Elastic Chicago User Group

Thank you to Improving for hosting our meetup. Improving is a modern digital services consulting firm focused on solving business problems with innovative technical solutions.

RSVP Instructions:
Please provide your email when you register for this event. Please bring an ID to the event for check-in.

📅 Date and Time:
Wednesday, May 13th from 5:30-8:00 pm

📍Location:
Improving - 222 S Riverside Plaza 15th Floor, Chicago, IL 60606

🔑 Arrival Instructions:

• Please bring an ID for check-in
• Upon arrival at 222 Riverside, check in at the Improving table
• Take the elevator to the 15th floor - the meetup will be in the common area through the doors.

🚗 Parking:

• SpotHero is a great option to resvere parking in advance
• Improving recommends the following parking garages: 229 S. Desplaines St (which is also the 625 W. Adams building), 500 West Monroe, and the outdoor lot at 718 W Monroe.

📝Agenda:

• 5:30 PM – Doors open, grab a seat, and enjoy some pizza!
• 6:00 PM – Welcome & Introduction by Improving
• 6:05 pm – One Does Not Simply Query a Stream - Viktor Gamov, Principal Developer Advocate, Confluent
• 6:30 – Building Autonomous AI Agents with Elasticsearch & LLMs (Lightning talk) - Deepesh Kumar (MS in AI @Illinois Tech)
• 6:45 pm – A Practical Approach to Real‑Time SQL Data Indexing in Elasticsearch - Mangesh Walimbe (Application Architect)
• 7:00 pm: Networking and refreshments
• 8:00 pm: Event ends

💭 Talk Abstracts:
One Does Not Simply Query a Stream - Viktor Gamov, Principal Developer Advocate, Confluent
Streaming 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.

A Practical Approach to Real‑Time SQL Data Indexing in Elasticsearch - Mangesh Walimbe (Application Architect)
SQL databases are designed to store and manage large volumes of structured data, but they are not optimized for high‑speed search and analytics. Elasticsearch, by contrast, provides powerful indexing and near real‑time search capabilities, making it a strong complement to traditional relational systems. Ensuring that SQL data is continuously available in Elasticsearch, however, can be a complex and time‑consuming process. This presentation outlines a streamlined approach for processing, filtering, and ingesting SQL database records into Elasticsearch using Logstash pipelines, based on practical implementation experience.

Join the Elastic Chicago User Group and AWS Chicago User Group on Wednesday, June 3rd for a meetup. We'll have presentations from followed by food, refreshments, and networking.

📅 Date and Time:
Wednesday, June 3rd from 5:00-7:00 pm

📍Location:
Associated Forum - 10 S Riverside Plaza #800, Chicago, IL 60606
The main entrance to the building is on the corner of Monroe and Canal.

🔑 RSVP & Arrival Instructions:
Please include your email address when registering for this event and bring a valid ID for check-in at the venue. Attendees will need to show ID to lobby security for access to Suite 800

🚗 Parking:
500 W. Monroe and 10 S. Wacker are both within ½ a block radius. ParkChirp or Spothero typically have discounted rates. Metra and CTA are within a ½ block radius.

📝Agenda:

• 5:00 PM – Doors open, grab a seat, and enjoy some pizza!
• 5:30 PM – Welcome & Introductions
• 6:00 pm – From Abandoned Carts to Recovered Revenue: Building an AI Agent with AWS & Elasticsearch - Aashana Shanu (Sr. Software Engineer)
• 6:30 – Talk # 2 - More details to come

💭 Talk Abstracts:
From Abandoned Carts to Recovered Revenue: Building an AI Agent with AWS & Elasticsearch - Aashana Shanu (Sr. Software Engineer)
This talk explores how Amazon Web Services and Elasticsearch can be combined to build real-time, intelligent systems.
Using Elastic Agent for continuous data ingestion and AWS Lambda as an MCP (Model Context Protocol) tool, the architecture enables AI agents to interact directly with live data and decision logic. Paired with AWS’s event-driven stack, this creates a system where actions are triggered, evaluated, and executed in near real time.
The innovation is in turning search into a decision engine and serverless functions into AI-integrated tools, enabling adaptive, context-aware workflows instead of static automation.