This training is divided into 4 parts. Each part is designed to teach you concepts about distributed systems, the ways that they fail, and how to utilize some of the tools available in erlang and elixir to help mitigate those failures.

You'll need these things installed or available in order to go through this training.

• Elixir >= 1.7
• Erlang >= 20
• Redis

Run through these steps before starting on the examples. These should help ensure that your system is set up correctly.

In other trainings we've seen issues with corporate vpns or firewalls. These issues typically cause connections to be very slow or not connect at all. You may need to temporarily disable these or add rules to allow epmd and erlang to open ports on your local machine.

If you're on macos then the first time you start a node with distribution turned on then you may see a prompt to allow epmd open network connections. You want to allow this.

You'll find it useful to run multiple nodes simultaneously for debugging and testing. There are many ways to do this such as tmux, emacs buffers, split terminal windows, or whatever other method works for you. We want to ensure that you can connect nodes together before we move on.

• Open up two terminal windows using whatever method you like.
• In window 1: run iex --name [email protected]
• In window 2: run iex --name [email protected]
• In window 1: run Node.connect(:"[email protected]")
• In window 2: run Node.list(). The output should be [:"[email protected]"]

If you have an error during any of these steps please ask Chris or Ben for help.

Part 1 provides a rough overview of connecting erlang nodes. We will see how to start processes on specific nodes, some of the failure scenarios when BEAMs disconnect, sending RPCs and other fundamental concepts.

Part 2 starts with a local only implementation of map reduce. Your task will be to make this map reduce implementation more robust against worker failure. It'll also explain message delivery guarantees and demonstrate the benefit of idempotent messages.

In Part 3 we start with a simple link shortener and make it more reliable and decrease its overall latency by replicating our state across a cluster. We'll learn about the distributed process registries available in erlang and elixir and how we can utilize them.

Part 4 builds on the latency improvements we made to our link shortener in part 3. In this section we will look at more efficient ways of replicating our state across the cluster and add aggregates for how often people view our links.

This training uses standard, distributed erlang. While there are many limitations and issues with dist-erl the goal of this training is not to promote a specific tool but instead to teach the underlying concepts that are universal to all distributed systems. Dist-erl provides the lowest barier for doing that. We make no attempt to hide the issues with dist-erl. If you need a more robust solution you should look at Partisan.