Join us at our office on Wednesday, May 1st, for a San Francisco Elastic User Group meetup. We'll have presentations from Ari Hershowitz and Bahubali Shetti (Senior Director, Product Marketing at Elastic), followed by networking, light bites, and refreshments.

Date and time:

Wednesday, May 1st, from 5:00 - 7:00 pm PDT

Location:

Elastic Office - 19th Floor

88 Kearny Street, San Francisco, CA

RSVP Instructions:

Please register no later than Monday, April 29th, 2024. We need to provide a list of the attendees' names to building security 48 hours before the event. Visitors will need to check in at the lobby with an ID for access to the 19th floor.

Directions & Parking:

This Elastic office does not offer parking. Below are a few recommendations for nearby public parking garages. Please keep in mind that parking is not allowed to be expensed and must be paid for on your own.

• The White House Garage: 223 Sutter St, San Francisco, CA 94108
• Post Montgomery Center Garage: 173 Sutter St, San Francisco, CA 94101
• Paramount Garage: 177 Jessie St, San Francisco, CA 94105

Bart & Muni Information:

• The nearest BART station is Montgomery St. Station
• The nearest Muni Station is Market & New Montgomery

Agenda:

• 5:00 pm: Doors open; say hi, grab a seat, and eat some food.
• 5:15 pm: Elasticsearch in the United States House - Ari Hershowitz
• 6:00 pm: Learn how Elastic uses RAG in providing better Observability Analysis For All Signals - Bahubali Shetti (Senior Director, Product Marketing at Elastic)
• 6:30-7:00 pm: Networking & refreshments
• 7:00 pm: Event ends

Talk Abstracts:

Elasticsearch in the United States House - Ari Hershowitz

The Parliamentarian of the United States House stores more than two hundred years of precedents. These were written down on index cards and eventually transferred to SQL Server. The search was done with a SQL query, and -- even though there are only a few thousand records -- it could take up to a minute to retrieve a result. We built a customized user interface and index using Elasticsearch, that brought down search latency to milliseconds. As an application, it is pretty run-of-the-mill. But it wholly transformed the workflow in the office and allowed the Parliamentarian to do much more extensive research than before on their records. There are small applications like this throughout government, where indexing alone can make a big difference. I'll discuss this opportunity, and the challenges of building a custom UI and facets for the Parliamentarian and similar use cases.

Learn how Elastic uses RAG in providing better Observability Analysis For All Signals - Bahubali Shetti (Senior Director, Product Marketing at Elastic)

Elastic's platform has the Elastic Learned Sparse Encoder Representations (ELSER) (an advanced NLP model) built in aid in handling various NLP tasks like search, text classifications, entity extraction. Elastic Observability uses ELSER to help find the proper contextual information when analyzing issues as an SRE. Github issues, runbooks from wikipedia or other places, customer tickets, and more can be ingested, indexed, and run through ELSER to help aid in adding contextual internal information when an SRE is analyzing issues with Elastic Observability's AI Assistant. We will show you how this works in various features such as APM & Universal Profiling.