Really like how you frame refactoring as a learning exercise: solve it your own way first, then study and reshape a provided solution to truly understand it. Having each iteration captured in a Git repo with npm run stepX is a great way to make improvements measurable and reversible. It reminds me of experimenting in Solar Smash —small steps, clear feedback, better outcomes.

This is a really interesting overview of failure detection! I agree that the fixed timeout approach has its limitations. It's cool how Phi Accrual Failure Detection adapts based on historical data, offering a more nuanced suspicion level. Makes you think about other areas where adapting to context could improve system performance. Reminds me of a simple game I play sometimes to relax, , where you have to constantly adapt to the changing terrain!