Hans-Peter Grahsl is a Staff Developer Advocate at Decodable. He is an open-source community enthusiast and in particular passionate about event-driven architectures, distributed stream processing systems and data engineering. For his code contributions, conference talks and blog post writing at the intersection of the Apache Kafka and MongoDB communities, Hans-Peter received multiple community awards. He likes to code and is a regular speaker at developer conferences around the world.
As the saying goes: nothing is older than yesterday’s news, uhm, data. Join us for an immersive hands-on lab to explore real-time ETL using the triumphant trio Apache Flink, Debezium, and LangChain4j.
Participants will gain practical experience in setting up different end-to-end real-time data pipelines, streaming data from an operational database to an analytics data store—continuously, efficiently, and with a very low latency—enabling use cases such as full-text search and live dashboarding, enriched with LLM-derived metadata.
In the lab, you will learn how to:
- Build a real-time data pipeline from Postgres to OpenSearch, based on Apache Flink and Debezium for change data capture (CDC)
- Use Flink's connector capabilities to set up seamless real-time ETL pipelines between various data sources and sinks
- Implement data transformations, filtering, and aggregations on top of CDC streams in real time with the help of streaming SQL
- Integrate a large language model (LLM) for sentiment analysis based on LangChain4j, enabling deeper insights into the processed data
Join this lab to advance your skills in working with real-time data and learn how robust and leading open-source technologies support your business-critical stream processing workloads.
As this is a practical hands-on-lab, please bring your laptop with the following things installed:
- Java 11
- Apache Maven
- Docker
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