Scaling Logstash with BGP + Elasticsearch Query Language ES|QL

This event has been rescheduled to Wednesday, May 1st!

Join us on Wednesday, May 1st, at the ElastiFlow office for a Boston Elastic User Group meetup. Leo Chan (Senior Systems Engineer at Breckinridge Capital Advisors) and Jessica Garson (Sr. Developer Advocate at Elastic) will present, followed by networking, pizza, and refreshments.

Please RSVP if you plan on attending so we can provide the venue with an accurate headcount and add your name to the guest list for building security.

Thank you to ElastiFlow for providing space at their office for this meetup!

Date & Time:
Wednesday, May 1st, from 5:30-7:30 pm EDT

Location:
ElastiFlow Office - 9th Floor: 120 Causeway St., Boston, MA 02114

Arrival Instructions:
From the street, look for the Rapid 7 entrance. Check in at the front desk and then take the elevator to the 8th Floor. There will be an ElastiFlow team member working the elevator up to their space on the 9th floor.

Agenda:

• 5:30 pm: Doors open; say hi, grab a seat, and eat some food.
• 5:45 pm: Scaling Logstash with BGP - Leo Chan (Senior Systems Engineer at Breckinridge Capital Advisors)
• 6:30 pm: Elasticsearch Query Language — ES|QL - Jessica Garson (Sr. Developer Advocate at Elastic)
• 7:00 - 7:30 pm: Networking & refreshments

Talk Abstracts:

Scaling Logstash with BGP - Leo Chan (Cloud & Networking Engineering at Rakuten)

Logstash continues to be a cornerstone of the Elasticsearch ecosystem. This presentation explores traditional methods for achieving high redundancy in Logstash, such as Pacemaker and HAProxy. Additionally, it delves into a lesser-known but commonly used approach for scaling Logstash.

In this talk, we'll cover:
- Ways to scale Logstash
- Options and drawbacks to make Logstash highly available
1. HAProxy
2. Pacemaker
3. BGP

Elasticsearch Query Language — ES|QL - Jessica Garson (Sr. Developer Advocate at Elastic)

Elasticsearch and Kibana added a brand new query language: ES|QL — coming with a new endpoint (_query) and a simpler syntax. It lets you refine your results one step at a time and adds new features like data enrichment and processing right in your query. And you can use it across the Elastic Stack — from the Elasticsearch API to Discover and Alerting in Kibana. But the biggest change is behind the scenes: Using a new compute engine that was built with performance in mind.
Join us for a quick overview and a look at syntax and internals.