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League of Legends: Scaling to Millions of Ninjas, Yordles, and Wizards

Posted by Scott Delap and Randy Stafford  on  Apr 07, 2011 2

Scott Delap and Randy Stafford explain the architectural decisions made in order to scale, monitor and operate 24/7 the game League of Legends, bringing insight on how they use Oracle Coherence for that.

Yes, SQL!

Posted by Uri Cohen  on  Mar 01, 2011

Uri Cohen presents the key characteristics of SQL and NoSQL databases and how to create a layer on top of distributed data stores in order to use SQL to query for data. For further information please contact Gigaspaces.

Advanced GORM - Performance, Customization and Monitoring

Posted by Burt Beckwith  on  Jan 27, 2011 3

Burt Beckwith discusses potential performance problems using mapped collections and Hibernate 2nd-level cache in GORM, along with strategies for avoiding such performance penalties.

Squid Wrangling

Posted by Sam Newman and Chris Read  on  Jan 14, 2011

Sam Newman and Chris Read describe the architectural change of a large European website by introducing a caching layer based on Squid in order to scale out to handle increased demand, and the cultural change done by breaking down the dev-ops silos.

Scaling Australia's Most Popular Online News Sites with Ehcache

Posted by Ari Zilka and Matthias Matook  on  Dec 06, 2010 4

Matthias Matook and Ari Zilka share the real-world experience of implementing Enterprise Ehcache at Australia's most visited online news sites. The talk will focus on the challenges and technical solutions to deal with massive page hits, high concurrency and how to achieve linear scalability without additional hardware.

Scaling Your Cache & Caching at Scale

Posted by Alex Miller  on  Jun 07, 2010

Alex Miller explains shortly why caching is useful, followed by examples of typical difficulties encountered when setting up a cache, like large datasets, data eviction, stale data, replication, loading, duplication. Miller also discusses available choices for designing a distributed caching architecture, and ways to test a cache for performance.

Scale at Facebook

Posted by Aditya Agarwal  on  May 28, 2010 3

Beside presenting the overall Facebook architecture and scaling solutions used, Aditya Agarwal talks about the iterative process of constantly improving the site, making sure to avoid over-engineering and adapting along the way by dropping solutions that worked in the past but are no longer useful. The last part of the session was dedicated to answering questions from the audience.

Horizontal Scalability via Transient, Shardable, and Share-Nothing Resources

Posted by Adam Wiggins  on  Apr 20, 2010 1

Adam Wiggins believes that now is the time of horizontal scalability achieved by using resources that are transient, shardable and share nothing with other resources. He gives as example several applications and a language: memcached, CouchDB, Hadoop, Redis, Varnish, RabbitMQ, Erlang, detailing how each one applies those principles.

Evolving the Key/Value Programming Model to a Higher Level

Posted by Billy Newport  on  Jan 19, 2010 6

In this presentation from QCon San Francisco 2009, Billy Newport discusses the ways that developers interact with key/value (KV) stores such as memcached and WebSphere eXtreme Scale, entity vs column-oriented approaches, synchronous and asynchronous operations, large data sets, using a DBMS as a column store, collocating closures and data, and features that could be added to increase scalability.

A Crash Course in Modern Hardware

Posted by Cliff Click  on  Jan 12, 2010 17

In this presentation from the JVM Languages Summit 2009, Cliff Click discusses the Von Neumann architecture, CISC vs RISC, the rise of multicore, Instruction-Level Parallelism (ILP), pipelining, out-of-order dispatch, static vs dynamic ILP, performance impact of cache misses, memory performance, memory vs CPU caching, examples of memory/CPU cache interaction, and tips for improving performance.

Data Grid Design Patterns

Posted by Brian Oliver  on  Nov 04, 2009

Brian Oliver explains a number of data grid design patters: Command, Functor, Store and Forward Messaging, and Push Replication. He also mentions some traditional patterns used so far and Coherence Incubator, a repository for design patterns reference implementations.

An Introduction to Data Grids

Posted by Cameron Purdy  on  Oct 10, 2009 1

Cameron Purdy explains how a data grid functions by using a partition topology for data access, update, recovery and local storage, accessing data using read/write-through and write behind, and invoking operations through Observable, QueryMap and InvocableMap interfaces. He also offers some examples of data grids solving complex problems and introduces Coherence, Oracle’s data grid solution.

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