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Lablup Backend.AI Meta-package

Project description

Backend.AI is a streamlined backend service framework hosting heterogeneous programming languages and popular AI frameworks. It manages the underlying computing resources for multi-tenant computation sessions where such sessions are spawned and executed instantly on demand.

In the names of sub-projects, we use a private code-name “Sorna” which we take from a famous science fiction “Jurassic Park” – meaning that we do all the dirty jobs in the behind. In the novel, Isla Nublar is the “front-end” island where tourists see the dinosaurs and Isla Sorna is the “back-end” island where a secret dinosaurs production facility is located.

All sub-projects are licensed under LGPLv3+.

Server-side Components

Manager with API Gateway

It routes external API requests from front-end services to individual agents. It also monitors and scales the cluster of multiple agents (a few tens to hundreds).

Agent

It manages individual server instances and launches/destroys Docker containers where REPL daemons (kernels) run. Each agent on a new EC2 instance self-registers itself to the instance registry via heartbeats.

REPL

A set of small ZMQ-based REPL daemons in various programming languages and configurations. It also includes a sandbox implemented using ptrace-based sytem call filtering written in Go.

Sorna Common

A collection of utility modules commonly shared throughout Backend.AI projects.

Client-side Components

Client Libraries

A client library to access the Sorna API servers with ease.

Sorna Media

The front-end support libraries to handle multi-media outputs (e.g., SVG plots, animated vector graphics)

  • The Python package (lablup) is installed inside kernel containers.

  • To interpret and display media generated by the Python package, you need to load the Javascript part in the front-end.

  • https://github.com/lablup/sorna-media

Integrations with IDEs and Editors

Sorna Jupyter Kernel

Jupyter kernel integration of the Sorna Cloud API.

Installation

The Sorna project uses latest features in Python 3.6+ and docker. We highly recommend to use [pyenv](https://github.com/yyuu/pyenv) to use an isolated setup with custom Python versions that might not be supported by your

First, install Docker on your system. We have tested Sorna on Linux/Ubuntu and macOS (“Docker for Mac”).

For a single PC setup, just run pip install sorna. It will automatically install all above sub-projects as well as their dependencies.

Development

### git flow

The sorna repositories use [git flow](http://danielkummer.github.io/git-flow-cheatsheet/index.html) to streamline branching during development and deployment. We use the default configuration (master -> preparation for release, develop -> main development, feature/ -> features, etc.) as-is.

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