str(uuid.uuid4())
wf_id = 'create_deployment_environment'
deployment_env_creation_task_name = \
'system_workflows.deployment_environment.create'
context = self._build_context_from_deployment(
deployment, deployment_env_creation_task_id, wf_id,
deployment_env_creation_task_name)
kwargs = {
'management_plugins_to_install':
deployment_plan['management_plugins_to_install'],
'workflow_plugins_to_install':
deployment_plan['workflow_plugins_to_install'],
'policy_configuration': {
'policy_types': deployment_plan['policy_types'],
'policy_triggers': deployment_plan['policy_triggers'],
'groups': deployment_plan['groups'],
},
'__cloudify_context':
context
}
new_execution = models.Execution(
id=deployment_env_creation_task_id,
status=models.Execution.PENDING,
created_at=now,
blueprint_id=deployment.blueprint_id,
workflow_id=wf_id,
deployment_id=deployment.id,
error='',
parameters=self._get_only_user_execution_parameters(kwargs))
get_storage_manager().put_execution(new_execution.id, new_execution)
celery_client().execute_task(deployment_env_creation_task_name,
'cloudify.management',
deployment_env_creation_task_id,
kwargs=kwargs)
def _delete_deployment_environment(self, deployment_id):
deployment = get_storage_manager().get_deployment(deployment_id)
deployment_env_deletion_task_id = str(uuid.uuid4())
wf_id = 'delete_deployment_environment'
deployment_env_deletion_task_name = \
'cloudify_system_workflows.deployment_environment.delete'
context = self._build_context_from_deployment(
deployment,
deployment_env_deletion_task_id,
wf_id,
deployment_env_deletion_task_name)
kwargs = {'__cloudify_context': context}
new_execution = models.Execution(
id=deployment_env_deletion_task_id,
status=models.Execution.PENDING,
created_at=str(datetime.now()),
blueprint_id=deployment.blueprint_id,
workflow_id=wf_id,
deployment_id=deployment_id,
error='',
parameters=self._get_only_user_execution_parameters(kwargs))
get_storage_manager().put_execution(new_execution.id, new_execution)
deployment_env_deletion_task_async_result = \
celery_client().execute_task(
deployment_env_deletion_task_name,
'cloudify.management',
deployment_env_deletion_task_id,
kwargs=kwargs)
# wait for deployment environment deletion to complete
deployment_env_deletion_task_async_result.get(timeout=300,
propagate=True)
# verify deployment environment deletion completed successfully
execution = get_storage_manager().get_execution(
deployment_env_deletion_task_id)
if execution.status != models.Execution.TERMINATED:
raise RuntimeError('Failed to delete environment for deployment '
'{0}'.format(deployment_id))
def _delete_deployment_environment(self, deployment_id):
deployment = get_storage_manager().get_deployment(deployment_id)
deployment_env_deletion_task_id = str(uuid.uuid4())
wf_id = 'delete_deployment_environment'
deployment_env_deletion_task_name = \
'system_workflows.deployment_environment.delete'
context = self._build_context_from_deployment(
deployment, deployment_env_deletion_task_id, wf_id,
deployment_env_deletion_task_name)
kwargs = {'__cloudify_context': context}
new_execution = models.Execution(
id=deployment_env_deletion_task_id,
status=models.Execution.PENDING,
created_at=str(datetime.now()),
blueprint_id=deployment.blueprint_id,
workflow_id=wf_id,
deployment_id=deployment_id,
error='',
parameters=self._get_only_user_execution_parameters(kwargs))
get_storage_manager().put_execution(new_execution.id, new_execution)
deployment_env_deletion_task_async_result = \
celery_client().execute_task(
deployment_env_deletion_task_name,
'cloudify.management',
deployment_env_deletion_task_id,
kwargs=kwargs)
# wait for deployment environment deletion to complete
deployment_env_deletion_task_async_result.get(timeout=300,
propagate=True)
# verify deployment environment deletion completed successfully
execution = get_storage_manager().get_execution(
deployment_env_deletion_task_id)
if execution.status != models.Execution.TERMINATED:
raise RuntimeError('Failed to delete environment for deployment '
'{0}'.format(deployment_id))
def _verify_deployment_environment_created_successfully(self,
deployment_id,
is_retry=False):
deployment_env_creation_execution = next(
(execution for execution in
get_storage_manager().executions_list(
deployment_id=deployment_id) if execution.workflow_id ==
'create_deployment_environment'),
None)
if not deployment_env_creation_execution:
raise RuntimeError('Failed to find "create_deployment_environment"'
' execution for deployment {0}'.format(
deployment_id))
# Because of ES eventual consistency, we need to get the execution by
# its id in order to make sure the read status is correct.
deployment_env_creation_execution = \
get_storage_manager().get_execution(
deployment_env_creation_execution.id)
if deployment_env_creation_execution.status == \
models.Execution.TERMINATED:
# deployment environment creation is complete
return
elif deployment_env_creation_execution.status == \
models.Execution.STARTED:
# deployment environment creation is still in process
raise manager_exceptions\
.DeploymentEnvironmentCreationInProgressError(
'Deployment environment creation is still in progress, '
'try again in a minute')
elif deployment_env_creation_execution.status == \
models.Execution.FAILED:
# deployment environment creation execution failed
raise RuntimeError(
"Can't launch executions since environment creation for "
"deployment {0} has failed: {1}".format(
deployment_id, deployment_env_creation_execution.error))
elif deployment_env_creation_execution.status in (
models.Execution.CANCELLED, models.Execution.CANCELLING,
models.Execution.FORCE_CANCELLING):
# deployment environment creation execution got cancelled
raise RuntimeError(
"Can't launch executions since the environment creation for "
"deployment {0} has been cancelled [status={1}]".format(
deployment_id, deployment_env_creation_execution.status))
# status is 'pending'. Waiting for a few seconds and retrying to
# verify (to avoid eventual consistency issues). If this is already a
# failed retry, it might mean there was a problem with the Celery task
if not is_retry:
time.sleep(5)
self._verify_deployment_environment_created_successfully(
deployment_id, True)
else:
# deployment environment creation failed but not on the workflow
# level - retrieving the celery task's status for the error
# message, and the error object from celery if one is available
celery_task_status = celery_client().get_task_status(
deployment_env_creation_execution.id)
error_message = \
"Can't launch executions since environment for deployment {" \
"0} hasn't been created (Execution status is still '{1}'). " \
"Celery task status is ".format(
deployment_id, deployment_env_creation_execution.status)
if celery_task_status != CELERY_TASK_STATE_FAILURE:
raise RuntimeError(
"{0} {1}".format(error_message, celery_task_status))
else:
celery_error = celery_client().get_failed_task_error(
deployment_env_creation_execution.id)
raise RuntimeError(
"{0} {1}; Error is of type {2}; Error message: {3}"
.format(error_message, celery_task_status,
celery_error.__class__.__name__, celery_error))
def _verify_deployment_environment_created_successfully(
self, deployment_id, is_retry=False):
deployment_env_creation_execution = next(
(execution for execution in get_storage_manager().executions_list(
deployment_id=deployment_id)
if execution.workflow_id == 'create_deployment_environment'),
None)
if not deployment_env_creation_execution:
raise RuntimeError(
'Failed to find "create_deployment_environment"'
' execution for deployment {0}'.format(deployment_id))
# Because of ES eventual consistency, we need to get the execution by
# its id in order to make sure the read status is correct.
deployment_env_creation_execution = \
get_storage_manager().get_execution(
deployment_env_creation_execution.id)
if deployment_env_creation_execution.status == \
models.Execution.TERMINATED:
# deployment environment creation is complete
return
elif deployment_env_creation_execution.status == \
models.Execution.STARTED:
# deployment environment creation is still in process
raise manager_exceptions\
.DeploymentEnvironmentCreationInProgressError(
'Deployment environment creation is still in progress, '
'try again in a minute')
elif deployment_env_creation_execution.status == \
models.Execution.FAILED:
# deployment environment creation execution failed
raise RuntimeError(
"Can't launch executions since environment creation for "
"deployment {0} has failed: {1}".format(
deployment_id, deployment_env_creation_execution.error))
elif deployment_env_creation_execution.status in (
models.Execution.CANCELLED, models.Execution.CANCELLING,
models.Execution.FORCE_CANCELLING):
# deployment environment creation execution got cancelled
raise RuntimeError(
"Can't launch executions since the environment creation for "
"deployment {0} has been cancelled [status={1}]".format(
deployment_id, deployment_env_creation_execution.status))
# status is 'pending'. Waiting for a few seconds and retrying to
# verify (to avoid eventual consistency issues). If this is already a
# failed retry, it might mean there was a problem with the Celery task
if not is_retry:
time.sleep(5)
self._verify_deployment_environment_created_successfully(
deployment_id, True)
else:
# deployment environment creation failed but not on the workflow
# level - retrieving the celery task's status for the error
# message, and the error object from celery if one is available
celery_task_status = celery_client().get_task_status(
deployment_env_creation_execution.id)
error_message = \
"Can't launch executions since environment for deployment {" \
"0} hasn't been created (Execution status is still '{1}'). " \
"Celery task status is ".format(
deployment_id, deployment_env_creation_execution.status)
if celery_task_status != CELERY_TASK_STATE_FAILURE:
raise RuntimeError("{0} {1}".format(error_message,
celery_task_status))
else:
celery_error = celery_client().get_failed_task_error(
deployment_env_creation_execution.id)
raise RuntimeError(
"{0} {1}; Error is of type {2}; Error message: {3}".format(
error_message, celery_task_status,
celery_error.__class__.__name__, celery_error))
