Wrangling Logs with Logstash and ElasticSearch

Sponsored Sessions
Location: E143
Average rating: ****.
(4.00, 5 ratings)

Browsing through large amounts of data can be cumbersome and impractical. Searching through that raw data can still be very time consuming. These problems are only compounded when the data is unstructured and you still have the issues of access and usability to contend with.

Learn how to use open source to build an enterprise grade log processing and searching solution that scales. We’ll cover the challenges and all the software that makes a diy solution possible: logstash, elasticsearch, rabbitmq and Kibana. We’ll cover a practical use case with examples and provide you with everything you need to get up and running.

This session is sponsored by Media Temple

Photo of Nate Jones

Nate Jones

Media Temple

Nate Jones has been building software for over a decade and currently leads the team responsible for improving the tools and processes we use to develop and release software at Media Temple. When he’s not building or improving systems and tools, he can usually be found dissecting new technologies or sharpening his code-fu.

Photo of David Castro

David Castro

Media Temple

David Castro leads the team responsible for guarding the ever growing set of customer email. Over the past year, the team reengineered the backend to be more tailored to email’s unique storage and backup requirements and replaced the aging webmail interface with an updated offering. Before this role, he spearheaded the architecture and development of Media Temple’s public facing API. In his spare time he enjoys refactoring his backyard.


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