15-319 / 15-619 - Cloud Computing (Online)
All projects will be done on Amazon Web Services.
This course is supported by AWS in Education Coursework Grant award
All project descriptions are on the OLI course page.
|Project Name||Description||Date Assigned||Due Date|
|AWS Account Setup||Students will first setup their AWS accounts for use in the course.||15 Jan 2013||20 Jan 2013|
Students will use Amazon AWS and provision their first compute resources. Students will work with provisioning management software and launch instances on Amazon EC2. Students will learn benefit and tradeoffs of running programs in parallel versus sequential. Students will have to solve a problem using resources provisioned in Amazon within particular cost constraints.
AMI ID for this Project: ami-ed30ba84
|22 Jan 2013||
EC2 Provisioning, EC2 Performance, Amazon S3:
Elastic MapReduce and Apache Whirr: 3 Feb 2013
Email Analysis: Sequential, MapReduce and Bonus:
|Project 2||Students will work on Virtualization Technologies. Students will observe and quantify provisioning variation on public clouds within and across instance types;
learn about various virtualization suites and observe differences between full and para virtualization as well as virtual machine isolation; Students will learn
to use the Amazon AWS SDK to manage and monitor EC2 instacnes, as well as scale them manually and automatically.
AMI ID for Provisioning Variation, Network Bandwidth Analysis: ami-3b44d352
AMI ID for Provisioning Variation in Larger Instances: ami-e15ccb88
AMIs for Managing Cloud Resources: Workload AMI: ami-2200904b and Management AMI: ami-3b44d352
AMI ID for AutoScaling: ami-92b82afb
Provisioning Variation, Network Bandwidth Analysis and Provisioning Variation in Larger Instances: 12 Feb 2013
Virtualization Taxonomy, Para vs. Full Virtualization and Virtual Machine Isolation: 19 Feb 2013
Launch and Monitor EC2 Instance using the Amazon SDK and Manual Scaling: 26 Feb 2013
AutoScaling: 5 Mar 2013
|Provisioning Variation, Network Bandwidth Analysis and Provisioning Variation in Larger Instances: 17 Feb 2013
Virtualization Taxonomy, Para vs. Full Virtualization and Virtual Machine Isolation: 24 Feb 2013
Launch and Monitor EC2 Instance using the Amazon SDK and Manual Scaling: 3 Mar 2013
AutoScaling: 17 Mar 2013
|Project 3||Students will work on cloud storage technologies and evaluate their strengths and weaknesses. Students will compare and contrast flat files and databases for storing structured infromation. Students
will also compare different storage backends on Amazon to compare their performance for an OLTP benchmark. Students will then implement a vertically scaling database using the AWS tools. Finally,
students will work with Amazon DynamoDB (a NoSQL database) to create an Image archive that is reachable from a web interface.
AMI ID for Files vs. Database: ami-fab52b93
AMI ID for Vertical scaling: ami-fab52b93
AMI ID for Horizontal scaling: ami-fab52b93
AMI ID for Amazon DynamoDB: ami-acf963c5
Files vs. Database and Vertical Scaling: 3/19/2013
Horizontal Scaling: 3/26/2013
Amazon DynamoDB:: 4/3/2013
Files vs. Database and Vertical Scaling: 3/24/2013
Horizontal Scaling: 3/31/2013
Amazon DynamoDB:: 4/7/2013
|Project 4||Students will work on developing applications using the MapReduce programming model. Students will write their own MapReduce code using Apache Hadoop and provision instances on Amazon EC2 to run them. This project will tie together knowledge gained through the completion of the previous projects.
AMI ID for MapReduce: ami-d885e0b1
Hadoop MapReduce and Project 4 Survey: 4/09/2013
NGram Generation: 4/16/2013
Language Model Generation: 4/23/2013
Hadoop MapReduce and Project 4 Survey: 4/14/2013
NGram Generation: 4/21/2013
Language Model Generation: 5/3/2013