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The Bike Shed

439: Async Ruby & Rails with Trevor Turk

34 min episode · 2 min read
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Episode

34 min

Read time

2 min

Topics

Remote Work

AI-Generated Summary

Key Takeaways

  • Async HTTP for parallel requests: Replace Typeus with async-http gem to parallelize external API calls without switching servers. AccuWeather requires six simultaneous requests that async handles efficiently, preventing serial slowdowns when APIs experience maintenance or delays.
  • Rails 7.2 fiber compatibility: Rails now checks database connections in and out per query instead of holding them until response completion. This prevents connection pool exhaustion that previously crashed databases when thousands of concurrent fiber requests attempted to open simultaneous connections.
  • Memory versus CPU constraints: Fiber-based servers like Falcon shift applications from memory-bound to CPU-bound scaling. Instead of adding dynos for RAM, monitor CPU utilization at 80 percent while staying within small dyno RAM limits for IO-heavy proxy applications.
  • Open source contribution strategies: File detailed bug reports, update documentation with working configurations, and share real-world usage patterns. Trevor's Heroku Falcon config post helped others and eventually became official documentation, demonstrating how user experience reports accelerate ecosystem maturity.

What It Covers

Trevor Turk explains how async Ruby and Falcon server enable Hello Weather to handle 500 requests per minute on three Heroku dynos, making Ruby viable for IO-heavy applications traditionally requiring Node or Elixir.

Key Questions Answered

  • Async HTTP for parallel requests: Replace Typeus with async-http gem to parallelize external API calls without switching servers. AccuWeather requires six simultaneous requests that async handles efficiently, preventing serial slowdowns when APIs experience maintenance or delays.
  • Rails 7.2 fiber compatibility: Rails now checks database connections in and out per query instead of holding them until response completion. This prevents connection pool exhaustion that previously crashed databases when thousands of concurrent fiber requests attempted to open simultaneous connections.
  • Memory versus CPU constraints: Fiber-based servers like Falcon shift applications from memory-bound to CPU-bound scaling. Instead of adding dynos for RAM, monitor CPU utilization at 80 percent while staying within small dyno RAM limits for IO-heavy proxy applications.
  • Open source contribution strategies: File detailed bug reports, update documentation with working configurations, and share real-world usage patterns. Trevor's Heroku Falcon config post helped others and eventually became official documentation, demonstrating how user experience reports accelerate ecosystem maturity.

Notable Moment

Trevor hired Samuel Williams as a coach for two weeks to deploy async Ruby. Williams discovered bugs in Heroku's Erlang-based router during the process, demonstrating how paying experts accelerates learning faster than formal education.

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