Welcome to the graduate course on Cloud Computing

Cloud computing serves many large-scale applications ranging from search engines like Google to social networking websites like Facebook to online stores like Amazon. More recently, cloud computing has emerged as an essential technology to enable emerging fields such as Artificial Intelligence (AI), the Internet of Things (IoT), and Machine Learning. The exponential growth of data availability and demands for security and speed has made the cloud computing paradigm necessary for reliable, financially economical, and scalable computation. The dynamicity and flexibility of Cloud computing have opened up many new forms of deploying applications on infrastructure that cloud service providers offer, such as renting of computation resources and serverless computing.

This course will cover the fundamentals of cloud services management and cloud software development, including but not limited to design patterns, application programming interfaces, and underlying middleware technologies. More specifically, we will cover the topics of cloud computing service models, data centers resource management, task scheduling, resource virtualization, SLAs, cloud security, software defined networks and storage, cloud storage, and programming models. We will also discuss data center design and management strategies, which enable the economic and technological benefits of cloud computing. Lastly, we will study cloud storage concepts like data distribution, durability, consistency, and redundancy. 


Lecture Info



Undergraduate-level Operating System or a similar course is preferred. This course assumes familiarity with systems, including how operating systems work and how networks work. If you don’t have this background, you should be in communication with me (the instructor) at the beginning of the semester.


Who is this course for?

This course is primarily intended for graduate students and motivated seniors who want to learn the latest research advances in distributed systems and cloud computing areas, and are interested in building cloud-based distributed systems used/demanded by existing/emerging data-intensive applications.


Grading policy

Your grade will be calculated as follows:


Grading rules

The final grade is computed according to the following rules:


Late Days

Each student will be granted 5 late days to use for the homework. After all free late days are used up, the penalty is 10% for each additional late day. Late days can not be used for the mid-way and final research presentation.


Student Integrity

Cheating in this course will result in a grade of F for the course and the University policies will be followed.


Students with Disabilities

If you need any accommodation, you are highly encouraged to contact both your instructor and Disability Resources Center (DRC).


Office hours

Course Schedule

The course schedule is tentative and subject to change.

Lecture Date Topic Required Readings Optional Readings Announcements

Tue: Sept 5

Introduction and Logistics

Armbrust2010, Vaquero11

Rackspace2012, Shafii2012, DeanSOSP2015, Cano2016, Vieira2012, Vogels2016, reiss2012, Ferguson2012, Rajagopalan2013, Das2013 Assignment 1: student info
2 Thu: Sept 7 Introduction to Cloud Computing


3 Tue: Sept 12 Virtualization I







4 Thu: Sept 14 Virtualization II



Proposal literature review due: Sept 26th

Coding Assignment 1 due: Sept 30th

5 Tue: Sept 19

Containers I

Namespaces in operation,
CGroups documentation

VM lighter than container,
6 Thu: Sept 21 Container II

Docker docs,
Docker architecture

Improving Docker registry Homework assignment 2: due date Oct 5th
  Tue: Sept 26 Project Ideas Discussion



Proposal and literature review due Today

7 Thu: Sept 28 Cloud Storage

GFS Paper,

HDFS Paper

Hadoop Architecture Guide  
8 Tue: Oct 3 Consistency Models

Visual Guide to NoSQL Systems,
Delta Store (Meta),
BespoKV paper

Chain Replication,
9 Thu: Oct 5 Key-Value Stores

Scaling Memcached at Facebook,

10 Tue: Oct 10 Programming Model I


Hadoop vs Spark,
MapReduce Architecture,
11 Thu: Oct 12 Programming Model II

Pocket paper

A Berkeley View on Serverless Computing,
A Berkeley View of Cloud Computing,
The Wukong paper

Mid Project discussions and presentations start next week.
  Tue: Oct 17

Patient API,
Incident Migration,
AutoScale KV store

Project Discussions

  Thu: Oct 19

Harmful Post Detection,
Distributed Fuzzy Inference

Project Discussions

  Tue: Oct 24

Incentivized Collaboration,
Distributed Movie Recommendation,
Model Splitting for Distributed ML

Project Discussions

12 Thu: Oct 26 Serverless Caching


AWS Lambda

 Coding Assignment 2: due Nov 5th
13 Tue: Oct 31 Serverless Storage + Parallel Processing


Hacker News,
14 Thu: Nov 2 Serverless Parallel Processing + Cloud Control Operations


Wukong Docs  
15 Tue: Nov 7 MapReduce Scheduling


MapReduce Heterogeneity  
16 Thu: Nov 9 Coding Assignment 2 design discussion + Demo +
Cloud Resource Management I



Mesos Video  
17 Tue: Nov 14 Cloud Resource Management II

Google Borg,
Borg: the next generation,
Alibaba Trace Analysis,
Borg to Kubernetes

Alibaba Microservice Trace Analysis,
Borg Video
 Coding Assignment 3: due Nov 20th
18 Thu: Nov 16 Deep Learning in Cloud


Why Ray?,
Spark Summit,

Parameter Server

19 Tue: Nov 21 Deep Learning in Cloud II / Federated Learning as a Service


  Thu: Nov 23 Thanksgiving Break


20 Tue: Nov 28 Communication in FL


  Thu: Nov 30

 Patient API,
 Incident Migration,
 Auto Scale KV Store

Project Presentations

   Homework Assignment 3: due Today
  Tue: Dec 5

Harmful Post Detection,
Distributed Fuzzy Inference,
Incentivized Learning

Project Presentations

  Thu: Dec 7

Model Splitting for ML,
Online Movie Rec.

Project Presentations

  Tue: Dec 12 Final Report Discussion




Final Project 

The research project can be done in a group of 2 to 3 students. The project will be judged on the following criteria:

Project Proposal Report

Recommended structure for the Proposal Report is:

Mid-way Project Presentation

You should present the current progress of your final project including design, related work review, any results if you have some (to show motivation or evaluation).


Final Project Presentation

You should present the final project including design, related work, and final results to showcase your project.


Project Final Report

The final deliverable of this course is a conference-quality paper. Focus on the following Questions 0 through 5 (an extended version of Question 0 through 3 in the Checkpoint Report requirement):

As well as pay attention to:

It is common that the implementation or experimental methodology gets adapted in the course of your investigation. And therefore, given that this is your final write-up, please make sure to refine/change/expand based on your mid-way presentation feedback to reflect your latest implementation & evaluation activities.

Leaderboard - KV performance


Group Members Throughput 3 KV Stores Average Latency Ranking
Tejasvi Bansal, Rishabh Agarwal 7362 3.1 ms  
Ammar Ahmed, Connor Howe 8240 2.87 ms  
Xinran Wang, Jiaxiang Tang, Minrui Tian 7900 3.20 ms  
Jon Meshesha, Andrew Owens 4456 3.53 ms  
Pat Johnson 9572 3.1 ms  
Leo Dong, Michael Andrev, Apekshik 30332 1.43 ms 2nd           image.png
Sahil Raina, Jingxian Chai, Shunichi Sawamura 25588 2.9 ms 3rd             image.png
Aahan Tyagi, Hemanth Kumar, Vishal Kancharla 83865 3.2 ms 1stimage.png