Description
This on-line course gives students an overview of the field of Cloud Computing, its enabling technologies, main building blocks, and hands-on experience through 4 projects utilizing a public cloud (Amazon Web Services). Cloud computing services are being adopted widely across a variety of organizations and in many domains. Simply, cloud computing is the delivery of computing as a service over a network, whereby distributed resources are rented, rather than owned, by an end user as a utility.
The course will introduce this domain and cover the topics of data centers, virtualization, cloud storage, and programming models. As an introduction, we will discuss the motivating factors, benefits, challenges, and service models. Modern data centers enable many of the economic and technological benefits of the cloud paradigm; hence, we will describe several concepts behind data center design and management. Next, we will focus on virtualization as a key cloud technique for offering software, computation and storage services. We will study how CPU, memory and I/O resources are virtualized, with examples from Xen and VMWare, and present real use cases such as Amazon EC2. Subsequently, students will learn about different cloud storage concepts including data distribution, durability, consistency and redundancy. HDFS, PVFS, HBASE, Cassandra and S3 will be presented as case studies. Students will understand the details of the MapReduce programming model and gain a broad overview of alternative programming models such as Pregel, and GraphLab.
Students will work with Amazon Web Services, use them to rent and provision compute resources and then program and deploy applications that run on these resources. In addition, students will work with cloud storage systems and learn to develop applications in the MapReduce programming paradigm.
The course will introduce this domain and cover the topics of data centers, virtualization, cloud storage, and programming models. As an introduction, we will discuss the motivating factors, benefits, challenges, and service models. Modern data centers enable many of the economic and technological benefits of the cloud paradigm; hence, we will describe several concepts behind data center design and management. Next, we will focus on virtualization as a key cloud technique for offering software, computation and storage services. We will study how CPU, memory and I/O resources are virtualized, with examples from Xen and VMWare, and present real use cases such as Amazon EC2. Subsequently, students will learn about different cloud storage concepts including data distribution, durability, consistency and redundancy. HDFS, PVFS, HBASE, Cassandra and S3 will be presented as case studies. Students will understand the details of the MapReduce programming model and gain a broad overview of alternative programming models such as Pregel, and GraphLab.
Students will work with Amazon Web Services, use them to rent and provision compute resources and then program and deploy applications that run on these resources. In addition, students will work with cloud storage systems and learn to develop applications in the MapReduce programming paradigm.
General Information
Course Webpage:
Course Content
Course content can be accessed via http://oli.cmu.edu. Use the course key to register for the course.
| Name | Office Hours | |
|---|---|---|
Chaomin Yu | When? Where? | |
Ge Gao | When? Where? | |
Yuefeng Zhou | When? Where? | |
Majd F. Sakr | When? Where? | |
Jason Boles | When? Where? | |
Yicheng Qin | When? Where? | |
Becket Qin | When? Where? | |
Neha Kapoor | When? Where? | |
Mingyuan Li | When? Where? | |
Zhiyu Xie | When? Where? | |
Tim Brown | When? Where? | |
Dejian Fang | When? Where? | |
Daniel Del Duca | When? Where? | |
Mohammed Suhail Rehman | When? Where? | |
Cathy Bishop | When? Where? |
General Resources
Nothing has been added to the General Resources section, yet. Stay tuned!