Join us for our upcoming meetup at WeWork Nomad –- thank you to Intersys for providing the space.
The agenda for the evening is:
6:00 pm - doors open. Food & beverages will be provided
6:30 pm - talks start
8:30 pm - we'll start to wrap things up
6.0 is coming
To help our awesome community prepare we will be doing a run through of the major changes that will land with the Elastic Stack in 6.0.
We have things like rolling-major version upgrades, even more Lucene data structure optimisations, sequence IDs, saying farewell to _types, dashboard modes, automated cluster alerts, Logstash pipelines and a pipeline viewer, Beats integration with kubernetes and a whole raft of new Beats modules.
Our Pioneer Program also makes a return, so if you are already using the beta releases of the stack and are submitting issues, you're a winner!
Chad Tindel is a Principal Solution Architect for Elastic based out of NYC. His main area of focus is helping Media, Telecom, and Financial Services customers understand and use the Elastic stack in their environment. Chad has also worked as a Solution Architect at Prevoty, MongoDB, Cloudera and Red Hat, and was a Software Architect at Hewlett Packard before that focusing on Linux kernel development and High Availability solutions. He holds a B.S. in Computer Science from California Polytechnic State University, San Luis Obispo and an M.S. in Finance from the University of Denver.
Elastic Machine Learning Module
A quick overview of the new machine learning module that comes with Elasticsearch. X-Pack machine learning will be a valuable tool for data analytics. It uses unsupervised machine learning for anomaly detection and to help discover their causes. We will provide a 10000 feet view of the process and one or two use cases.
John Murphy was born in Pittsburgh and graduated Summa Cum Laude from Point Park University with a degree in information technology. After college, he went to work in the newly burgeoning field of e-discovery working with companies such as Bayer, Walmart, Enron, and Merck. E-discovery was one of the first use cases of big data. During this time, John worked as the head of technology and later moved into R&D. It was in that role that John began working on computer assisted review with a group that included four Ph.D. linguists as well as several professors from the University of Toronto. During that time John began working with up and coming technologies such as Lucene (the base of ElasticSearch), distributed processing, machine learning and natural language processing. For fun, John enjoys chess, cooking, and playing Dota.