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50:33

Life of a Twitter JVM Engineer

Posted by Tony Printezis  on  Apr 10, 2016

Tony Printezis presents how services are deployed and monitored at Twitter, the benefits of using a custom-built JVM, and the challenges of the use of the JVM in an environment like Twitter.

55:33

Flying Faster with Heron

Posted by Karthik Ramasamy  on  Apr 03, 2016 1

Karthik Ramasamy presents the design and implementation of Heron, the new de facto stream data processing engine at Twitter. Ramasamy shares Twitter’s experience of running Heron in production.

53:13

Analyzing Social Networks with F#

Posted by Evelina Gabasova  on  Apr 22, 2015

Evelina Gabasova explains how to run a social network analysis on Twitter and how to use data science tools to find out more about followers.

01:03:55

Scalable Big Data Stream Processing with Storm and Groovy

Posted by Eugene Dvorkin  on  Jan 18, 2015

Eugene Dvorkin provides an introduction to Storm framework, explains how to build real-time applications on top of Storm with Groovy, how to process data from Twitter in real-time, etc.

48:36

Functional Systems @ Twitter

Posted by Marius Eriksen  on  Jan 09, 2015

Marius Eriksen explains Twitter's experiences with functional programming (with Scala) @ Twitter: where functional techniques worked and where not. Also: how the Scala language has scaled with Twitter

27:24

TSAR: How to Count Tens of Billions of Daily Events in Real Time Using Open Source Technologies

Posted by Gabriel Gonzalez  on  Nov 22, 2014 1

Gabriel Gonzalez introduces TSAR (TimeSeries AggregatoR), a service for real-time event aggregation designed to deal with tens of billions of events per day at Twitter.

56:02

Real-Time Systems at Twitter

Posted by Brian Degenhardt  on  Aug 01, 2014

Brian Degenhardt discusses lessons that Twitter learned managing a high rate of change and complexity, and how those can be applied anywhere.

49:17

Scaling Engineering Culture at Twitter

Posted by Raffi Krikorian  on  Feb 25, 2014

Raffi Krikorian discusses the software engineering challenges met re-architecting Twitter and the cultural change impact that came with it.

49:30

Decomposing Twitter: Adventures in Service-Oriented Architecture

Posted by Jeremy Cloud  on  Jul 03, 2013 3

Jeremy Cloud discusses SOA at Twitter, approaches taken for maintaining high levels of concurrency, and briefly touches on some functional design patterns used to manage code complexity.

38:00

Timelines at Scale

Posted by Raffi Krikorian  on  Apr 03, 2013

Raffi Krikorian explains the architecture used by Twitter to deal with thousands of events per sec - tweets, social graph mutations, and direct messages-.

17:55

Zipkin: a Distributed Tracing Framework

Posted by Johan Oskarsson  on  Feb 08, 2013

Johan Oskarsson explains how Twitter is using Zipkin to trace a pages in order to see their execution path and to determine the time spent for loading for performance monitoring and analysis.

Scaling Scalability: Evolving Twitter Analytics

Posted by Dmitriy Ryaboy  on  Jan 13, 2013

Dmitriy Ryaboy shares some of the lessons learned scaling Twitter’s analytics infrastructure: Data loves a schema, Make data sources discoverable, and Make costs visible.

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