NETS 2120: Scalable and Cloud Computing (Fall 2026)
What is the "cloud"? How do we build software systems and components that scale to
millions of users and petabytes of data, and are "always available"?
In the modern Internet, virtually all large Web services run atop multiple geographically distributed data centers: Google, Yahoo, Facebook, iTunes, Amazon, eBay, Bing, etc. Services must scale across hundreds of thousands of machines, tolerate faults, and support millions of concurrent requests. The major providers (including Amazon, Google, and Microsoft) are also hosting third-party applications in their data centers - forming so-called "cloud computing" services. This course, aimed at a sophomore with exposure to basic programming within the context of a single machine, focuses on the issues and programming models related to such cloud and distributed data processing technologies: data partitioning, storage schemes, scalable analytics, and massively-parallel algorithms and data structures.
NETS2120 is a core requirement for the Data Science Minor. It counts as a project elective for
CSCI and
ASCS, and
as an AI Project Elective for the AI BSE.
Instructor
Andreas Haeberlen
Office hours: TBA (Levine 560)
Teaching assistants
Format
The format will be two 1.5-hour lectures per week, plus assigned readings. There will be regular
homework assignments with code reviews, three midterms, and a term project. We will use an online forum for course-related discussions.
Time and location
Tuesdays/Thursdays 10:15-11:45am (Location TBA)
Prerequisites
CIS 1200, Programming Languages and Techniques
CIS 1600, Mathematical Foundations of Computer Science
Textbooks
Spark: The Definitive Guide, by Bill Chambers and Matei Zaharia (O'Reilly)
ISBN 9781491912218; read online for free, or buy for approx. $54.
Additional materials will be provided as handouts or in the form of light technical papers.
Grading
Homework 20%, Term project 25%, Exams 50%, Participation/quizzes 5%
Policies
You can find a list of key course policies here.
Assignments
Homework assignments will be available for download; solutions should be submitted via GradeScope.
Tentative schedule
| Date | Topic | Details | Reading | Remarks |
|---|
| 25-Aug |
Introduction |
Course introduction
What is the Cloud, and why is it interesting?
Data-centric computing
Course goals
Logistics
Policies
|
|
|
| 27-Aug |
The Cloud |
What is the Cloud?
Cloud hardware
Problems with classical scaling
Utility computing
Kinds of clouds
Virtualization
Cloud challenges
|
Armbrust et al.: "A view of cloud computing" |
HW0 released |
| 01-Sep |
Concurrency |
Scalability and parallelization; Amdahl's law
Synchronization/concurrency/consistency
Mutual exclusing and locking
NUMA and shared-nothing
Frontend/backend
Sharding
|
Vogels: "Eventually consistent" |
|
| 03-Sep |
The Internet |
The Internet; packet switching
Path properties; TCP
HW1 overview
|
MDN: "JavaScript language overview" |
HW0 due; HW1 released |
| 08-Sep |
Faults and Failures |
Fault models
Examples of non-crash faults
Replication; durability and availability
Primary-backup replication
Quorum replication
Network partitions; CAP theorem
|
Tseitlin: "The antifragile organization" |
|
| 10-Sep |
Cloud basics |
History of cloud computing
Interacting with the cloud
EC2 basics
EBS basics
Overview of some other AWS services
|
Puthal et al.: "Cloud computing features, issues, and challenges: a big picture" |
HW1MS1 due |
| 15-Sep |
Cloud storage |
Key-value stores
KVS and concurrency
KVS and the Cloud
Case study: S3
Case study: DynamoDB
|
Cooper et al.: "PNUTS to Sherpa - Lessons from Yahoo!'s Cloud Database" |
|
| 17-Sep |
Spark |
Introduction to scalable analytics
MapReduce
The Streams API
Apache Spark
Lambdas and serialization
|
Spark textbook, Chapter 2 and 3 |
HW1MS2 due; HW2 released |
| 22-Sep |
Programming in Spark |
Spark jobs
Working with files
Spark transformations
Spark actions
The Structured API
Distributed shared variables
|
Spark textbook, Chapters 4-8 |
|
| 24-Sep |
Understanding Spark |
Origins of Spark
The HDFS file system
Using HDFS
Apache Livy
|
Zaharia et al.: "Spark: Cluster Computing with Working Sets" |
HW2MS1 due |
| 29-Sep |
(Exam) |
First midterm exam
|
|
|
| 01-Oct | Fall break (October 1-4) |
| 05-Oct | Last day to drop |
| 06-Oct |
Graph algorithms |
Distributed graph algorithms
Distributed graphs
Graph algorithms in Spark
Single-source shortest path
K-Means clustering
Naive Bayes learning
|
|
|
| 08-Oct |
Random-walk algorithms |
Random-surfer model
Naive PageRank
Full PageRank
Adsorption / label propagation
|
Baluja et al.: "Video Suggestion and Discovery for YouTube" |
HW2MS2 due; HW3 released |
| 13-Oct |
Iterative processing |
Iterative processing
Bulk synchronous parallelism
Pregel and graph processing
Overview of deep neural nets
|
Malewicz et al.: "Pregel - A System for Large-Scale Graph Processing" |
|
| 15-Oct |
Web programming |
Web overview
HTML and CSS
Client/server model
The Domain Name System
|
Ghedini et al.: "HTTP/3: The past, the present, and the future" |
|
| 20-Oct |
Web programming (continued) |
HTTP and HTTPS
HTTP/2 and HTTP/3
Server design
|
|
|
| 22-Oct |
Node.js |
Motivation: CGI and servlets
Node.js; basic operation
Hello world with Node
Accessing data
Cookies and sessions
|
"Node at LinkedIn: the pursuit of thinner, lighter, faster" |
HW3 due; HW4 and project handout released |
| 23-Oct | Last day to pass/fail |
| 27-Oct |
Dynamic content |
Project overview
Project advice
The Document Object Model
XMLHttpRequest
|
"React: Facebook's Functional Turn on Writing JavaScript" |
|
| 29-Oct |
(Exam) |
Second midterm exam
|
|
|
| 02-Nov | Last day to withdraw |
| 03-Nov |
AJAX |
AJAX overview
AJAX with jQuery
socket.io and async
Working with APIs
|
|
HW4MS1 due; team formation deadline; project begins |
| 05-Nov |
Web services |
Web services
Data interchange; challenges
Data formats
|
|
|
| 10-Nov |
Security |
Cryptography; RSA
Digital signatures
Attacks and Defenses
|
OWASP Top 10 |
HW4MS2 due; first project check-in |
| 12-Nov |
Databases |
Motivations for databases and data management
Relational model, data streams
SQL basics; declarative approach; query optimization
Transactions; ACID
|
Shute et al.: "F1: A Distributed SQL Database That Scales" |
HW4MS3 due |
| 17-Nov |
Peer-to-peer |
Decentralization
Partly centralized systems; BitTorrent
Unstructured overlays; epidemic protocols
Structured overlays; consistent hashing; KBR
Case study: Pastry
Security challenges
|
Rodrigues and Druschel: "P2P systems" |
Second project check-in |
| 19-Nov |
Case study: Bitcoin |
Distributed ledgers
Bitcoin and Proof-of-Work
Bitcoin Script
Challenges in Bitcoin
|
Nakamoto: "Bitcoin: A Peer-to-Peer Electronic Cash System" |
|
| 24-Nov |
Case study: Facebook |
Facebook's TAO
Scalability in TAO
Fault handing in TAO
Facebook's Haystack
Haystack design
|
Bronson et al.: "TAO: Facebook's Distributed Data Store for the Social Graph" |
Third project check-in |
| 26-Nov | Thanksgiving break (November 26-29) |
| 01-Dec |
Special topics |
TBA
|
|
Fourth project check-in |
| 03-Dec |
(Exam) |
Third midterm exam
|
|
|
| 08-Dec | Reading days (December 8-9) |
| 10-Dec | Finals period; in-person project demos (December 10-17) |
|
