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An updated and curated list of readings to illustrate best practices and patterns in building scalable, available, stable, performant, and intelligent large-scale systems. Concepts are explained in the articles of prominent engineers and credible references. Case studies are taken from battle-tested systems that serve millions to billions of users. Understand your problems: scalability problem (fast for a single user but slow under heavy load) or performance problem (slow for a single user) by reviewing some design principles and checking how scalability and performance problems are solved at tech companies. The section of intelligence are created for those who work with data and machine learning at big (data) and deep (learning) scale.
The worker pool distributes work across the workers to the least loaded worker. The pool was tested by a load generator that produces tasks at a inconsistent interval, faster than the time it takes to complete the tasks itself. The tasks also take an inconsistent amount of time to finish. In this example the tasks were just sleeps.