Why Spring Belongs In Your Data Stream (From Edge to Multi-Cloud)

Fabrizio Marini - Cloudera

Let’s build data streaming apps anywhere with Spring at any scale.

With modern applications spanning from edge to any and all clouds to support data collection, real-time streaming, sensor ingest, edge computing, IoT use cases, and edge AI, we need to be able to run our Spring microservices anywhere. Apache Kafka allows us to build computing at the edge and produce and consume messages at scale in any IoT, hybrid, or cloud environment. We will also send messages via MQTT protocol to be used for high-speed messaging. We will have a demo that shows coding, running, and deploying Spring-based Edge applications to Raspberry Pis and NVIDIA Jetson devices.

Spring is often forgotten in real-time data processing and replaced with Python or Scala. Java and Spring are perfect for real-time data processing.

Spring belongs in your real-time data pipeline, and I’ll show you how to incorporate it into streaming applications as part of a FLaNK-Spring application. Kafka, Flink, Spark, NiFi, and Spring work together to build fast, safe streaming applications to deploy in bare metal, VMs, containers, pods, VMware Tanzu, or any cloud.