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.

FAQ

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

Load 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.)

Table of Contents

Cluster Installation

Indices and tables