In this course, you will gain practical exposure to the skills, tools, and knowledge needed in automating software engineering processes and infrastructure necessary for continuous deployment of software. Students will have the chance to build new or extend existing software engineering tools and design an automated deployment pipeline.

In the course, a mixture of traditional lectures with activities and in-class workshops will be used. During lectures, we will cover core concepts related to a topic. During the in-class workshops, we will perform sample exercises with relevant tools that reinforce lecture material. Evaluation will be based on tech talks, homework assignments, workshop attendance, and final project.

After the course, students are able to:

• Programmatically provision images.
• Automatically apply configuration management to production environments.
• Automatically create and maintain build environments.
• Maintain test suites and measure testing quality and coverage.
• Automatically generate new tests, using feedback-directed random testing, fuzzing, and data-flow analysis.
• Programmatically measure code quality via static and dynamic code analysis.
• Understand components of infrastructure.
• Remotely regulate behavior of deployed software via feature flags and configuration servers.
• Apply advanced strategies for deployment of software.
• Monitor and analyze telemetry data.
• Implement resilience testing on production environments (e.g., Chaos Monkey).

Location: Monteith Engineering Research Center, Room 0313, 1:30-2:45pm.

The following schedule is subject to change.

Watch Lecture Videos.

The primary objective of the course will be to allow students to gain experience in incrementally building a continous delivery pipeline from scratch. Throughout the semester, students are expected to complete a component of the pipeline by each milestone deadline.

Details on requirements for milestones will be released throughout the course. A student's pipeline should demonstrate the following components by the milestone deadline:

[ CM ] -> [ BUILD+TEST+ANALYSIS ] -> [ DEPLOY ] -> [ SPECIAL ]

• Mattermost
• NC State - Stack Overflow

• An empirical study on principles and practices of continuous delivery and deployment

• Effective DevOps
• Ansible: Up and Running
• Continous Delivery
• Continous Integration
• Designing Data-Intensive Applications
• Systems Performance: Enterprise and the Cloud
• The Practice of Cloud System Administration
• DevOps: A Software Architect's Perspective, SEI

• http://newrelic.com/devops/toolset

• Spring 2019
• Spring 2018
• Fall 2017
• Spring 2017
• Fall 2016
• Spring 2015
• Fall 2015