How to Stop Failures From Spreading Between Services
The article outlines practical runtime patterns that prevent failures from cascading across microservices. It covers downstream safeguards such as timeouts, retries with exponential backoff and jitter, and circuit breakers, then shifts to upstream controls like load shedding, load leveling, rate limiting, and constant‑work techniques. The author emphasizes wrapping these mechanisms in reusable libraries or sidecar proxies to ensure consistency. By applying these tactics, engineers can contain faults with minimal code changes and improve overall system resilience.
How Machine Learning and Optimization Work Well Together
Tim Varelmann, founder of Bluebird Optimization, explains how machine learning (ML) and mathematical optimization complement each other in real‑world decision making. He identifies three repeatable patterns—handling uncertainty with probabilistic forecasts, replacing costly physics equations with surrogate ML models, and optimizing...
Linear Regression
The 170th Polymathic Engineer newsletter breaks down linear regression, the cornerstone of machine learning, from intuition to mathematics. It walks readers through a salary‑prediction example, explains features, weights, bias, and error minimization, then expands to multivariate and polynomial regression. The...