Configuration

BentoML starts with an out-of-the-box configuration that works for common use cases. For advanced users, many features can be customized through configuration. Both BentoML CLI and Python APIs can be customized by the configuration. Configuration is best used for scenarios where the customizations can be specified once and applied to the entire team.

Note

BentoML configuration underwent a major redesign in release 0.13.0. Previous configuration set through the bentoml config CLI command is no longer compatible with the configuration releases in 0.13.0 and above. Please see legacy configuration property mapping table below to upgrade configuration to the new format.

BentoML configuration is defined by a YAML file placed in a directory specified by the BENTOML_CONFIG environment variable. The example below starts the bento server with configuration defined in ~/bentoml_configuration.yml

$ BENTOML_CONFIG=~/bentoml_configuration.yml bentoml serve-gunicorn IrisClassifier:latest

Users only need to specify a partial configuration with only the properties they wish to customize instead of a full configuration schema. In the example below, the microbatching workers count is overridden to 4. Remaining properties will take their defaults values.

BentoML Configuration

bento_server:
    microbatch:
        workers: 4

Throughout the BentoML documentation, features that are customizable through configuration are demonstrated like the example above. For a full configuration schema including all customizable properties, refer to the BentoML configuration template defined in default_configuration.yml.

Docker Deployment

Configuration file can be mounted to the Docker container using the -v option and specified to the BentoML runtime using the -e environment variable option.

$ docker run -v /local/path/configuration.yml:/home/bentoml/configuration.yml -e BENTOML_CONFIG=/home/bentoml/configuration.yml

Configuration Priority

Some customizable properties in the configuration can also be specified in the BentoML CLI or Python API parameters. Values specified through BentoML CLI and Python API parameters will always take precedence over the values defined in the configuration.

Legacy Property Mapping

Starting BentoML release 0.13.0, the legacy bentoml.cfg based configuration is deprecated and no longer compatible with the YAML based configuration system. Please refer to the mapping below to migrate to the YAML based configuration.

CFG Properties		YAML Properties
Section	Key	Key
core	bentoml_deploy_version	bento_bundle.deployment_version
core	default_docker_base_image	bento_bundle.default_docker_base_image
instrument	default_namespace	bento_server.metrics.namespace
instrument	prometheus_multiproc_dir	DEPRECATED
logging	logging_config	See Logging guide
logging	console_logging_enabled	logging.console.enabled
logging	file_logging_enabled	logging.file.enabled
logging	level	logging.level
logging	log_format	DEPRECATED
logging	dev_log_format	DEPRECATED
logging	base_log_dir	logging.file.directory
logging	prediction_log_filename	DEPRECATED
logging	feedback_log_filename	DEPRECATED
logging	yatai_web_server_log_filename	yatai.logging.path
yatai_service	url	yatai.remote.url
yatai_service	s3_signature_version	yatai.repository.s3.signature_version
yatai_service	repository_base_url	See Repository Base URL section
yatai_service	db_url	yatai.database.url
yatai_service	s3_endpoint_url	yatai.repository.s3.endpoint_url
yatai_service	default_namespace	yatai.namespace
yatai_service	tls_root_ca_cert	yatai.remote.tls.root_ca_cert
yatai_service	tls_client_key	yatai.remote.tls.client_key
yatai_service	tls_client_cert	yatai.remote.tls.client_cert
yatai_service	access_token	yatai.remote.access_token
yatai_service	access_token_header	yatai.remote.access_token_header
apiserver	default_port	bento_server.port
apiserver	enable_metrics	bento_server.metrics.enabled
apiserver	enable_feedback	bento_server.feedback.enabled
apiserver	default_timeout	bento_server.timeout
apiserver	default_max_request_size	bento_server.max_request_size
apiserver	default_image_input_accept_file_extensions	adapters.image_input.default_extensions
apiserver	default_gunicorn_workers_count	bento_server.workers
yatai	bento_uri_default_expiration	yatai.repository.s3.expiration OR yatai.repository.gcs.expiration

Repository Base URL

The repository base URL property has been broken down into properties for the individual repository implementations, instead of being derived automatically.

For file system, what was previously specified as /user/home/bentoml/repository should defined as the following in YAML.

BentoML Configuration

yatai:
    repository:
        type: file_system
        file_system:
            directory: /user/home/bentoml/repository

For S3 or GCS, what was previously specified as s3://s3_address should defined as the following in YAML.

BentoML Configuration

yatai:
    repository:
        type: s3
        s3:
            url: s3://s3_address