Sign-up here: http://www.meetup.com/Cascading-New-York-Metro/events/212056932/
When:
Wednesday, October 15, 2014
6:30 PM
Where:
Twitter NYC office
340 Madison, 6th Floor
New York, NY
What:
Please join us for our October Elasticsearch meetup at Twitter featuring speakers from Elasticsearch, Found AS, Concurrent, and food and drinks.
Speaker Bios:
Elasticsearch: Costin Leau is an engineer at Elasticsearch, leading the Hadoop efforts. An open-source veteran, Costin led various Spring projects and authored an OSGi spec. Speaker at various editions of EclipseCon/OSGi DevCon, JavaOne, Devoxx/Javapolis, JavaZone, SpringOne, TSSJS on Java/Spring/Hadoop related topics.
Found AS: Konrad Beiske is a senior software engineer at Found AS, a company whose primary product is a hosted Elasticsearch service. Konrad holds a Master’s Degree in Computer Science, with an emphasis on databases and distributed systems. He has been focusing on Elasticsearch during the past two years. Konrad gives presentations about Elasticsearch and distributed systems at meetups and conferences, and he writes regularly on the Foundation blog.
Konrad will be presenting on Elasticsearch in Production — things to think about before going into production with your Elasticsearch implementation.
Concurrent: Supreet Oberoi is the Vice President of Field Engineering at Concurrent. Prior, as the Director of Big Data application infrastructure for American Express, he led the development of use cases for fraud, operational risk, marketing and privacy on Big Data platforms. He is a holder of multiple patents in data engineering and has also had leadership roles at Real-Time Innovations, Oracle and Microsoft.
Supreet will be presenting on “Large scale log processing with Cascading & Elastic Search”. Elasticsearch is becoming a popular platform for log analysis with its ELK stack: Elasticsearch for search, Logstash for centralized logging, and Kibana for visualization. Complemented with Cascading, the application development platform for building Data applications on Apache Hadoop, developers can correlate at scale multiple log and data streams to perform rich and complex log processing before making it available to the ELK stack. Join Supreet Oberoi from Concurrent, the people behind Cascading, as he explains how Cascading enables efficient and robust development of data-applications for Hadoop. In addition, he will talk about the challenges in operationalizing large-scale log processing applications on which businesses can depend.
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