Matthew Mark Miller discusses Kubernetes’ primitives and microservices patterns on top of them, including rolling deployments, stateful services and adding behaviors via sidecars.
Alan Barrington-Hughes and Pavithra Ramaswamy discuss key concepts in agile database refactoring, demonstrating a no outage deployment with nginx using a blue-green method.
Nick Beenham describes how the Enterprise Services Team at Comcast transformed from large monolithic deployments with cycle times of anything from 90 days to cycle times measured in hours.
The authors discuss the top lessons learned from building a fully integrated developer platform, leveraging Cloud Foundry and OpenStack, answering questions from the audience.
John Northrup demonstrates how GitLab helps developers along their entire workflow from first commit, issue tracking, continuous integrations, and deployment into Pivotal Cloud Foundry.
Colin Humphreys talks about how the Cloud Foundry community deploys the distributed system powering the one of the most successful open source platforms, along with details on the tooling used.
Casey West uses twelve-factor app essay as a guide to discuss the do’s and dont’s of building and running containers, each factor providing an opportunity to consider avoiding certain anti-patterns.
David Xia explains how Helios testing framework drives integration tests and spins up self-contained environments during test runs, increasing Spotify’s code quality and successful deployments.
Craig Walls and Roy Clarkson introduce the capabilities provided by Spring Cloud Services and demonstrate how to deploy cloud native applications to Cloud Foundry.
Andrew Spyker and Sharma Podila talk about the motivations and the technology powering container deployment on top of the AWS EC2 service, sharing results and lessons learned.
Jamshid Mahdavi explains how WhatsApp has developed their server components, the deployment processes, and how they monitor, alert, and repair the inevitable failures in a billion-users service.
Tony Printezis presents how services are deployed and monitored at Twitter, the benefits of using a custom-built JVM, and the challenges of the use of the JVM in an environment like Twitter.