Add an eventSessions at Google I/O 2011 in Room 6
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- Space: Room 6
Tuesday 10th May 2011
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Storing Your Application's Data in the Google Cloud
by Mike Schwartz and Navneet Joneja
Google Storage for Developers is a RESTful service for storing and accessing your data on Google's infrastructure. This 101 session shows basic examples of storing data on Google's Cloud, highlights the new features launched since Google I/O 2010, and discusses how to integrate with other Google Developer products
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Scaling App Engine Applications
by Justin Haugh and Guido van Rossum
During this talk, we’ll discuss how to write highly scalable apps on App Engine. We’ll describe how an app is granted more instances as traffic grows, and the importance of low latency, low memory usage, concurrency, async APIs, load testing, and profiling. We’ll also help you avoid common pitfalls, like entity contention and hot tablets.
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App Engine Backends
by Justin Haugh and Greg Darke
Applications written on App Engine can scale to amazing heights, but have strict limits on processing time, cpu, and memory usage. App Engine Backends have few restrictions: they can use up to 1GB of memory, 4.8GHz of CPU, are individually addressable, and have no request deadlines. We'll dive into the new kinds of programs that Backends enable and cover best practices.
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Putting Task Queues to Work
by Nicholas Verne and Vivek Sahasranaman
Does your app require software that you can't run on App Engine? By using the brand new pull based queues, you can crunch through all sorts of work like OCR, video encoding, and image manipulation in a VM. Add work to queues using App Engine's Task Queue API and process the tasks in a VM by pulling from queues using the REST API. Pull queues open up a lot of new possibilities for your apps so come and hear from the team that built this functionality and bring your questions!
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Building Enterprise Applications on App Engine
by Chris Schalk and Greg Dalesandre
As Google App Engine has evolved from it grassroots developer origins to an Enterprise ready technology, this session will lead both developer and Enterprise IT professionals on a full Enterprise development lifecycle demonstrating how to use the new features of App Engine for Business in an Enterprise context. As a summary of the talk, several existing App Engine for Business customers will share their experiences so far in using App Engine for Business during its trial period.
Wednesday 11th May 2011
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Full Text Search
by Bo Majewski and Ged Ellis
At last we are adding a full text search service to App Engine. The upcoming service will be built on top of the very infrastructure used by Google. In addition to full text search queries we will also offer numeric, geo, date search capabilities, and much more. This session will cover the basic full text search API, briefly outline more advanced features, and how full text search ties to existing services such as datastore
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Coding For The Cloud: How We Write Enterprise Apps for Google on App Engine
by Ben Fried, Justin McWilliams, Eric Schoeffler and Justin Fagnani
Google's IT department builds the enterprise apps that run Google as a company. Come hear Google's CIO and engineers talk about what they've built and learn the tips, techniques and software design patterns that you can use to build applications on App Engine.
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Fireside Chat with the App Engine Team
by Brett Slatkin, Max Ross, Guido van Rossum, Greg Dalesandre, Alon Levi, Sean Lynch, Peter S. Magnusson, Mickey Kataria and Peter McKenzie
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Smart App Design
by Travis Green, Max Lin, Robert Kaplow, Jóhannes Kristinsson and Ryan McGee
Learn how to recommend the unexpected, automate the repetitive, and distill the essential using machine learning. This session will show you how you can easily add smarts to your apps with the Prediction API, and how to create apps that rapidly adapt to new data.
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Large-scale Data Analysis Using the App Engine Pipeline API
The Pipeline API makes it easy to analyze complex data using App Engine. This talk will cover how to build multi-phase Map Reduce workflows; how to merge multiple large data sources with "join" operations; and how to build reusable analysis components. It will also cover the API's concurrency model, how to debug in production, and built-in testing facilities.
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