An Analysis of Distributed Systems Syllabi With a Focus on Performance-Related Topics

TL;DR

This paper examines 51 distributed systems courses to understand how performance topics are integrated, focusing on teaching practices, infrastructure scale, and performance techniques used in curricula.

Contribution

It provides a comprehensive analysis of current syllabi, highlighting prevalent performance topics, techniques, and infrastructure scales in distributed systems education.

Findings

Performance and scalability are key goals in courses.

Performance benchmarking and monitoring are commonly taught activities.

Techniques like replication, caching, and sharding are frequently covered.

Abstract

We analyze a dataset of 51 current (2019-2020) Distributed Systems syllabi from top Computer Science programs, focusing on finding the prevalence and context in which topics related to performance are being taught in these courses. We also study the scale of the infrastructure mentioned in DS courses, from small client-server systems to cloud-scale, peer-to-peer, global-scale systems. We make eight main findings, covering goals such as performance, and scalability and its variant elasticity; activities such as performance benchmarking and monitoring; eight selected performance-enhancing techniques (replication, caching, sharding, load balancing, scheduling, streaming, migrating, and offloading); and control issues such as trade-offs that include performance and performance variability.