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AppRTCUbuntu.md

AppRTC Demo Code

Development

Detailed information on devloping in the webrtc github repo can be found in the WebRTC GitHub repo developer's guide.

Running AppRTC locally requires the Google App Engine SDK for Python and Grunt.

Detailed instructions for running on Ubuntu Linux are provided below.

Installing Google App Engine SDK for Python on Linux

Unzip the App Engine SDK file you downloaded google_appengine_1.9.40.zip, for example:

unzip google_appengine_1.9.40.zip -d /var/www/destination_folder

There is no App Engine installation script that you need to run after unzipping the files. Add the google_appengine directory to your PATH:

export PATH=$PATH:/path/to/google_appengine/

Make sure Python 2.7 is installed on your machine using the following command:

/usr/bin/env python -V

The output should look like this: Python 2.7.. If Python 2.7 isn't installed, install it now using the installation instructions for your Linux distribution.

Running on Ubuntu Linux

Install grunt by first installing npm. npm is distributed as part of nodejs.

sudo apt-get install nodejs
sudo npm install -g npm

On Ubuntu 14.04 the default packages installs /usr/bin/nodejs but the /usr/bin/node executable is required for grunt. This is installed on some Ubuntu package sets; if it is missing, you can add this by installing the nodejs-legacy package,

sudo apt-get install nodejs-legacy

It is easiest to install a shared version of grunt-cli from npm using the -g flag. This will allow you access the grunt command from /usr/local/bin. More information can be found on gruntjs Getting Started.

sudo npm -g install grunt-cli

Omitting the -g flag will install grunt-cli to the current directory under the node_modules directory.

Finally, you will want to install grunt and required grunt dependencies. This can be done from any directory under your checkout of the webrtc/apprtc repository.

npm install

On Ubuntu, you will also need to install the webtest package:

sudo apt-get install python-webtest

Before you start the AppRTC dev server and *everytime you update the source code you need to recompile the App Engine package by running,

grunt build

Start the AppRTC dev server from the out/app_engine directory by running the Google App Engine SDK dev server,

dev_appserver.py --host 0.0.0.0 --port  9090 ./out/app_engine

Then navigate to http://localhost:9090 in your browser (given it's on the same machine).

Allow Secure HTTP

Install Stunnel package using the code below:

apt-get install stunnel4 -y

Configure Stunnel - Stunnel configures itself using a file named "stunnel.conf" which by default is located in "/etc/stunnel".

Create a "stunnel.conf" file in the "/etc/stunnel" directory:

sudo gedit /etc/stunnel/stunnel.conf

We’re going to be using a SSL certificate to identify ourselves to the server so we have to set the path to that certificate in "stunnel.conf" file using this line (We will create the certificate file in the next step):

cert = /etc/stunnel/stunnel.pem

Next we specify a service for use with Stunnel. It can be any of the services which use networking such as mail server, proxy server, etc.

After setting a name for the service you’re going to use, you must tell Stunnel to listen on which port for that service. This can be any of the 65535 ports, as long as it’s not blocked by another service or firewall:

[https]
accept = 433

Then depending on the service you’re going to use the secure tunnel on, you must specify the port and IP address of that in the configuration file Basically Stunnel takes packets from a secure port and then forwards it to the port and IP address of the service you specified.

Squid proxy by default runs on localhost and port 9090 so we have to tell Stunnel to forward accepted connections to that port:

connect = 127.0.0.1:9090

So overall the "stunnel.conf" file must contain the lines below:

client = no
[https]
accept = 433
connect = 127.0.0.1:9090
cert = /etc/stunnel/stunnel.pem

Note: The client = no part isn't necessary, Stunnel by default is set to server mode. Step 5: Create SSL Certificates

Stunnel uses SSL certificate to secure its connections, which you can easily create using the OpenSSL package:

openssl genrsa -out key.pem 2048
openssl req -new -x509 -key key.pem -out cert.pem -days 1095
sudo cat key.pem cert.pem >> sudo /etc/stunnel/stunnel.pem

Basically, the commands above is for creating a private key, creating a certificate using that key and combining the two of them into one files named "stunnel.pem" to use with Stunnel.

Note: When creating the certificate, you will be asked for some information such as country and state, which you can enter whatever you like but when asked for "Common Name" you must enter the correct host name or IP address of your droplet (VPS).

Also, enable Stunnel automatic startup by configuring the "/etc/default/stunnel4" file, enter command below to open the file in text editor:

gedit /etc/default/stunnel4

And change ENABLED to 1:

ENABLED=1

Finally, restart Stunnel for configuration to take effect, using this command:

/etc/init.d/stunnel4 restart

Testing

All tests by running grunt.

To run only the Python tests you can call,

grunt runPythonTests

Enabling Local Logging

Note that logging is automatically enabled when running on Google App Engine using an implicit service account.

By default, logging to a BigQuery from the development server is disabled. Log information is presented on the console. Unless you are modifying the analytics API you will not need to enable remote logging.

Logging to BigQuery when running LOCALLY requires a secrets.json containing Service Account credentials to a Google Developer project where BigQuery is enabled. DO NOT COMMIT secrets.json TO THE REPOSITORY.

To generate a secrets.json file in the Google Developers Console for your project:

  1. Go to the project page.
  2. Under APIs & auth select Credentials.
  3. Confirm a Service Account already exists or create it by selecting Create new Client ID.
  4. Select Generate new JSON key from the Service Account area to create and download JSON credentials.
  5. Rename the downloaded file to secrets.json and place in the directory containing analytics.py.

When the Analytics class detects that AppRTC is running locally, all data is logged to analytics table in the dev dataset. You can bootstrap the dev dataset by following the instructions in the Bootstrapping/Updating BigQuery.

BigQuery

When running on App Engine the Analytics class will log to analytics table in the prod dataset for whatever project is defined in app.yaml.

Schema

bigquery/analytics_schema.json contains the fields used in the BigQuery table. New fields can be added to the schema and the table updated. However, fields cannot be renamed or removed. Caution should be taken when updating the production table as reverting schema updates is difficult.

Update the BigQuery table from the schema by running,

bq update -t prod.analytics bigquery/analytics_schema.json

Bootstrapping

Initialize the required BigQuery datasets and tables with the following,

bq mk prod
bq mk -t prod.analytics bigquery/analytics_schema.json

Deployment

In order to deploy your own AppRTC instance you need a TURN/ICE server and a signaling server, in addition to AppRTC itself. The signaling server (Collider) is part of this repository and can be found here) while the TURN server used is rfc5766-turn-server. Credentials and TURN server instances are provided by a CEOD service that generates TURN servers on demand in form of a JSON response.

This means you need to either set-up a web server that returns TURN credentials and IP addresses (basically mimic the CEOD server) in a JSON response, or replace the CEOD details with your own TURN server provider details, and then change to turn_url = constants.TURN_URL_TEMPLATE.

You can test using your own TURN server by appending the ?ts=serverUrl parameter, details on AppRTC URL parameters can be found at https://appr.tc/params.html.

References

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