CPU Scheduling and Memory Management in Distributed Systems
Learn how CPU scheduling and memory management impact the performance and scalability of distributed systems.
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:
CPU scheduling: It determines which ready-to-run process gets to use the CPU and for how long.
Memory management: It controls how memory is allocated to processes, keeping them isolated from one another and providing abstractions like
.virtual memory A memory management technique that extends a computer's physical RAM (Random Access Memory) by using a portion of the hard drive or solid-state drive (SSD) as "virtual" RAM.
The diagram below illustrates this core relationship, showing how the
In a distributed system, these low-level decisions have magnified consequences.
Inefficient scheduling on one node can create a bottleneck that slows down the entire system, while poor memory management can lead to crashes or latency spikes that violate
Preemptive CPU scheduling
CPU scheduling determines the order in which processes are executed.
To understand this, imagine a debate: in a