About us
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
1
From Streams to Search: Real-Time Data with Kafka + Elasticsearch
Plug and Play Tech Center, 440 N Wolfe Rd, Sunnyvale, CA, USThe Elastic Silicon Valley User Group & Bay Area Apache Kafka Meetup are partnering for a joint meetup on Tuesday, April 7th. We'll have presentations from followed by food, refreshments, and networking.
⚡️ Interested in presenting a lightning talk?⚡️ If you have you ever considered presenting, but think 30 or 45 minutes is too long to start with, this is a great opportunity to try it out. Interested? Please email us at meetups@elastic.co.
📅 Date and time:
Tuesday, April 7th from 5:30 - 7:30 pm PDT📍Location:
Plug and Play Tech Center - Silicon Valley Room
440 N Wolfe Rd, Sunnyvale, CA 94085🪧 Arrival Instructions:
Attendees will need to check in at the Plug and Play lobby upon arrival. We'll provide the guest list to the venue 24 hours in advance for badge creation.📝 Agenda:
- 5:30 pm Doors open
- 5:45 pm: One Does Not Simply Query a Stream - Viktor Gamov, Principal Developer Advocate, Confluent
- 6:15: Building a Meltano Target for Elasticsearch: Automating SPACE Metrics Dashboard - DT Mirizzi, Principal Software Engineer at Palo Alto Networks
- 6:45 pm: With Elastic, Search finds the insight, Workflows acts on it & Agent Builder Explains it - Steve Leung - Sr. Solutions Architect @ Elastic
- 7:30 pm: Event ends
💭Talk Abstracts:
One Does Not Simply Query a Stream - Viktor Gamov, Principal Developer Advocate, ConfluentStreaming data with Apache Kafka® has become the backbone of modern applications. While streams are ideal for continuous data flow, they lack built-in querying capabilities. Unlike databases with indexed lookups, Kafka’s append-only logs are designed for high-throughput processing—not for on-demand queries. This necessitates additional infrastructure to query streaming data effectively.Traditional approaches replicate stream data into external stores: relational databases like PostgreSQL for operational queries, object storage like S3 accessed via Flink, Spark, or Trino for analytics, and Elasticsearch for full-text search and log analytics. Each serves a purpose—but they also introduce silos, schema mismatches, freshness issues, and complex ETL pipelines that increase system fragility.In this session, we’ll explore solutions that aim to unify operational, analytical, and search workloads across real-time data.
We'll demonstrate stream processing with Kafka Streams, Apache Flink®, and SQL engines; real-time analytics with Apache Pinot® ; search capabilities with Elasticsearch; and modern lakehouse approaches using Apache Iceberg® with Tableflow to represent Kafka topics as queryable tables. While there's no one-size-fits-all solution, understanding the tools and trade-offs will help you design more robust and flexible architectures.With Elastic, Search finds the insight, Workflows acts on it & Agent Builder Explains it - Steve Leung - Sr. Solutions Architect @ Elastic
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