Migration from MMS 0.4

MMS 1.0 is a major release that contains significant architecture improvement based on MMS 0.4.

MMS 1.0 adopted micro-services based architecture, the frontend request handler is separated from backend inference worker. The frontend is a java based web service which provide REST API, and backend is python based worker which execute custom service code (Other language worker support is also planed).

Installation

MMS 1.0 made following changes for pip installation package:

java 8: java is required for MMS 1.0. You must install java 8 (or later) and make sure java is on available in $PATH environment variable before installing MMS. If you have multiple java installed, you can use $JAVA_HOME environment vairable to control which java to use.
mxnet: mxnet will not be installed by default with MMS 1.0 any more. You have to install it manually.

See more detail: Install MMS

Command line interface

MMS 1.0 made some parameter changes in mxnet-model-server command line tool. The following command line parameters from previous versions will no longer function:

–service, See Register model for how to override service entry-point.
–gen-api, See API description for how to generate your swagger client code.
–port, See Configure MMS listening port for how to configure MMS listening ports.
–host, See Configure MMS listening port for how to bind to specific network interface.
–gpu, See Config properties for how to limit the number of GPUs.
–log-file, See Logging for how to specify a log file.
–log-rotation-time, See Logging for how to configure log rotation.
–log-level, See Logging for how to configure log level.
–metrics-write-to, See Metrics for how to configure metrics.

For further information on the parameters’ updates, please see the Command Line Interface section of the server documentation.

API

You can continue to use MMS 0.4 inference API in MMS 1.0. However they are deprecated. Please migrate to new inference API

Model archive

You can continue to use your existing MMS 0.4 model archive (.model file). We stronger recommend you to migrate to new Model archive (.mar) format.

Please refer to following documents:

model-archiver

mxnet-model-export is no longer supported. Instead we release a model-archiver CLI tool. model-archiver now can be installed standalone:

pip install model-archiver

See model-archiver for more detail.

Docker container

MMS docker image makes it easier for you to serve a model. In 0.4 release, MMS require a configuration file (mms_app_cpu.conf or mms_app_gpu.conf) to start MMS in docker container. The old conf file format is no longer supported. To make it simple, MMS no longer requires the –mms-config parameter, the default configuration should work for most of use cases. MMS will start automatically while docker container starts:

docker run -itd --name mms -p 80:8080 -p 8081:8081 awsdeeplearningteam/multi-model-server

After docker container started, you can use Management API to load models for inference.

See Docker Image for detail.

Logging

MMS 1.0 provides highly customizable logging feature. MMS 0.4 logging parameter (–log-file, , –log-rotation-time and –log-level) in command line is not supported.

For more detail see Logging configuration

Metrics

MMS 1.0 redesigned metrics feature:

The old –metrics-write-to parameter is not supported, instead a rich configuration is provided.
The built-in ClouldWatch integration is removed, instead MMS 1.0 provide a template allows user to integrated with any metrics server.

See Metrics for more detail.

Configuration

MMS 1.0 provide a rich set of configuration parameters allow advanced user to customize/tune MMS. A completely new set of parameters are introduced in new config.properties file. The MMS 0.4 format of configuration file is not supported any more.

See Advanced configuration for more detail.

SSL

MMS 0.4 support SSL via nginx, now MMS 1.0 provide native SSL support. See Enable SSL for detail.