talk-data.com talk-data.com

Event

Data pipeline troubleshooting: Root cause analysis with lineage metadata

2025-11-27 – 2025-11-27 Meetup Visit website ↗

Activities tracked

1

Join us for a VIRTUAL meetup on Thursday, November 27th from 6:00 pm CEST.

📍 Zoom [Online]

🗓 Agenda:

  • 6:00pm: Welcome & Intro
  • 6:05pm: Mario Fiore Vitale (a maintainer of Debezium)

Have follow-up questions afterward? Log in to Slack or Join our Forum (https://www.confluent.io/community/ask-the-community) to ask any follow-up questions!

💡 Speaker: Mario Fiore Vitale (a maintainer of Debezium)

Title: Data pipeline troubleshooting: Root cause analysis with lineage metadata

Abstract: Remember when debugging streaming data pipelines felt like playing detective at a crime scene, where the evidence kept shifting? Well, grab your magnifying glass because we’re about to turn you into Sherlock Holmes of the streaming world. We’ll simulate a disruptive change in an order processing pipeline that captures database changes with Debezium, processes them through Apache Flink, and tracks lineage metadata with OpenLineage and Marquez.

Online Meetup Etiquette

  • Please hold your questions until the end of the presentation or use the zoom chat during!
  • Please arrive on time as zoom meetings can become locked for many reasons (though if you get locked out a recording will be available, but you may have to wait a little while for it!)
  • Important note: If Zoom asks for a password to join please use 'kafka'

If you would like to speak or host our next event please let us know! Email: [email protected] Slack community: Confluent slack

Sessions & talks

Showing 1–1 of 1 · Newest first

Search within this event →

Data pipeline troubleshooting: Root cause analysis with lineage metadata

2025-11-27
talk
Mario Fiore Vitale (Debezium)

Remember when debugging streaming data pipelines felt like playing detective at a crime scene, where the evidence kept shifting? Well, grab your magnifying glass because we’re about to turn you into Sherlock Holmes of the streaming world. We’ll simulate a disruptive change in an order processing pipeline that captures database changes with Debezium, processes them through Apache Flink, and tracks lineage metadata with OpenLineage and Marquez.