backend.ai-console

Make AI Accessible: Backend.AI GUI console (web/app) for End-user / SysAdmin / DevOps.

For more information, see manual.

Changelog

View changelog

Role

Backend.AI console focuses to

• Serve as desktop app (windows, macOS and Linux) and web service
• Provide both basic administration and user mode
  • Use CLI for detailed administration features such as domain administation
• Versatile devices ready such as mobile, tablet and desktop.
• Built-in websocket proxy feature for apps

User Features

• Session management
  • Set default resources for runs
  • Choose and run environment-supported apps
  • Terminal for each session
  • Fully-featured VSCode editor and environments
• Pipeline
  • Experiments (with SACRED / MLFlow)
  • AutoML (with NNI / MLFlow)
  • Manages container streams with pipeline vfolders
  • Checks queue and scheduled jobs
• Storage management
  • Create / delete folders
  • Upload / download files (with upload progress)
  • Integrated SSH/SFTP server (app mode only)
  • Share folders with friends / groups
• Statistics
  • User resource statistics
  • Session statistics
  • Workload statistics
  • Insight (working)
• Configurations
  • User-specific web / app configurations
  • Beta features
  • Console logs / errors

Management Features

• Keypair management
  • Allocate resource limitation for keys
  • Add / remove resource policies for keys
• Kernel managements
  • List supported kernels
  • Add kernel
  • Refresh kernel list
  • Categorize repository
  • Add/update resource templates
  • Add/remove docker registries
• User management
  • User creation / deletion / key management / resource templates
• Manager settings
  • Add /setting repository
  • Plugin support
• Proxy mode to support various app environments (with node.js (web), electron (app) )
  • Needs backend.ai-wsproxy package
• Service information
  • Component compatibility
  • Security check
  • License information
• Work with console server (github/lablup/backend.ai-console-server)
  • Delegate login to console server
  • Support userid / password login

Setup Guide

Baked versions

backend.ai-console production version is also served as backend.ai-app and refered by backend.ai-console-server as submodule. If you use backend.ai-console-server, you are using latest stable release of backend.ai-console.

Configuration

Backend.AI Console uses config.toml located in app root directory. You can prepare many config.toml.[POSTFIX] in configs directory to switch various configurations.

These are options in config.toml.

[general]
apiEndpoint = "[Default API Endpoint. If blank, user input field will be shown.]"
apiEndpointText = "[Placeholder text instead of API endpoint input field.]"
defaultSessionEnvironment = "[Default session kernel. If blank, alphabetically first kernel will be default.]"
siteDescription = "[Site description placeholder. It will be at the bottom of 'Backend.AI' at the top left corner.]"
connectionMode = "[Connection mode. Default is API. Currenly supports API and SESSION]"
allowChangeSigninMode = false # Allows user to change signin mode between `API` and `SESSION`
signupSupport = false # Enable / disable signup feature support. Manager plugin is required.
allowSignout = false # Let users signout from service. Signup plugin is required.
allowAnonymousChangePassword = false # Enable / disable anonymous user can send change password email. Manager plugin is required.
allowProjectResourceMonitor = true # Allow users to look up its group monitor statistics
debug = false # Debug flag. Enable this flag will bypass every error messages from manager to app notification.

[wsproxy]
proxyURL = "[Proxy URL]"
proxyBaseURL = "[Base URL of websocket proxy,]"
proxyListenIP = "[Websocket proxy configuration IP.]"

[server]
consoleServerURL = "[Console server website URL. App will use the site instead of local app.]"
                   # Uses websocket proxy in the app

[plugins]
# Reserved to load plugins
# login = "login-test.js"
# sidebar = "sidebar-test.js"

Branches

• master : Development branch
• release : Latest release branch
• feature/[feature-branch] : Feature branch. Uses git flow development scheme.
• tags/v[versions] : version tags. Each tag represents release versions.

Development Guide

Backend.AI console is built with

• lit-element as webcomponent framework
• npm as package manager
• rollup as bundler
• electron as app shell

Code of conduct

View Code of conduct for community guidelines.

Initializing

$ npm i

If this is not your first-time compilation, please clean the temporary directories with this command:

$ make clean

You must perform first-time compilation for testing. Some additional mandatory packages should be copied to proper location.

$ make compile_wsproxy

Some necessary libraries will be copied to src/lib. Now you are ready to test.

Developing / testing without bundling

$ npm run server:d # To run dev. web server
$ npm run build:d # To watch source changes
$ npm run wsproxy # To run websocket proxy

Unit Testing

The project uses testcafe as testing framework. To perform functional tests, you must run complete Backend.AI cluster before starting test.

$ npm run server:d # To run dev. web server
$ npm run test # Run tests (tests are located in `tests` directory)

Electron (app mode) development / testing

Live testing

Terminal 1:

$ npm run server:d # To run test server

OR

$ npm run server:p # To run compiled source

Terminal 2:

$ npm run electron:d # Run Electron as dev mode.

Serving Guide

Preparing bundled source

$ make compile

Then bundled resource will be prepared in build/rollup. Basically, both app and web serving is based on static serving sources in the directory. However, to work as single page application, URL request fallback is needed.

Serving with nginx

If you need to serve with nginx, please install and setup backend.ai-wsproxy package for websocket proxy. Bundled websocket proxy is simplified version for single-user app.

This is nginx server configuration example. [APP PATH] should be changed to your source path.

server {
    listen      443 ssl http2;
    listen [::]:443 ssl http2;
    server_name [SERVER URL];
    charset     utf-8;

    client_max_body_size 15M;   # maximum upload size.

    root [APP PATH];
    index index.html;

    location / {
        try_files $uri /index.html;
    }
    keepalive_timeout 120;

    ssl_certificate [CERTIFICATE FILE PATH];
    ssl_certificate_key [CERTIFICATE KEY FILE PATH];
}

Building docker image using docker-compose

Make sure that you compile the console.

e.g. You will download the backend.ai-console-server package.

$ make compile

Web server

Good for develop phase. Not recommended for production environment.

Note: This command will use console source in build/rollup directory. No certificate will be used therefore console server will serve as HTTP.

Copy console-server.example.conf in docker_build directory into current directory as console-server.conf and modify configuration files for your needs.

$ docker-compose build console-dev // build only
$ docker-compose up console-dev    // for testing
$ docker-compose up -d console-dev // as a daemon

Visit http://127.0.0.1:8080 to test console server.

Web server with SSL

Recommended for production.

Note: You have to enter the certificates (chain.pem and priv.pem) into certificates directory. Otherwise, you will have an error during container initialization.

Copy console-server.example.ssl.conf in docker_build directory into current directory as console-server.conf and modify configuration files for your needs.

$ docker-compose build console  // build only
$ docker-compose up console     // for testing
$ docker-compose up -d console  // as a daemon

Visit https://127.0.0.1:443 to test console server serving. Change 127.0.0.1 to your production domain.

Removing

$ docker-compose down

Manual image build

$ make compile
$ docker build -t backendai-console .

Testing / Running example

Check your image name is backendai-console_console or backendai-console_console-ssl. Otherwise, change the image name in the script below.

$ docker run --name backendai-console -v $(pwd)/config.toml:/usr/share/nginx/html/config.toml -p 80:80 backendai-console_console /bin/bash -c "envsubst '$$NGINX_HOST' < /etc/nginx/conf.d/default.template > /etc/nginx/conf.d/default.conf && nginx -g 'daemon off;'"
$ docker run --name backendai-console-ssl -v $(pwd)/config.toml:/usr/share/nginx/html/config.toml -v $(pwd)/certificates:/etc/certificates -p 443:443 backendai-console_console-ssl /bin/bash -c "envsubst '$$NGINX_HOST' < /etc/nginx/conf.d/default-ssl.template > /etc/nginx/conf.d/default.conf && nginx -g 'daemon off;'"

Building / serving with console-server

If you need to serve as console-server (ID/password support) without compiling anything, you can use pre-built code through console-server submodule.

To download and deploy console from pre-built source, do the following in backend.ai-console-server repository:

git submodule init
git submodule update
cd src/ai/backend/console/static
git checkout master
git fetch
git pull

Running websocket proxy with node.js

This is only needed with pure ES6 dev. environment / browser. Websocket proxy is embedded in Electron and automatically starts.

$ npm run wsproxy

If console app is behind an external http proxy, and you have to pass through it to connect to a console-server or manager server, you can set EXT_HTTP_PROXY environment variable with the address of the http proxy. Local websocket proxy then communicates with the final destination via the http proxy. The address should include the protocol, host, and/or port (if exists). For example,

export EXT_HTTP_PROXY=http://10.20.30.40:3128 (Linux)
set EXT_HTTP_PROXY=http://10.20.30.40:3128 (Windows)

Even if you are using Electron embedded websocket proxy, you have to set the environment variable manually to pass through a http proxy.

Build web server with specific configuration

You can prepare site-specific configuration as ini format. Also, you can build site-specific web bundle refering in configs directory.

Note: Default setup will build es6-bundled version. If you want to use es6-unbundled, make sure that your webserver supports HTTP/2 and setup as HTTPS with proper certification.

$ make web site=[SITE CONFIG FILE POSTFIX]

If no prefix is given, default configuration file will be used.

Example:

$ make web site=beta

You can manually modify config.toml for your need.

App Building Guide

Building Electron App

Electron building is automated using Makefile.

$ make clean  # clean prebuilt codes
$ make mac # build macOS app
$ make win # build win64 app
$ make linux # build linux app
$ make all # build win64/macos/linux app

Windows x86-64 version

$ make win

Note: Building Windows x86-64 on other than Windows requires Wine > 3.0 Note: On macOS Catalina, use scripts/build-windows-app.sh to build Windows 32bitpackage. From macOS 10.15+, wine 32x is not supported. Note: Now the make win command support only Windows x64 app, therefore you do not need to use build-windows-app.sh anymore.

macOS version

$ make mac

Linux x86-64 version

$ make linux

Packaging as zip files

Note: this command only works on macOS, because packaging uses ditto, that supports both PKZIP and compressed CPIO format.

Note: Packaging usually performs right after app building. Therefore you do not need this option in normal condition.

Note: Requires electron-installer-dmg to make macOS disk image. It requires Python 2+ to build binary for package.

$ make pack

Manual run to test Electron

Note: There are two Electron configuration files, main.js and main.electron-packager.js. Local Electron run uses main.js, not main.electron-packager.js that is used for real Electron app.

$ make dep # Compile with app dependencies
$ npm run electron:d  # OR, ./node_modules/electron/cli.js .

Localization

Locale resources are JSON files located in resources/i18n.

Extracting i18n resources

Run

make i18n

to update / extract i18n resources.

Adding i18n strings

• Use _t as i18n resource handler on lit-element templates.
• Use _tr as i18n resource handler if i18n resource has HTML code inside.
• Use _text as i18n resource handler on lit-element Javascript code.

Example

In lit-html template:

<div>${_t('general.helloworld')}</div>

In i18n resource (en.json):

{
   'general':{
      'helloworld': 'Hello World'
   }
}

Adding new language

1. Copy en.json to target language. (e.g. ko.json)
2. Add language identifier to supportLanguageCodes in backend-ai-console.ts. e.g.

  @property({type: Array}) supportLanguageCodes = ["en", "ko"];

3. Add language information to supportLanguages in backend-ai-usersettings-general-list.ts.

Note: DO NOT DELETE 'default' language. It is used for browser language.

  @property({type: Array}) supportLanguages = [
    {name: _text("language.Browser"), code: "default"},
    {name: _text("language.English"), code: "en"},
    {name: _text("language.Korean"), code: "ko"}
  ];