CS6501-015: Cloud System Reliability
Fall 2023, UVA CS

Course Overview

In our increasingly digital world, the role of cloud systems is more critical than ever. As we continue to depend heavily on cloud services, understanding and reinforcing their reliability becomes a crucial aspect.

This course explores the foundational principles, practical aspects, and emerging trends in the reliability of cloud-based systems. The curriculum is structured around two aspects: first, understanding common reliability challenges in cloud systems, e.g., hardware faults, misconfigurations, etc.; and second, providing students exposure to reliable software techniques, such as program analysis and formal methods. Through critical engagement with literature discussion and course projects, students will gain a comprehensive understanding of the challenges and strategies associated with building and maintaining reliable cloud systems.

Prerequisite: Experience in CS4414 (Operating Systems), CS4434 (Dependable Computing Systems), CS6111 (Cloud Computing), or other related system courses.

Class Info

Grading

  • Reviews: 15%
  • Class Participation: 15%
  • Presentation: 20%
  • Project: 50%

Reviews

  • Students are required to review assigned readings thoroughly. These readings include seminal and contemporary research papers on cloud system reliability, which will be discussed in class.
    • Reading: Read both assigned papers before each class, making sure to understand the key points, methodologies, findings, and conclusions.
    • Review: Prepare a one-page review for one of assigned readings based on your choice, summarizing the main arguments and your own reflections. This review will be submitted before the start of each class. You are allowed to miss at maximum three reviews without receiving penalties.
      • Format: There is no strict requirement for review formats. If you need a template to start with, you can refer to the question list in How to Read an Engineering Research Paper by William G. Griswold.
      • Presenter: If you are presenting this paper in the class, you don’t need to submit the review for this class.
      • AI-tool policy: While we acknowledge the convenience of AI writing assistants like ChatGPT in the academic domain, it is crucial for students to cultivate their critical thinking and writing skills. The review should reflect your own experience and insight into the content. Students may use AI tools for brainstorming initial ideas or checking grammar errors, but the final reviews submitted must be authored by the student. Students are expected to elaborate their reviews in the class.
Violation of UVA Academic integrity: Directly copying from paper contents, peers or online resources will be considered as a violation of academic integrity and will lead to consequences.

Class Participation

  • Attendance: Regular attendance is expected and will be taken into consideration when grading class participation.
    • There will be a few quizzes regarding paper contents and reviews. Students’ answers will be part of their overall grade.
  • Engagement: You are expected to actively participate in class discussions by asking questions, sharing your thoughts, responding to your classmates’ ideas, and contributing to an inclusive and respectful classroom environment.
  • Peer Feedback: Provide constructive feedback during your peers’ presentations and contribute to post-presentation discussions.

Presentation

  • Each student will be assigned one or more research papers (based on class size) to present during the semester.
    • Preparation: Prepare a 25-30 minutes presentation on the paper, summarizing the research problem, methods, results, and implications.
    • Discussion: Be prepared to answer questions and lead a discussion about the paper after your presentation.

Project

Acknowledgements

This course is heavily influenced by other amazing system seminar courses including JHU CS624 and UIUC CS 598XU. A selection of readings and materials are incorporated from their courses. Many thanks for valuable input from Prof. Ryan Huang and Prof. Tianyin Xu to improve teaching and design of this course.