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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Industrial IoT Middleware OT IT Bridge between Edge and Cloud with Apache Kafka and Flink
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Industrial IoT Middleware for Edge and Cloud OT/IT Bridge powered by Apache Kafka and Flink

As industries continue to adopt digital transformation, the convergence of Operational Technology (OT) and Information Technology (IT) has become essential. The OT/IT Bridge is a key concept in industrial automation to connect real-time operational processes with business-oriented IT systems ensuring seamless data flow and coordination. By leveraging Industrial IoT middleware and data streaming technologies like Apache Kafka and Flink, businesses can achieve a unified approach to managing both production processes and higher-level business operations to drive greater efficiency, predictive maintenance, and streamlined decision-making.
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One Apache Kafka Cluster Type Does NOT Fit All Use Cases
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Apache Kafka Cluster Type Deployment Strategies

Organizations start their data streaming adoption with a single Apache Kafka cluster to deploy the first use cases. The need for group-wide data governance and security but different SLAs, latency, and infrastructure requirements introduce new Kafka clusters. Multiple Kafka clusters are the norm, not an exception. Use cases include hybrid integration, aggregation, migration, and disaster recovery. This blog post explores real-world success stories and cluster strategies for different Kafka deployments across industries.
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Hybrid Cloud Architecture with Apache Kafka Mainframe Oracle IBM AWS Azure GCP
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App Modernization and Hybrid Cloud Architectures with Apache Kafka

Hybrid cloud architectures are the new black for most companies. A cloud-first is obvious for many, but legacy infrastructure has to be maintained, integrated, and (maybe) replaced over time. Event Streaming with the Apache Kafka ecosystem is a perfect technology for building hybrid replication in real-time at scale.
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