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SpringOne2GX 2014 Replay: Scalable Big Data stream processing with Storm and Groovy

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SpringOne2GX 2014 Replay: Scalable Big Data stream processing with Storm and Groovy

· Java Zone
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Learn how to troubleshoot and diagnose some of the most common performance issues in Java today. Brought to you in partnership with AppDynamics.

Speaker: Eugene Dvorkin

More Groovy Track

Slides: http://www.slideshare.net/SpringCentral/storm-twtterwebmd

With advances in distributed computing and creation of frameworks like Storm and Spark, building real-time, fault-tolerant, and scalable solutions to process huge volume of data in real-time has become easy. Storm is one of the most popular framework to develop real-time analytics and event processing applications. Storm enables to tackle real-time Big Data challenges the same way Hadoop enables batch processing of Big Data. One of the use cases of Storm is processing feeds from social networks in real-time. Social networks like Twitter, Facebook, LinkedIn, Google+ became part of our life. By analyzing social networks, companies can process important information about their product, services, and provide real-time information to customers. In this talk, Eugene will provide introduction to Storm framework, explain how to build real-time applications on top of Storm with Groovy, how to process data from Twitter in real-time and architectural decision behind WebMD MedPulse mobile application.

Understand the needs and benefits around implementing the right monitoring solution for a growing containerized market. Brought to you in partnership with AppDynamics.

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