Computing in the cloud has emerged as a leading paradigm for cost-effective, scalable, well-managed computing. Users pay for services provided in a broadly shared, power efficient datacenter, enabling dynamic computing needs to be met without paying for more than is needed. Actual machines may be virtualized into machine-like services, or more abstract programming platforms, or application-specific services, with the cloud computing infrastructure managing sharing, scheduling, reliability, availability, elasticity, privacy, provisioning and geographic replication.
This course will survey the aspects of cloud computing by reading about 30 papers and articles, executing cloud computing tasks on a state of the art cloud computing service, and implementing a change or feature in a state of the art cloud computing framework. There will be no final exam, but there will be two in class exams. Grades will be about 50% project work and about 50% examination results.
This class is supported in part by a AWS in Education Grant award.
- Lecture time: MW 16:40 - 18:00, starting January 19
- Units: 12
- Prerequisites: 15-213, 18-213, 15-513, 18-600 from CMU, with a grade of at least a B (or 15-619 with at least A-).
- Location: DH 2315 (remote only when required by CMU policy)
- Communicating with course staff: https://piazza.com/cmu/spring2022/15719/home (you must be invited into this Piazza site by course staff after you have been accepted into the class)
- Web site: www.cs.cmu.edu/~15719
- Syllabus: PDF
Learning GoalsStudents completing Advanced Cloud Computing will develop a broad based understanding of state-of-the-art technologies, underlying business and technological trends, key systems and artifacts and research directions in modern data center computing, scalable distributed systems, and programming frameworks enabling the widespread adoption of cloud computing. Many will go on to code, design and architect innovative new cloud computing services and offerings, and to develop business processes to exploit opportunities afforded by modern cloud computing.
Learning ObjectivesSpecific skills learned and outcomes achieved by graduates of this course include:
- Describe, explain, justify, and criticize differing perspectives on the definition, novelty, and essential features of state of the art cloud computing.
- Design and implement distributed systems for big data science applications to operate in and exploit advanced features of cloud computing systems.
- Design, criticize, implement and improve features of large scale cluster computing, with emphasis on scale elasticity, limitations on unusually long duration corner cases, high availability in the face of rare and dependent failure modes.
- Interpret and criticize cloud computing research papers, and anticipate and design strategies to avert structural or implementation problems identified.
Who We Are
|Greg Ganger||CIC 2208||(412) 268-1297|
|Majd Sakr||GHC 7006||(412) 268-1161|
Course Staff and Teaching Assistants
|Name||Office Hours (Timezone is EST)||Location|
|Ting Chen||Tue 6.30-8.30pm||Zoom + OHQ|
|Yun Hong||Wed 1-3pm||Zoom + OHQ|
|Michael Kuchnik||Tue 1-3pm||Zoom + OHQ|
|Xuanyi Li||Fri 5-7pm||Zoom + OHQ|
|Hojin Park||Mon 11am-1pm||Zoom + OHQ|
|Ge Song||Fri 4-5pm; Sat 4-5pm||Zoom + OHQ|
|Scarlett Song||Tue 10am-12pm||Zoom + OHQ|
|Weitao Tan||Thu 7.30-9.30pm||Zoom + OHQ|
|Yida Wu||Sun 10.15am-12.15pm||Zoom + OHQ|