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Elastic Seattle User Group

4.7•92 ratings

Seattle, WA, US

1,602 members · Public group

What we’re about

We’re delighted to have you join the Elastic global community! This group is for anyone interested in making data usable in real-time and at scale for use cases like security, observability, enterprise search, and many more, using our Elasticsearch, Kibana, Logstash, and Beats products (https://www.elastic.co/products/).

Speak at a meetup: The Community wants to hear from you! Present about your Elastic Stack stories, be it a 5-15 minute lightning talk or a detailed 25-45 minute technical presentation with Q&A. Our Speaker Guide is full of tips on giving a stellar presentation. If you’re interested, visit the elastic/call-for-meetups repo or send us an email at meetups@elastic.co.

Elastic Community Youtube Channel: All meetups are recorded and uploaded to YouTube within a few days of the event. Subscribe here to stay up to date!

Local community organizers wanted!

We’re always on the lookout for committed local organizers who will help the group thrive. If this sounds interesting to you, the Community Team at Elastic is here to support you! Email us at meetups@elastic.co.

We know that people enjoy giving back to the communities they care about, so we’ve created an Organizer guide to help you get started on your path to leading an Elastic user group.

Learn more about Elastic:

Elastic Contributor Program: https://www.elastic.co/community/contributor

Elastic Community: https://www.elastic.co/community

Community Newsletter: https://www.elastic.co/community/newsletter

Discussion Forums: https://discuss.elastic.co/

Elastic Cloud Free Trial: https://www.elastic.co/cloud/elasticsearch-service/signup

Code of Conduct: This Meetup community adheres to the Elastic Community Code of Conduct. Attendance to events run as part of this Meetup group means you agree to be an awesome human and engage by these rules.

Upcoming events

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Thu, Oct 23 · 5:30 PM PDT
Tracking Longterm Health with Elasticsearch x AWS User Group Seattle
AWS Skills Center, 1007 Stewart St, Seattle, WA, US
The Elastic Seattle User Group & AWS User Group Seattle (AWSUGSEA) are partnering for a joint meetup on Thursday, October 23rd. We'll have presentations from Justin Castilla (Sr. Developer Advocate at Elastic) Natalie Serebryakova (Staff Cloud Engineer at IN-N-OUT.CLOUD), followed by food, refreshments, and networking.

📅 Date & Time:
Thursday, October 23rd, from 5:30-7:30 pm PDT

📍Location:
AWS Skills Center (across the street from its former location at the Amazon Kiro building)

Amazon Oscar building
1007 Stewart St
2nd floor
Seattle, WA 98101

🚗 Parking:
- SpotHero - Book a parking spot in advance
🪧 Arrival Instructions:
- Guests will go upstairs to the AWS Skills Center on 2nd floor. It’s directly up the stairs or elevator or they can use escalator and just follow floor signage to navigate to the entrance.
- Check-in with our guest reception team and then be directed to the rooms. Even though the Skills Center closes at 5pm, they will be open for the user group.
💭Talk Abstracts:
Tracking Longterm Health with a Sympathetic Voice - Justin Castilla - Sr. Developer Advocate at Elastic

This talk will introduce developers to the Model Context Protocol (MCP) through a practical example that demonstrates how to build AI-powered applications that integrate Claude Desktop with external data sources like Elasticsearch. Attendees will learn core MCP concepts while exploring real-world implementation patterns like structured data validation, multi-step workflows, LLM-as-a-jury evaluation, and semantic search capabilities. Developers with basic Python and API experience will leave understanding how to create MCP servers that transform static data into interactive, AI-accessible resources, enabling new paradigms for user interaction in their own applications.

AWS EKS GPU Spot Recovery Operator for ML Workloads - Natalie Serebryakova - Staff Cloud Engineer at IN-N-OUT.CLOUD

In this session Natalie will be speaking about Kubernetes operator for AWS EKS that detects Spot interruptions on GPU nodes, triggers ML job checkpointing, and recovers training by rescheduling on available nodes. This I prepared with an idea to provide an interesting example of a repeatable workflow for maximizing GPU cost savings without losing progress on ML training jobs. The setup covered in this talk will include services AWS EventBridge, S3/EFS , IAM, and CloudWatch. Natalie will be presenting a live example to show node interruption handling, and seamless ML job recovery using my developed solution.
7 attendees