September 19–20, 2016: Training
September 20–22, 2016: Tutorials & Conference
New York, NY

Schedule: Continuous delivery sessions

11:35am–12:15pm Wednesday, 09/21/2016
DevOps Automation, Continuous delivery Regent Audience level: Beginner
Michael Gorven (Facebook/Instagram)
Average rating: ***..
(3.75, 8 ratings)
Every time an Instagram engineer commits code to master (up to 40 times a day), it is automatically tested and deployed to a fleet of thousands of web servers in as little as 10 minutes. Michael Gorven describes the iterative approach Instagram took to build this system, the problems it faced along the way, the solutions it implemented, and the key principles which enable this to work. Read more.
2:25pm–3:05pm Wednesday, 09/21/2016
Financial systems Continuous delivery, Security Gramercy Audience level: Intermediate
Average rating: **...
(2.50, 4 ratings)
Automation has reached a point where the CI/CD workflow from commit to deploy is controlled in some way by bots. Multitenant CI/CD platforms often have permissions to access a wide range of systems and services and hence can be an attractive target for attackers. Binu Ramakrishnan highlights current security risks and CI/CD threat modeling and offers novel solutions to mitigate those risks. Read more.
4:45pm–5:25pm Thursday, 09/22/2016
DevOps Cloud, Continuous delivery Nassau Audience level: Intermediate
Yvette Pasqua (Meetup)
Average rating: ****.
(4.40, 5 ratings)
One of the most exciting (and difficult) decisions for a software company to make is to rebuild its infrastructure. But once teams are spun up and start working, then what? Yvette Pasqua, Wayne Folkes, and Alessandro Bologna offer a practical perspective on how to successfully plan, design, build, and ship infrastructure, sharing lessons from the front lines of Meetup's recent redesign. Read more.
4:45pm–5:25pm Thursday, 09/22/2016
Measuring the right things Automation, Continuous delivery Beekman Audience level: Beginner
Akshay Shah (Uber), Michael Hamrah (Uber)
Average rating: ****.
(4.80, 5 ratings)
As Uber broke its monolith into microservices, monitoring became increasingly difficult. No single service could answer a critical question: is the business running? Akshay Shah and Michael Hamrah share the challenges Uber faced when monitoring business outcomes instead of engineering metrics and why building an anomaly detection system to solve those problems is easier than you might expect. Read more.