Stream All Things - Patterns of Modern Data Integration
|Architecture, Performance et Securité||Intermédiaire|
|Friday 11:15 - 12:00|
80% of the time in every project is spent on data integration: Getting the data you want the way you want it. This problem remains challenging despite 40 years of attempts to solve it. We want a reliable, low latency system that can handle varied data from wide range of data management systems. We want a solution that is easy to manage and easy to scale. Is it too much to ask?
In this presentation, we’ll discuss the basic challenges of data integration and introduce design and architecture patterns that are used to tackle these challenges. We will explore how these patterns can be implemented using Apache Kafka and share pragmatic solutions that many engineering organizations used to build fast, scalable and manageable data pipelines.Kafka Stream Processing Event-Driven Microservices
|La salle sera affectée entre 24 et 72h avant la conférence|
Gwen is a product manager at Confluent. She has 15 years of experience working with code and customers to build scalable data architectures, integrating relational and big data technologies. Gwen is the author of “Kafka - The Definitive Guide” and "Hadoop Application Architectures", and a frequent presenter at industry conferences. Gwen is a PMC member on the Apache Kafka project and committer on Apache Sqoop. When Gwen isn't building data pipelines or thinking up new features, you can find her pedaling on her bike exploring the roads and trails of California, and beyond.