Vergangene Events

Zeebe meets Confluent - Taming event-driven architectures

Dieses Meetup liegt in der Vergangenheit

44 Personen haben teilgenommen

camunda services GmbH

Zossener Strasse 55-58 · Berlin

Wie du uns findest

The event takes places at "the Pool" on the 4th floor.

Bild des Veranstaltungsortes


6:00pm: Doors open
6:00pm - 6:30pm: Catering/Snacks, Drinks and Networking
6:30pm - 7:15pm: Bernd Rücker, Camunda
7:15pm – 8:00pm: Pere Urbon Bayes, Confluent
8:00pm - 8:15pm - Additional Q&A & Networking
9:00pm: end


Bernd Rücker, Co-Founder Camunda

Bernd is a co-founder of Camunda. But foremost he is a software developer and consultant. He is doing BPM for more than 10 years now and committed in various Open Source Workflow Engines over time. By coaching countless projects he got totally passionate about the whole 'developer friendly BPM' story. When has some spare time he gives talks at conferences or write articles and books (e.g. Real-Life BPMN book).

The Big Picture: Monitoring and Orchestration of Your Microservices Landscape with Kafka and Zeebe

A company’s business processes typically span more than one microservice. In an e-commerce company, for example, a customer order might involve microservices for payments, inventory, shipping and more. Implementing long-running, asynchronous and complex collaboration of distributed microservices is challenging. How can we ensure visibility of cross-microservice flows and provide status and error monitoring? How do we guarantee that overall flows always complete, even if single services fail? Or, how do we at least recognize stuck flows so that we can fix them?
In this talk, I’ll demonstrate an approach based on real-life projects using the open source workflow engine to orchestrate microservices. Zeebe can connect to Kafka to coordinate workflows that span many microservices, providing end-to-end process visibility without violating the principles of loose coupling and service independence. Once an orchestration flow starts, Zeebe ensures that it is eventually carried out, retrying steps upon failure. In a Kafka architecture, Zeebe can easily produce events (or commands) and subscribe to events that will be correlated to workflows. Along the way, Zeebe facilitates monitoring and visibility into the progress and status of orchestration flows. Internally, Zeebe works as a distributed, event-driven and event-sourced system, making it not only very fast but horizontally scalable and fault tolerant—and able to handle the throughput required to operate alongside Kafka in a microservices architecture. Expect not only slides but also fun little live-hacking sessions and real-life stories.


Pere Urbon Bayes

Pere is a Technical Architect and Account Manager for Confluent out of Berlin, Germany. He has been working with data and architecting systems for more than 15 years as a freelance engineer and consultant. In that role he was focused on data processing and search, helping companies build reliable and scalable data architectures. His work sits usually at the crossroad of infrastructure, data engineers and scientists, ontologist and product. Prior to that he was part of Elastic, the company behind Elasticsearch, where he was part of the Logstash team, helping companies build reliable ingestion pipelines into Elasticsearch. When not working, Pere loves to spend time with his lovely wife and kids and to train for a good long distance race or duathlon.

Building the next generation streaming platform with Kafka

The need to integrate a swarm of systems has always been present in the history of IT, however with the advent of microservices, big data and IoT this has simply exploded. Through the exploration of a few use cases, this presentation will introduce stream processing, a powerful and scalable way to transform and connect applications around your business.

We will explain in this talk how Apache Kafka and the Confluent Platform can be used to connect the diverse collection of applications the actual business face. Components such as KSQL where non developers can process stream events at scale or Kafka Stream oriented to build scalable applications to process event data.