This is a past event

174 people went

Elastic Office

800 El Camino West Suite 170 · Mountain View, CA

How to find us

There may be some signs of construction outside of the space.

Location image of event venue

Details

Join us for a Logstash-focused meetup on August 31, featuring two members of the Elastic Logstash development team. Food and beverages will be provided.

• 6:30: Eat, drink, and meet folks

• 7:00: Using your relational database with the ELK stack

• 7:30: What's next in Logstash

• 8:00: General Q&A

Using your relational database with the ELK stack

Ever wanted to know all about using your relational database with the ELK stack? Tal Levy, developer on the Logstash team, is here to help! In this presentation, Tal will cover how to ingest data from your database using the new Logstash JDBC plugin. He will also explore how to transform your data for seamless visualization in Kibana, and share strategies on how to keep Elasticsearch indices up-to-date with your database. Tal will conclude with a demo bringing everything together to ingest, visualize, and learn from Musicbrainz music data.

Tal Levy is a software engineer working on the Logstash team building out new features and integrations. When he is not clickclacking on his keyboard, you can find him cycling and climbing.

What's next in Logstash

In this talk, we’ll give you an exciting preview into the world of Logstash 2.0, our next major release. We are focusing on three main themes for 2.x: resiliency, manageability, and performance improvements. We’ll take you through a tour of these themes and some use cases that we intend to address. We’ll talk about what a Logstash cluster will look like, plus APIs that will be used to interact with it. Under our resiliency project, we discuss persistence queues and how it will be used in Logstash.

Suyog Rao is team lead for the Logstash product at Elastic. He spends his time developing, supporting customers and training users on the ELK stack. Previously, he worked on a high-throughput, low-latency infrastructure for ingesting and analyzing terabytes of log data using Elasticsearch, Apache Kafka, and Storm.