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

on YouTube ↗45m

" summary

Live demo builds an end-to-end pipeline: MQTT sensors -> MiNiFi edge agent -> NiFi -> Kafka -> Flink SQL -> alert topic -> MQTT actuator, all wired with the Spring dashboard showing real-time values. No custom code required to reshape JSON, register schemas, or run windowed averages; Flink runs sliding 15s windows every 5s and triggers alerts when average temperature >30°C. Community Docker compose boots Kafka, Flink, NiFi; Flink sustains thousands/sec, NiFi persists to disk for at-least-once safety and HA via three nodes.

AI-written summary · about

" chapters (5)

1. 0:00Start
2. 4:26FLINK IS A DISTRIBUTED DATA PROCESSING SYSTEM
3. 9:08CSP Community Edition
4. 10:00Greenhouse demo architecture - Today Demo
5. 14:19Greenhouse demo architecture - Original Version

" related talks

• 50mWalking Through Spring Cloud Data FlowGlenn Renfro, Ilayaperumal Gopinathan · SpringOne 2020
• 52mCloud-native streaming and event-driven microservicesMarius Bogoevici · Spring I/O 2016
• 47mStream All the Things!Dean Wampler · Scala.IO 2017
• 01h 06mOrchestrating Data Microservices with Spring Cloud Data Flow - Mark PollackMark Pollack · SpringOne Platform 2017
• 40mFlink in Zalando's World of MicroservicesJavier Lopez, Mihail Vieru · Flink Forward Berlin 2016
• 44mData Processing With MicroservicesMichael Minella · Spring I/O 2017
• 26mHow Streaming Helps Your Staging Environment and Sandboxes Stay Up To DateMike Solomon · Flink Forward Virtual 2020
• 43mEvent Streams & Data Rapids: Harnessing the Full Power of Messaging Platforms.Mark Heckler · Devoxx Ukraine 2022: Secure our Future