15-719 Advanced Cloud Computing (Spring 2017)


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.

Learning Goals

Students 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 Objectives

Specific 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.
  • Instructors (719-staff at mailman dot srv dot cs dot cmu dot edu)

    Picture of Greg Greg Ganger CIC 2208 (412) 268-1297 TBD,
    CIC 2208
    Picture of Majd Majd Sakr GHC 7006 (412) 268-1161 Tues 3-4pm,
    GHC 7006
    Picture of George George Amvrosiadis CIC 2311 (412) 268-xxxx TBD,
    CIC 2311
    Picture of Alex Alex Glikson TBA,
    GHC 5th Floor
    Picture of Michael Michael Kuchnik TBA,
    GHC 5th Floor
    Picture of Kevin Kevin Hsieh TBA,
    GHC 5th Floor
    Picture of Andrew Andrew Chung TBA,
    GHC 5th Floor
    Picture of David David Dai TBA,
    GHC 5th Floor
    Picture of Pooja Pooja Nilangekar TBA,
    GHC 5th Floor
    Picture of Yiyun Yiyun Yao TBA,
    GHC 5th Floor
    Picture of Shangjie Shanjie Chen TBA,
    GHC 5th Floor

    Last updated: 2017-03-02 18:53:37 -0500