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Join us to learn something new & meet others who are passionate about search, observability, & security.
Agenda:
5:30 pm: Doors open; say hi & eat some food
6:00 pm: 12 Levels of Search - Easy to Complex, by Jon Avezbaki, Developer Advocate at Elastic
6:30 pm: Q&A with Jon
6:40 pm: "One Does Not Simply Query a Stream", by Viktor Gamov, Principal Developer Advocate at Confluent
7:10 pm: Q&A with Viktor
7:20 - 7:30 pm: Networking & event wrap-up
Abstracts:
12 Levels of Search - Easy to Complex
You can't learn calculus without arithmetic. Search is no different. In this talk, we'll go over a full, high-level overview of search engineering. We'll start with the basics, & then make our way through more intermediate & advanced topics, like RAG & agentic memory. This is not a talk that will dive into any one area of search in great detail. Rather, it aims to provide a birds-eye prespective of the field so that we can begin to understand what topics & best practices we may be lacking in our understanding. These potentially unexplored avenues can significantly benefit our search & AI systems by expanding our technological toolkit.
Bio:
Jon worked for 8 years as a software engineer in the finance & traffic engineering industries before pivoting to developer advocacy at Elastic. He now empowers developers through education, outreach, & community engagement.
"One Does Not Simply Query a Stream"
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, & Elasticsearch for full-text search & log analytics. Each serves a purpose-but they also introduce silos, schema mismatches, freshness issues, & complex ETL pipelines that increase system fragility. In this session, we'll explore solutions that aim to unify operational, analytical, & search workloads across real-time data. We'll demonstrate stream processing with Kafka Streams, Apache Flink, & SQL engines; real-time analytics with Apache Pinot; search capabilities with Elasticsearch; & 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 & trade-offs will help you design more robust & flexible architectures.
Bio:
Viktor Gamov is a Principal Developer Advocate at Confluent, founded by the original creators of Apache Kafka. With a rich background in implementing & advocating for distributed systems & cloud-native architectures, Viktor excels in open-source technologies. He is passionate about assisting architects, developers, & operators in crafting systems that are not only low in latency & scalable but also highly available.
As a Java Champion & an esteemed speaker, Viktor is known for his insightful presentations at top industry events like JavaOne, Devoxx, Kafka Summit, & QCon. His expertise spans distributed systems, real-time data streaming, JVM, & DevOps.
Viktor has co-authored "Enterprise Web Development" from O'Reilly & "Apache Kafka in Action" from Manning.
Follow Viktor on X - @gamussa to stay updated with Viktor's latest thoughts on technology, his gym & food adventures, & insights into open-source & developer advocacy.
Where: Elastic NYC Office
1250 Broadway, Floor 16, Training Room
New York, NY 10001
When: June 2nd | Doors open at 5:30 PM
If you're a long-time Elastic user or just starting your journey, this is the perfect opportunity to share ideas, meet new people, & get inspired. See you there!
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