Call for proposals is now open for Code BEAM SF 19 - North America’s biggest conference covering Elixir and Erlang!
SUBMIT YOUR PROPOSAL http://bit.ly/2xJ5OWt
Our programme committee will review proposals for the following themes:
INTRODUCTION TO ERLANG AND ELIXIR
Experienced in Erlang and/or Elixir? Do you have a point of view that would help beginners who are unsure of where to dig in? In this track, you will share your experience, giving beginners a sense of the lay of the software ecosystem, help the community, and contribute back to everyone’s benefit.
Erlang and Elixir’s popularity is growing but it’s not always clear what off-the-shelf software is useful in production quality systems. We’re looking for existing production systems’ maintainers to share what they use to monitor and test their systems. This track will include the war stories and experience reports of novice and expert users alike.
Every new domain that Erlang and Elixir push into brings a new class of problems and a new class of solutions. In this track, you’ll share your experience, where things have been peachy and where they haven’t been so much. The audience will walk away with a more clear idea of how to build highly reliable software.
Calling all leading experts and Elixir committers about new language constructs, VM implementations, and powerful libraries which form the Erlang eco-system. You will share how many of its features work and how to best use them to write fast and efficient code.
In this track, leading experts and committers will present new and leading frameworks such as (but not limited to) Phoenix, MongooseIM, Nerves and RabbitMQ. They will share how these frameworks work, how to best use them and where not to use them.
DISTRIBUTION, CONCURRENCY, MULTICORE, AND FUNCTIONAL
Scaling vertically by adding more powerful hardware is a thing of the past. We scaled horizontally, by adding more commodity hardware. With mega-core architectures, we have the choice of adding more hardware, more cores, or both. Erlang-style concurrency puts us ahead of the game when it comes to scaling with both approaches.