def deployment_dict_to_pb(deployment_dict):
deployment_pb = Deployment()
if deployment_dict.get('spec'):
spec_dict = deployment_dict.get('spec')
else:
raise YataiDeploymentException(
'"spec" is required field for deployment')
platform = spec_dict.get('operator')
if platform is not None:
# converting platform parameter to DeploymentOperator name in proto
# e.g. 'aws-lambda' to 'AWS_LAMBDA'
deployment_pb.spec.operator = DeploymentSpec.DeploymentOperator.Value(
platform.replace('-', '_').upper())
for field in ['name', 'namespace']:
if deployment_dict.get(field):
deployment_pb.__setattr__(field, deployment_dict.get(field))
if deployment_dict.get('labels') is not None:
deployment_pb.labels.update(deployment_dict.get('labels'))
if deployment_dict.get('annotations') is not None:
deployment_pb.annotations.update(deployment_dict.get('annotations'))
if spec_dict.get('bento_name'):
deployment_pb.spec.bento_name = spec_dict.get('bento_name')
if spec_dict.get('bento_version'):
deployment_pb.spec.bento_version = spec_dict.get('bento_version')
if deployment_pb.spec.operator == DeploymentSpec.AWS_SAGEMAKER:
sagemaker_config = spec_dict.get('sagemaker_operator_config', {})
sagemaker_config_pb = deployment_pb.spec.sagemaker_operator_config
for field in [
'region',
'api_name',
'instance_type',
'num_of_gunicorn_workers_per_instance',
'instance_count',
]:
if sagemaker_config.get(field):
sagemaker_config_pb.__setattr__(field,
sagemaker_config.get(field))
elif deployment_pb.spec.operator == DeploymentSpec.AWS_LAMBDA:
lambda_conf = spec_dict.get('aws_lambda_operator_config', {})
for field in ['region', 'api_name', 'memory_size', 'timeout']:
if lambda_conf.get(field):
deployment_pb.spec.aws_lambda_operator_config.__setattr__(
field, lambda_conf.get(field))
else:
raise InvalidArgument(
'Platform "{}" is not supported in the current version of '
'BentoML'.format(platform))
return deployment_pb
def create_azure_functions_deployment(
self,
name,
bento_name,
bento_version,
location,
premium_plan_sku=None,
min_instances=None,
max_burst=None,
function_auth_level=None,
namespace=None,
labels=None,
annotations=None,
wait=None,
):
deployment_pb = Deployment(name=name,
namespace=namespace,
labels=labels,
annotations=annotations)
deployment_pb.spec.bento_name = bento_name
deployment_pb.spec.bento_version = bento_version
deployment_pb.spec.operator = DeploymentSpec.AZURE_FUNCTIONS
deployment_pb.spec.azure_functions_operator_config.location = location
deployment_pb.spec.azure_functions_operator_config.premium_plan_sku = (
premium_plan_sku)
deployment_pb.spec.azure_functions_operator_config.min_instances = min_instances
deployment_pb.spec.azure_functions_operator_config.function_auth_level = (
function_auth_level)
deployment_pb.spec.azure_functions_operator_config.max_burst = max_burst
return self.create(deployment_pb, wait)
def create_ec2_deployment(
self,
name,
namespace,
bento_name,
bento_version,
region,
min_size,
desired_capacity,
max_size,
instance_type,
ami_id,
wait=None,
):
deployment_pb = Deployment(name=name, namespace=namespace)
deployment_pb.spec.bento_name = bento_name
deployment_pb.spec.bento_version = bento_version
if region:
deployment_pb.spec.aws_ec2_operator_config.region = region
deployment_pb.spec.operator = DeploymentSpec.AWS_EC2
deployment_pb.spec.aws_ec2_operator_config.autoscale_min_size = min_size
deployment_pb.spec.aws_ec2_operator_config.autoscale_desired_capacity = (
desired_capacity
)
deployment_pb.spec.aws_ec2_operator_config.autoscale_max_size = max_size
deployment_pb.spec.aws_ec2_operator_config.instance_type = instance_type
deployment_pb.spec.aws_ec2_operator_config.ami_id = ami_id
return self.create(deployment_pb, wait)
def create_sagemaker_deployment(
self,
name,
bento_name,
bento_version,
api_name,
instance_type,
instance_count,
timeout,
num_of_gunicorn_workers_per_instance=None,
region=None,
namespace=None,
labels=None,
annotations=None,
wait=None,
):
"""Create SageMaker deployment
Args:
name:
bento_name:
bento_version:
api_name:
instance_type:
instance_count:
timeout:
num_of_gunicorn_workers_per_instance:
region:
namespace:
labels:
annotations:
wait:
Returns:
ApplyDeploymentResponse
Raises:
BentoMLException
"""
deployment_pb = Deployment(name=name,
namespace=namespace,
labels=labels,
annotations=annotations)
deployment_pb.spec.bento_name = bento_name
deployment_pb.spec.bento_version = bento_version
deployment_pb.spec.operator = DeploymentSpec.AWS_SAGEMAKER
deployment_pb.spec.sagemaker_operator_config.api_name = api_name
deployment_pb.spec.sagemaker_operator_config.instance_count = instance_count
deployment_pb.spec.sagemaker_operator_config.instance_type = instance_type
deployment_pb.spec.sagemaker_operator_config.timeout = timeout
if region:
deployment_pb.spec.sagemaker_operator_config.region = region
if num_of_gunicorn_workers_per_instance:
deployment_pb.spec.sagemaker_operator_config.num_of_gunicorn_workers_per_instance = ( # noqa E501
num_of_gunicorn_workers_per_instance)
return self.create(deployment_pb, wait)
def _get_test_sagemaker_deployment_pb():
test_pb = Deployment(name='test_deployment_name', namespace='namespace')
test_pb.spec.bento_name = 'bento_name'
test_pb.spec.bento_version = 'bento_version'
test_pb.spec.operator = DeploymentSpec.DeploymentOperator.Value(
'AWS_SAGEMAKER')
test_pb.spec.sagemaker_operator_config.api_name = 'api_name'
test_pb.spec.sagemaker_operator_config.instance_type = 'mock_instance_type'
test_pb.spec.sagemaker_operator_config.instance_count = 1
return test_pb
def _get_test_lambda_deployment_pb():
test_pb = Deployment(name='test_deployment_name', namespace='namespace')
test_pb.spec.bento_name = 'bento_name'
test_pb.spec.bento_version = 'bento_version'
test_pb.spec.operator = DeploymentSpec.DeploymentOperator.Value(
'AWS_LAMBDA')
test_pb.spec.aws_lambda_operator_config.api_name = 'api_name'
test_pb.spec.aws_lambda_operator_config.region = 'us-west-2'
test_pb.spec.aws_lambda_operator_config.timeout = 100
test_pb.spec.aws_lambda_operator_config.memory_size = 128
return test_pb
def generate_lambda_deployment_pb():
test_deployment_pb = Deployment(name='test_aws_lambda', namespace='test-namespace')
test_deployment_pb.spec.bento_name = 'bento_name'
test_deployment_pb.spec.bento_version = 'v1.0.0'
# DeploymentSpec.DeploymentOperator.AWS_LAMBDA
test_deployment_pb.spec.operator = 3
test_deployment_pb.spec.aws_lambda_operator_config.region = 'us-west-2'
test_deployment_pb.spec.aws_lambda_operator_config.api_name = 'predict'
test_deployment_pb.spec.aws_lambda_operator_config.memory_size = 3008
test_deployment_pb.spec.aws_lambda_operator_config.timeout = 6
return test_deployment_pb
def create_lambda_deployment(
self,
name,
bento_name,
bento_version,
memory_size,
timeout,
api_name=None,
region=None,
namespace=None,
labels=None,
annotations=None,
wait=None,
):
"""Create Lambda deployment
Args:
name:
bento_name:
bento_version:
memory_size:
timeout:
api_name:
region:
namespace:
labels:
annotations:
wait:
Returns:
ApplyDeploymentResponse: status, deployment
Raises:
BentoMLException
"""
deployment_pb = Deployment(name=name,
namespace=namespace,
labels=labels,
annotations=annotations)
deployment_pb.spec.bento_name = bento_name
deployment_pb.spec.bento_version = bento_version
deployment_pb.spec.operator = DeploymentSpec.AWS_LAMBDA
deployment_pb.spec.aws_lambda_operator_config.memory_size = memory_size
deployment_pb.spec.aws_lambda_operator_config.timeout = timeout
if api_name:
deployment_pb.spec.aws_lambda_operator_config.api_name = api_name
if region:
deployment_pb.spec.aws_lambda_operator_config.region = region
return self.create(deployment_pb, wait)
def generate_sagemaker_deployment_pb():
test_deployment_pb = Deployment(name=TEST_DEPLOYMENT_NAME,
namespace=TEST_DEPLOYMENT_NAMESPACE)
test_deployment_pb.spec.bento_name = TEST_DEPLOYMENT_BENTO_NAME
test_deployment_pb.spec.bento_version = TEST_DEPLOYMENT_BENTO_VERSION
test_deployment_pb.spec.sagemaker_operator_config.api_name = TEST_BENTO_API_NAME
test_deployment_pb.spec.sagemaker_operator_config.region = TEST_AWS_REGION
test_deployment_pb.spec.sagemaker_operator_config.instance_count = (
TEST_DEPLOYMENT_INSTANCE_COUNT)
test_deployment_pb.spec.sagemaker_operator_config.instance_type = (
TEST_DEPLOYMENT_INSTANCE_TYPE)
test_deployment_pb.spec.operator = DeploymentSpec.AWS_SAGEMAKER
return test_deployment_pb
def generate_ec2_deployment_pb():
test_deployment_pb = Deployment(name='test_aws_ec2',
namespace='test-namespace')
test_deployment_pb.spec.bento_name = 'bento_name'
test_deployment_pb.spec.bento_version = 'v1.0.0'
# DeploymentSpec.DeploymentOperator.AWS_LAMBDA
test_deployment_pb.spec.operator = 3
test_deployment_pb.spec.aws_ec2_operator_config.region = 'us-west-2'
test_deployment_pb.spec.aws_ec2_operator_config.instance_type = "t2.micro"
test_deployment_pb.spec.aws_ec2_operator_config.ami_id = "test-ami-id"
test_deployment_pb.spec.aws_ec2_operator_config.autoscale_min_size = 1
test_deployment_pb.spec.aws_ec2_operator_config.autoscale_desired_capacity = 1
test_deployment_pb.spec.aws_ec2_operator_config.autoscale_max_size = 1
return test_deployment_pb
def mock_deployment_pb(name=MOCK_DEPLOYMENT_NAME):
mock_deployment = Deployment(name=name, namespace='mock-namespace')
mock_deployment.spec.azure_functions_operator_config.location = 'mock-location'
mock_deployment.spec.operator = 4
mock_deployment.created_at.GetCurrentTime()
return mock_deployment
def test_deployment_labels():
runner = CliRunner()
cli = create_bentoml_cli()
failed_result = runner.invoke(
cli.commands['lambda'],
[
'deploy',
'failed-name',
'-b',
'ExampleBentoService:version',
'--labels',
'test=abc',
],
)
assert failed_result.exit_code == 2
with mock.patch(
'bentoml.yatai.deployment.aws_lambda.operator.AwsLambdaDeploymentOperator.add'
) as mock_operator_add:
bento_name = 'MockService'
bento_version = 'MockVersion'
deployment_name = f'test-label-{uuid.uuid4().hex[:8]}'
deployment_namespace = 'test-namespace'
mocked_deployment_pb = Deployment(name=deployment_name,
namespace=deployment_namespace)
mocked_deployment_pb.spec.bento_name = bento_name
mocked_deployment_pb.spec.bento_version = bento_version
mocked_deployment_pb.spec.operator = DeploymentSpec.AWS_LAMBDA
mocked_deployment_pb.spec.aws_lambda_operator_config.memory_size = 1000
mocked_deployment_pb.spec.aws_lambda_operator_config.timeout = 60
mocked_deployment_pb.spec.aws_lambda_operator_config.region = 'us-west-2'
mock_operator_add.return_value = ApplyDeploymentResponse(
status=Status.OK(), deployment=mocked_deployment_pb)
success_result = runner.invoke(
cli.commands['lambda'],
[
'deploy',
deployment_name,
'-b',
f'{bento_name}:{bento_version}',
'--namespace',
deployment_namespace,
'--labels',
'created_by:admin,cicd:passed',
'--region',
'us-west-2',
],
)
assert success_result.exit_code == 0
list_result = runner.invoke(
cli.commands['deployment'],
[
'list',
'--labels',
'created_by=admin,cicd NotIn (failed, unsuccessful)',
'--output',
'wide',
],
)
assert list_result.exit_code == 0
assert deployment_name in list_result.output.strip()
assert 'created_by:admin' in list_result.output.strip()