presentation – Live Video Platform for FIFA World Cup


In this talk, we will describe globo.com’s live video stream architecture, which was used to broadcast events such as the FIFA World Cup (with peak of 500K concurrent users), Brazilian election debates (27 simultaneous streams) and BBB (10 cameras streaming 24/7 for 3 months) .

NGINX is one of the main components of our platform, as we use it for content distribution, caching, authentication, and dynamic content. Besides our architecture, we will also discuss the Nginx and Operational System tuning that was required for a 19Gbps throughput in each node, the open source Cassandra driver for Nginx that we developed, and our recent efforts to migrate to nginx-rtmp.

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presentation QCon 2015 – ptBR

http://www.infoq.com/br/presentations/contos-de-escalabilidade-na-plataforma-de-videos-online-da-globo

qcon-rio-2015-escalabilidade-na-plataforma-de-vdeos-ao-vivo-29-1024

In this presentation you’ll see how we developed (what we used) the live video platform for the FIFA World Cup 2014. It shows how we made it scalable using lots of open source solutions.

Keywords: linux, cassandra, nginx, redis, BGP, logstash, graphite, python, ruby, lua

Testing in python can be fun too!

Humble beginning

I come from (lately) Ruby,  Java and Clojure and currently I’m working with some python projects and I was missing the way I used to test my code with rspec.  After a quick research, I found three great projects that helps to make more readable tests, they are: py.test, Mock and sure.

Better assertions

I was missing a better way to make asserts into my tests. The option about using the plain assert is good but not enough and by using sure I could do some awesome code looking similar to rspec.

#instead of plain old assert
assert add(1, 4) == 5
#I'm empowered by
add(1, 4).should.be.equals(5)
[].should.be.empty
['chip8', 'schip8', 'chip16'].shouldnt.be.empty
[1, 2, 3, 4].should.have.length_of(4)

And this makes all the difference, my test code now is more expressive.

Struggling with monkeypatch

The other challenge I was facing was to understand and use monkeypatch for mocks and stubs.  I find easier to use the Mock library even though its @patch looks similar to monkeypatch but I could grasp it quickly.

#Stubing
def test_simple_math_remotely_stubed():
  server = Mock()
  server.computes_add = Mock(return_value=3)

  add_remotely(1, 2, server).should.be.equals(3)

#Mocking
def test_simple_math_remotely_mocked():
  server = Mock()

  add_remotely(1, 2, server)

  server.computes_add.assert_called_once_with(1, 2)

#Stubing an internal dependency
@patch('cmath.nasa.random')
def test_simple_math_with_randon_generated_by_nasa(nasa_random_generator):
  nasa_random_generator.configure_mock(return_value=42)

  add_and_sum_with_rnd(3, 9).should.be.equals(54)

#Mocking an internal dependency
@patch('cmath.mailer.send')
def test_simple_math_that_sends_email(mailer_mock):
  add_and_sends_email(3, 9)

  mailer_mock.assert_called_once_with(
          to='master@math.com',
          subject='Complex addition',
          body='The result was 12')

Make sure you

  1. Are using virtualenv for better lib version managment
  2. Have installed pytest, sure and mock
  3. Git cloned the project above to understand it.