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)