Stream Processing on the IBM Mainframe with Apache Flink - Genius or a Glitch in the Matrix
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Stream Processing on the Mainframe with Apache Flink: Genius or a Glitch in the Matrix?

Running Apache Flink on a mainframe may sound surprising, but it is already happening and for good reason. As modern mainframes like IBM z17 evolve to support Linux, Kubernetes, and AI workloads, they are becoming a powerful platform for real-time stream processing. This blog explores why enterprises are deploying Apache Flink on IBM LinuxONE, how it works in practice, and what business value it brings. With Kafka providing the data backbone, Flink enables intelligent processing close to where business-critical data lives. The result is a modern hybrid architecture that connects core systems with cloud-based innovation without needing to fully migrate off the mainframe.
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Replacing OT Middleware with Data Streaming using Kafka and Flink for Cloud-Native Industrial IoT with MQTT and OPC-UA
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Modernizing OT Middleware: The Shift to Open Industrial IoT Architectures with Data Streaming

Legacy OT middleware is struggling to keep up with real-time, scalable, and cloud-native demands. As industries shift toward event-driven architectures, companies are replacing vendor-locked, polling-based systems with Apache Kafka, MQTT, and OPC-UA for seamless OT-IT integration. Kafka serves as the central event backbone, MQTT enables lightweight device communication, and OPC-UA ensures secure industrial data exchange. This approach enhances real-time processing, predictive analytics, and AI-driven automation, reducing costs and unlocking scalable, future-proof architectures.
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