Cybersecurity with a Real-Time Digital Twin using Data Streaming with Apache Kafka Flink and Sigma
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Cybersecurity with a Digital Twin: Why Real-Time Data Streaming Matters

Cyberattacks on critical infrastructure and manufacturing are growing, with ransomware and manipulated sensor data creating severe risks. Digital twins combined with data streaming provide real-time visibility, continuous monitoring, and proactive defense across both IT and OT environments. Using technologies like Kafka, Flink and Sigma, organizations can detect anomalies instantly, strengthen resilience, and secure digital transformation.
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How Data Streaming with Apache Kafka and Flink Powers AI and Autonomous Networks in the Telecom Industry
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How Data Streaming Powers AI and Autonomous Networks in Telecom – Insights from TM Forum Innovate Americas

AI and autonomous networks took center stage at TM Forum Innovate Americas 2025 in Dallas. Leaders from AT&T, Verizon, and other telcos showed how large-scale AI is transforming customer experience, security, and network operations, while the vision of self-optimizing networks moves closer to reality. At the heart of these advances lies data streaming: real-time, governed data flows that connect OSS/BSS, feed AI with fresh context, and enable automation at scale. This article captures the key insights from the event and explains why data streaming is becoming the central nervous system of modern telecoms.
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IT OT Convergence with Unified Namespace UNS and Data Product in Industrial IoT using Data Streaming Apache Kafka MQTT OPC UA
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Unified Namespace vs. Data Product in IT/OT for Industrial IoT

Industrial companies are connecting machines, sensors, and enterprise systems like never before. Real-time data, cloud-native platforms, and AI are driving this transformation—but only if silos between OT and IT can be broken down. This blog introduces two key architecture patterns that support IT/OT convergence. The Unified Namespace structures live OT data, while Data Products govern and deliver that data across IT systems. Technologies like MQTT, OPC UA and Apache Kafka play a central role in building scalable, secure, and real-time data pipelines. Combined, these patterns enable clean integration, better data quality, and faster time to value—laying the foundation for success in manufacturing, energy, logistics, and beyond.
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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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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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Energy Trading with Apache Kafka and Flink at Uniper ReAlto Powerledger
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Energy Trading with Apache Kafka and Flink

Energy trading and data streaming are connected because real-time data helps traders make better decisions in the fast-moving energy markets. This data includes things like price changes, supply and demand, smart IoT meters and sensors, and weather, which help traders react quickly and plan effectively. As a result, data streaming with Apache Kafka and Apache Flink makes the market clearer, speeds up information sharing, and improves forecasting and risk management. This blog post explores the use cases and architectures for scalable and reliable real-time energy trading, including real-world deployments from Uniper, re.alto and Powerledger.
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Data Streaming with Apache Kafka for Industrial IoT in the Automotive Industry at Brose
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Apache Kafka in Manufacturing at Automotive Supplier Brose for Industrial IoT Use Cases

Data streaming unifies OT/IT workloads by connecting information from sensors, PLCs, robotics and other manufacturing systems at the edge with business applications and the big data analytics world in the cloud. This blog post explores how the global automotive supplier Brose deploys a hybrid industrial IoT architecture using Apache Kafka in combination with Eclipse Kura, OPC-UA, MuleSoft and SAP.
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Data Streaming with Apache Kafka and ARM CPU at the Edge and in the Cloud
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ARM CPU for Cost-Effective Apache Kafka at the Edge and Cloud

ARM CPUs often outperform x86 CPUs in scenarios requiring high energy efficiency and lower power consumption. These characteristics make ARM preferred for edge and cloud environments. This blog post discusses the benefits of using Apache Kafka alongside ARM CPUs for real-time data processing in edge and hybrid cloud setups, highlighting energy-efficiency, cost-effectiveness, and versatility. A wide range of use cases are explored across industries, including manufacturing, retail, smart cities and telco.
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MQTT Market Trends for 2024 including Sparkplug Data Governance Kafka Cloud
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MQTT Market Trends: Cloud, Unified Namespace, Sparkplug, Kafka Integration

The lightweight and open IoT messaging protocol MQTT gets adopted more widely across industries. This blog post explores relevant market trends for MQTT: cloud deployments and fully managed services, data governance with unified namespace and Sparkplug B, MQTT vs. OPC-UA debates, and the integration with Apache Kafka for OT/IT data processing in real-time.
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