Backend.AI Documentation

Latest API version: v3.20170615 (beta)

Backend.AI is a hassle-free backend for AI programming and service. It runs arbitrary user codes safely in resource-constrained environments, using Docker and our own sandbox wrapper.

Backend.AI supports various programming languages and runtimes, such as Python 2/3, R, PHP, C/C++, Java, Javascript, Julia, Octave, Haskell, Lua and NodeJS, as well as AI-oriented libraries such as TensorFlow, Keras, Caffe, and MXNet.


vs. Notebooks

Product Role Problem and Solution
Apache Zeppelin, Jupyter Notebook Notebook-style document + code front-ends Insecure host resource sharing
Backend.AI Pluggable back-end to any front-ends Built for multi-tenancy: scalable and better isolation

vs. Orchestration Frameworks

Product Target Value
Amazon ECS, Kubernetes Long-running service daemons Laod balancing, fault tolerance, incremental deployment
Backend.AI Stateful compute sessions Low-cost high-density computation
Amazon Lambda Stateless, light-weight functions Serverless, zero-management

vs. Big-data and AI Frameworks

Product Role Problem and Solution
TensorFlow, Apache Spark, Apache Hive Computation runtime Difficult to install, configure, and operate
Amazon ML, Azure ML, GCP ML Managed MLaaS Still complicated for scientists, too restrictive for engineers
Backend.AI Host of computation runtimes Pre-configured, versioned, reproducible, customizable (open-source)

(All product names and trade-marks are the properties of their respective owners.)

Indices and tables