Rob Witoff presents how JPL and the Curiosity rover mission use cloud computing, including EC2, CloudFormation, and Simple Workflow - to enable research, engineering and operations technologies.
Oleg Zhurakousky discusses architectural tradeoffs and alternative implementations of real-time high speed data ingest into Hadoop.
Debbie Madden discusses the types of attributes intrapreneurs have in common, how one can identify an intrapreneur, and what can be done to impact technical innovation from a human perspective?
Reza Rahman examines the efforts under way with JSR 356 to support WebSocket from its base-level integration in the Java Servlet and Java EE containers to a new API and toolset included in Java.
Mike Nolet shares lessons learned scaling AppNexus and architectural details of their system processing 30TB/day: Hadoop, DNS built in GSLB and Keepalived, and real-time data streaming built in C.
Runar Bjarnason explains how to approach I/O from a purely functional perspective, exploring the space of existing solutions, their benefits, and drawbacks.
Tim Berglund shares the vision of an organization without product managers with its implications and boundaries, provoking the listener to take a bold step into that direction.
Rich Hickey discusses how a functional database can impact the programming model, using Datomic as an example, but the principles apply to other systems using an immutable database.
Do Agile Methods Contain the Seeds of Their Own Destruction? (Safety and Our Ability to Learn from Failure)
Amr Elssamadisy explores the link between safety and success of agile methods, explaining what can be done to change the culture of an organization to create a base where agile methods can flourish.
Jim McCarthy discusses culture hacking, expressing a particular hacker ethos originating in the world of software hacking, promoting freedom, openness, and embodying rationality and design elegance.
Jim Webber explains how to understand the forces and tensions within a graph structure and to apply graph theory in order to predict how the graph will evolve over time.
Uri Laserson reviews the different available Python frameworks for Hadoop, including a comparison of performance, ease of use/installation, differences in implementation, and other features.