We used Elixir's Observer to hunt down bottlenecks

In a deep dive into optimizing resource allocation using Elixir's Observer, Sequin's team explored the challenges of dealing with machine overload despite moderate CPU utilization, highlighting how Observer helped diagnose the issue. The team used Observer to examine the scheduler's run queue and process attributes to identify bottlenecks, such as high scheduler utilization and large message queues, which indicated an overloaded machine. They learned that Erlang processes are lightweight and managed by the BEAM, which distributes CPU core time among processes efficiently, but issues can arise when processes have to wait for CPU time. To mitigate these issues, they optimized process memory usage and rearchitected processes handling excessive messages, improving system performance. Additionally, they ran experiments with the Flow library to parallelize CPU-intensive tasks, discovering the importance of cautious resource allocation to prevent starving other processes in the system. Overall, the insights gained from Observer allowed the team to better manage their system's runtime properties and prepare for future challenges.

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