4 HN users recommended this talk5 months2023–2025score 6
Years with an HN recommendation, 2007–2026
HN recommends it as a rare real-world look at a large fault-tolerant Erlang/Elixir system with no downtime in healthcare.
Bryan Hunter's GigCityElixir 2023 talk on HCA Healthcare's Waterpark system, built on Elixir/Erlang. It describes how the architecture is distributed and fault-tolerant, with a multi-datacenter cluster and runtime code swapping.
“an excellent presentation of design/architecture of a Real-World fault-tolerant and distributed System in Erlang/Elixir” (HN, 2023)
After watching the above which gives one an idea of the Erlang System's capabilities, watch this presentation by Bryan Hunter where the design and architecture of a complete distributed and fault-tolerant Erlang/Elixir system is shown; You get to really see the mind-blowing power of the Erlang System in this - [this video]
Complete distributed fault-tolerant Erlang/Elixir system architecture
This video may be of interest to you: [this video] Bryan Hunter explains how they do it at HCA healthcare (not specifically LiveView process, but processes in general).
This is a talk about a large scale, resilient elixir/erlang deployment in healthcare. Specifically they talk about running with no down time using hot code reloading here: [this video] but the whole talk is quite interesting regarding availability. Warning: the video is quite quiet.
Large-scale resilient healthcare deployment with no downtime
To add to this topic, people who do not know about erlang's hot code loading should watch this talk : [this video] A multi-DC running cluster where parts are progressively swapped at runtime. No database, only OTP.
Multi-DC cluster with parts progressively swapped at runtime
We use it across multiple versions of our software running in the same cluster. As long as you dark launch API changes, it's not much of an issue. [this video] (Doh, just realized I was replying to Mr. Elixir himself! And you're familiar with our project anyway :)
We use something like this at scale, similar to Riak's design. We use it to store things like the active state of millions of hospital patients in RAM for high availability (zero downtime when DCs or nodes fail). One copy per data center with a writer at one of the DCs. Our current cluster has 32 nodes (8 per DC -- we should have 5 DCs across the US but only have 4 at the moment). You can learn more about it here: [this video] .
Describes the commenter's production system for patient state in RAM
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