While most traditional media companies have been content to treat the Internet as merely another distribution medium and their IT departments as just one more service organization, The New York Times has embraced the digital age as fervently as the most progressive technology company. From a team of engineers who sit side-by-side with journalists in the newsroom and a well-funded R&D group to a large engineering team working on a slew of Web and mobile offerings, The Times has lived by the ethos that to continue to succeed, its technology must be as great as its journalism.
CIO Marc Frons will discuss a new philosophy that has borne fruit with a successful digital subscription model and fresh innovations in user engagement and interactive storytelling. But in a world of failing print economics and increased competition for online advertising, The Times must find new ways to make quality journalism profitable online.
CTO Rajiv Pant will relay experiences on their live transition to continuous delivery, give details on experimentation with emerging production frameworks with NodeJS and Scala, discuss their innovative directions on cloud and big data, and their unique philosophy and practice on current and future mobile apps.
By now, we are all comfortable with the orthodoxy: the product owner discerns the needs of the customer and feeds them to developers in the form a prioritized backlog. Developers pull work from that backlog, always confident that they're working on the highest-priority feature at the moment, and never having to worry about how those priorities are allocated. This system is simple, efficient, and has helped many teams function better than they used to. It's also time for the system to die.
A few revolutionary companies are experimenting with the idea that developers should be in charge not only of when they build new features, but _what_features to build. Rather than mere code technicians following the will of a product and marketplace expert, developers themselves become experts in their product domain, building the tools users need-by conceiving of those tools themselves. Dispensing with the product owner creates an entirely new organizational tenor: one in which everyone is encouraged to master the business's domain, to organize their work in autonomous ways, and to take ownership of the purpose for which the organization exists.
Come listen to the the vision of an organization without product managers, explore its implications, consider its boundaries, and see if you're willing to take this bold step.
Feudalism is an apt model for security today. We pledge our allegiance to service providers, and we expect them to provide us with security in return. More and more, this security is completely opaque; we cannot audit it, and we know details about it. And, predictably, the results are all over the map.
The average cloud provider does a better job at security than the average home user, but isn't nearly secure enough to satisfy the needs of many large corporations. Navigating this new world of feudal security is going to be the major challenge in the current decade. This talk examines both the challenges and the solutions.
For the last few decades, the relational database has dominated the industry when it comes to building data-centric applications. The mathematical foundations of SQL and the relational data model were key to ignite this multi-billion dollar business since general abstract knowledge about relational databases is applicable across any concrete implementation.
Recently there has been a surge in the interest for non-relational databases ("NoSQL") and so-called "Big Data". However, the landscape of Big Data remains fragmented with many (seemingly) different implementations and approaches, unable to interoperate and seemingly distinct from each other, preventing the non-relational approach to data to reach it full potential.
To get rid of this Tower of Babel we need to seek a mathematical basis for Big Data that emphasizes the correspondences between the various solutions, as opposed to strutting about the differences.
In this talk I will break down the relational data model and build a universal theory for Big Data. In the process we'll discover how Monads and Category Theory can help us along the way, how the mathematical concept of Duality helps us make sense of the 3Vs of Big Data (Volume, Velocity, Variety), and to top it off: how any developer could have come up with all of this by remembering the design principle of separating interface and implementation.
We can only imagine how the world would look right now if 45 years ago Ted Codd would have have gone through the same design process.