CPU Scheduling and Memory Management in Distributed Systems

A service’s latency depends on both its code and the resources available to run it. This lesson connects runnable queues, memory pressure, page faults and garbage collection to observable performance. The aim is to identify a bottleneck before choosing a tuning change.

Many high-performance distributed systems encounter bottlenecks not within their application code, but at the operating system (OS) level.

A system with abundant hardware can still suffer from high latency and low throughput, often because of the fundamental decisions the OS makes every millisecond about how to allocate CPU time and manage memory. Understanding these core mechanics is critical for designing scalable and reliable systems.

This lesson examines how the OS’s CPU scheduler and memory manager operate and why their behavior is essential for building predictable, high-performance applications.

Overview of CPU scheduling and memory management

Every application running on a computer, from a web server to a database, competes for two primary resources: CPU cycles and memory. The OS acts as a traffic controller, managing access to these resources to ensure fairness and efficiency.

This management process is divided into two key areas: