Скачать с ютуб Change Data Streaming Patterns With Debezium & Apache Flink | Decodable в хорошем качестве

Change Data Streaming Patterns With Debezium & Apache Flink | Decodable

ABOUT THE TALK: Microservices are one of the big trends in software engineering of the last few years. In this session we'll discuss and showcase how open-source change data capture (CDC) with Debezium can help developers with typical challenges they often face when working on microservices. Learn how to: - Employ the outbox pattern for reliable, eventually consistent data exchange between microservices, without incurring unsafe dual writes or tight coupling - Gradually extract microservices from existing monolithic applications, using CDC, the strangler fig pattern and Apache Flink - Coordinate long-running business transactions across multiple services using CDC-based saga orchestration, ensuring such activity gets consistently applied or aborted by all participating services. ABOUT THE SPEAKER: Gunnar Morling is a software engineer and open-source enthusiast by heart, currently working at Decodable on stream processing based on Apache Flink. In his prior role as a software engineer at Red Hat, he led the Debezium project, a distributed platform for change data capture. He is a Java Champion and has founded multiple open source projects such as JfrUnit, kcctl, and MapStruct. Gunnar is an avid blogger (morling.dev) and has spoken at a wide range of conferences like QCon, Java One, and Devoxx. He lives in Hamburg, Germany. ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers. Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies. FOLLOW DATA COUNCIL: Twitter:   / datacouncilai   LinkedIn:   / datacouncil-ai