def delete(self, deployment_pb):
try:
logger.debug('Deleting AWS Lambda deployment')
deployment_spec = deployment_pb.spec
lambda_deployment_config = deployment_spec.aws_lambda_operator_config
lambda_deployment_config.region = (lambda_deployment_config.region
or get_default_aws_region())
if not lambda_deployment_config.region:
raise InvalidArgument('AWS region is missing')
cf_client = boto3.client('cloudformation',
lambda_deployment_config.region)
stack_name = generate_aws_compatible_string(
deployment_pb.namespace, deployment_pb.name)
if deployment_pb.state.info_json:
deployment_info_json = json.loads(
deployment_pb.state.info_json)
bucket_name = deployment_info_json.get('s3_bucket')
if bucket_name:
_cleanup_s3_bucket_if_exist(
bucket_name, lambda_deployment_config.region)
logger.debug(
'Deleting AWS CloudFormation: %s that includes Lambda function '
'and related resources',
stack_name,
)
cf_client.delete_stack(StackName=stack_name)
return DeleteDeploymentResponse(status=Status.OK())
except BentoMLException as error:
return DeleteDeploymentResponse(status=error.status_proto)
def add(self, deployment_pb):
try:
deployment_spec = deployment_pb.spec
deployment_spec.aws_lambda_operator_config.region = (
deployment_spec.aws_lambda_operator_config.region
or get_default_aws_region())
if not deployment_spec.aws_lambda_operator_config.region:
raise InvalidArgument('AWS region is missing')
ensure_sam_available_or_raise()
ensure_docker_available_or_raise()
bento_pb = self.yatai_service.GetBento(
GetBentoRequest(
bento_name=deployment_spec.bento_name,
bento_version=deployment_spec.bento_version,
))
if bento_pb.bento.uri.type not in (BentoUri.LOCAL, BentoUri.S3):
raise BentoMLException(
'BentoML currently not support {} repository'.format(
BentoUri.StorageType.Name(bento_pb.bento.uri.type)))
return self._add(deployment_pb, bento_pb, bento_pb.bento.uri.uri)
except BentoMLException as error:
deployment_pb.state.state = DeploymentState.ERROR
deployment_pb.state.error_message = f'Error: {str(error)}'
return ApplyDeploymentResponse(status=error.status_proto,
deployment=deployment_pb)
def delete(self, deployment_pb):
try:
deployment_spec = deployment_pb.spec
sagemaker_config = deployment_spec.sagemaker_operator_config
sagemaker_config.region = (sagemaker_config.region
or get_default_aws_region())
if not sagemaker_config.region:
raise InvalidArgument('AWS region is missing')
sagemaker_client = boto3.client('sagemaker',
sagemaker_config.region)
_, _, sagemaker_endpoint_name = _get_sagemaker_resource_names(
deployment_pb)
try:
delete_endpoint_response = sagemaker_client.delete_endpoint(
EndpointName=sagemaker_endpoint_name)
logger.debug("AWS delete endpoint response: %s",
delete_endpoint_response)
except ClientError as e:
raise _aws_client_error_to_bentoml_exception(e)
_try_clean_up_sagemaker_deployment_resource(deployment_pb)
return DeleteDeploymentResponse(status=Status.OK())
except BentoMLException as error:
return DeleteDeploymentResponse(status=error.status_proto)
def delete(self, deployment_pb):
try:
deployment_spec = deployment_pb.spec
sagemaker_config = deployment_spec.sagemaker_operator_config
sagemaker_config.region = (sagemaker_config.region
or get_default_aws_region())
if not sagemaker_config.region:
raise InvalidArgument('AWS region is missing')
delete_sagemaker_deployment_resources_if_exist(deployment_pb)
return DeleteDeploymentResponse(status=Status.OK())
except BentoMLException as error:
return DeleteDeploymentResponse(status=error.status_proto)
def describe(self, deployment_pb):
try:
deployment_spec = deployment_pb.spec
sagemaker_config = deployment_spec.sagemaker_operator_config
sagemaker_config.region = (sagemaker_config.region
or get_default_aws_region())
if not sagemaker_config.region:
raise InvalidArgument('AWS region is missing')
sagemaker_client = boto3.client('sagemaker',
sagemaker_config.region)
_, _, sagemaker_endpoint_name = _get_sagemaker_resource_names(
deployment_pb)
try:
endpoint_status_response = sagemaker_client.describe_endpoint(
EndpointName=sagemaker_endpoint_name)
except ClientError as e:
raise _aws_client_error_to_bentoml_exception(
e,
f"Failed to fetch current status of sagemaker endpoint "
f"'{sagemaker_endpoint_name}'",
)
logger.debug("AWS describe endpoint response: %s",
endpoint_status_response)
endpoint_status = endpoint_status_response["EndpointStatus"]
service_state = ENDPOINT_STATUS_TO_STATE[endpoint_status]
deployment_state = DeploymentState(
state=service_state,
info_json=json.dumps(endpoint_status_response, default=str),
)
deployment_state.timestamp.GetCurrentTime()
return DescribeDeploymentResponse(state=deployment_state,
status=Status.OK())
except BentoMLException as error:
return DescribeDeploymentResponse(status=error.status_proto)
def describe(self, deployment_pb):
try:
deployment_spec = deployment_pb.spec
lambda_deployment_config = deployment_spec.aws_lambda_operator_config
lambda_deployment_config.region = (lambda_deployment_config.region
or get_default_aws_region())
if not lambda_deployment_config.region:
raise InvalidArgument('AWS region is missing')
bento_pb = self.yatai_service.GetBento(
GetBentoRequest(
bento_name=deployment_spec.bento_name,
bento_version=deployment_spec.bento_version,
))
bento_service_metadata = bento_pb.bento.bento_service_metadata
api_names = ([lambda_deployment_config.api_name]
if lambda_deployment_config.api_name else
[api.name for api in bento_service_metadata.apis])
try:
cf_client = boto3.client('cloudformation',
lambda_deployment_config.region)
cloud_formation_stack_result = cf_client.describe_stacks(
StackName='{ns}-{name}'.format(ns=deployment_pb.namespace,
name=deployment_pb.name))
stack_result = cloud_formation_stack_result.get('Stacks')[0]
# https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/\
# using-cfn-describing-stacks.html
success_status = ['CREATE_COMPLETE', 'UPDATE_COMPLETE']
if stack_result['StackStatus'] in success_status:
if stack_result.get('Outputs'):
outputs = stack_result['Outputs']
else:
return DescribeDeploymentResponse(
status=Status.ABORTED(
'"Outputs" field is not present'),
state=DeploymentState(
state=DeploymentState.ERROR,
error_message='"Outputs" field is not present',
),
)
elif stack_result[
'StackStatus'] in FAILED_CLOUDFORMATION_STACK_STATUS:
state = DeploymentState(state=DeploymentState.FAILED)
state.timestamp.GetCurrentTime()
return DescribeDeploymentResponse(status=Status.OK(),
state=state)
else:
state = DeploymentState(state=DeploymentState.PENDING)
state.timestamp.GetCurrentTime()
return DescribeDeploymentResponse(status=Status.OK(),
state=state)
except Exception as error: # pylint: disable=broad-except
state = DeploymentState(state=DeploymentState.ERROR,
error_message=str(error))
state.timestamp.GetCurrentTime()
return DescribeDeploymentResponse(status=Status.INTERNAL(
str(error)),
state=state)
outputs = {o['OutputKey']: o['OutputValue'] for o in outputs}
info_json = {}
if 'EndpointUrl' in outputs:
info_json['endpoints'] = [
outputs['EndpointUrl'] + '/' + api_name
for api_name in api_names
]
if 'S3Bucket' in outputs:
info_json['s3_bucket'] = outputs['S3Bucket']
state = DeploymentState(state=DeploymentState.RUNNING,
info_json=json.dumps(info_json))
state.timestamp.GetCurrentTime()
return DescribeDeploymentResponse(status=Status.OK(), state=state)
except BentoMLException as error:
return DescribeDeploymentResponse(status=error.status_proto)