Mārtiņš Kalvāns and Matti Pehrs overview the Data Infrastructure at Spotify, diving into some of the data infrastructure components, such us Event Delivery, Datamon and Styx.
Chun-Ho Hung and Nikhil Garg discuss Quanta, Quora's counting system powering their high-volume near-real-time analytics, describing the architecture, design goals, constraints, and choices made.
Eric Bottard and Ilayaperumal Gopinathan discuss easy composition of microservices with Spring Cloud Data Flow.
Gil Tene presents the current state of Java SE and OpenJDK, the role of Java in the Big Data and Infrastructure components, JCP, the ecosystem, trends, etc.
Marius Bogoevici demonstrates how to create complex data processing pipelines that bridge the big data and enterprise integration together and how to orchestrate them with Spring Cloud Data Flow.
Thomas Risberg discusses developing big data pipelines with Spring, focusing around the code needed and he also covers how to set up a test environment both locally and in the cloud.
Nivesh Gopathi describes the use cases for dynamic configuration and application secrets management, and how GapTech are solving these at scale using Spring Cloud Config, Vault and Consul.
Jie Yu discusses how containers are managed in Mesos, the future of container support in Mesos, and shows some of the new container networking and storage features.
Clint Checketts discusses the concerns to consider when rolling out a config server around security, encryption, and location of repositories, and Config Server's extensibility.
Uses of Big Data by a Non-Profit Engaged in Conducting Events Funded in Part by Third Party Sponsors
Thomas Grilk discusses how a non-profit can efficiently use data from customers/athletes in its marketing and sponsorship activities while respecting the privacy and confidentiality of its customers.
Preslav Le talks about how Dropbox’s infrastructure evolved over the years, how it looks today, as well the challenges and lessons learned on the way.
Rajat Monga talks about why Google built TensorFlow, an open source software library for numerical computation using data flow graphs, and what were some of the technical challenges in building it.