Sudhir Tonse presents Netflix' composable PaaS built with several components that have been open sourced.
Sebastian Stadil advises on selecting the right cloud from EC2, GCE, or OpenStack based on one's needs, outlining the deployment and administrative challenges to be faced with each option.
Anil Madhavapeddy suggests a different approach to building Internet services avoiding the complexity of today's services which incorporate many policies and security mechanisms.
Brenden Matthews describes the infrastructure built at Airbnb using Mesos in order to support Hadoop and Storm.
Details on Pinterest's architeture, its systems -Pinball, Frontdoor-, and stack - MongoDB, Cassandra, Memcache, Redis, Flume, Kafka, EMR, Qubole, Redshift, Python, Java, Go, Nutcracker, Puppet, etc.
Daniel Cukier shares insight in using cloud services to scale web applications, dealing with load balancing, session sharing, email, asynchronous processing, logging, monitoring, CD, RUM, etc.
Rachel Laycock advises on designing systems for rapid deployment, avoiding delivering pitfalls by using micro services and evolutionary architecture.
Clayton Bauman introduces Babel, an open source language implemented in C, targeted for cloud computing. Other features: interpreted, untyped stack-based, postfix, supports arrays, lists and hashes.
Dianne Marsh presents the open source tools used by Netflix to keep the continuous delivery wheels spinning.
Ben Christensen describes how the Netflix API evolved from a typical one-size-fits-all RESTful API designed to support public developers into a web service platform optimized to handle the diversity and variability of each device and user experience. The talk will also address the challenges involving operations, deployment, performance, fault-tolerance, and rate of innovation at massive scale.
Jim Driscoll discusses using ADFm to create and change Groovy scripts at runtime and debugging a live system with JWDP.
Jeremy Edberg discusses how Netflix designs their systems and deployment processes to help the service survive both catastrophic events like zone and regional outages and less catastrophic events like network latency and random instance death.