Browsing Tag

kafka

195 posts
Fraud Prevention in Mobility Services with Data Streaming using Apache Kafka and Flink with AI Machine Learning
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  • 396 views
  • 7 minute read

Fraud Detection in Mobility Services (Ride-Hailing, Food Delivery) with Data Streaming using Apache Kafka and Flink

Mobility services like Uber, Grab, and FREE NOW (Lyft) rely on real-time data to power seamless trips, deliveries, and payments. But this real-time nature also opens the door to sophisticated fraud schemes—ranging from GPS spoofing to payment abuse and fake accounts. Traditional fraud detection methods fall short in speed and adaptability. By using Apache Kafka and Apache Flink, leading mobility platforms now detect and block fraud as it happens, protecting their revenue, users, and trust. This blog explores how real-time data streaming is transforming fraud prevention across the mobility industry.
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Electric Vehicle (EV) Charging - Automotive and ESG with Data Streaming at Virta
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  • 8 minute read

Virta’s Electric Vehicle (EV) Charging Platform with Real-Time Data Streaming: Scalability for Large Charging Businesses

The rise of Electric Vehicles (EVs) demands a scalable, efficient charging network—but challenges like fluctuating demand, complex billing, and real-time availability updates must be addressed. Virta, a global leader in smart EV charging, is tackling these issues with real-time data streaming. By leveraging Apache Kafka and Confluent Cloud, Virta enhances energy distribution, enables predictive maintenance, and supports dynamic pricing. This approach optimizes operations, improves user experience, and drives sustainability. Discover how real-time data streaming is shaping the future of EV charging and enabling intelligent, scalable infrastructure.
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Event-Driven Agentic AI with Data Streaming using Apache Kafka and Flink
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  • 12 minute read

How Apache Kafka and Flink Power Event-Driven Agentic AI in Real Time

Agentic AI marks a major evolution in artificial intelligence—shifting from passive analytics to autonomous, goal-driven systems capable of planning and executing complex tasks in real time. To function effectively, these intelligent agents require immediate access to consistent, trustworthy data. Traditional batch processing architectures fall short of this need, introducing delays, data staleness, and rigid workflows. This blog post explores why event-driven architecture (EDA)—powered by Apache Kafka and Apache Flink—is essential for building scalable, reliable, and adaptive AI systems. It introduces key concepts such as Model Context Protocol (MCP) and Google’s Agent-to-Agent (A2A) protocol, which are redefining interoperability and context management in multi-agent environments. Real-world use cases from finance, healthcare, manufacturing, and more illustrate how Kafka and Flink provide the real-time backbone needed for production-grade Agentic AI. The post also highlights why popular frameworks like LangChain and LlamaIndex must be complemented by robust streaming infrastructure to support stateful, event-driven AI at scale.
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Shift Left Architecture at Siemens with Stream Processing using Apache Kafka and Flink
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  • 6 minute read

Shift Left Architecture at Siemens: Real-Time Innovation in Manufacturing and Logistics with Data Streaming

Industrial enterprises face increasing pressure to move faster, automate more, and adapt to constant change—without compromising reliability. Siemens Digital Industries addresses this challenge by combining real-time data streaming, modular design, and Shift Left principles to modernize manufacturing and logistics. This blog outlines how technologies like Apache Kafka, Apache Flink, and Confluent Cloud support scalable, event-driven architectures. A real-world example from Siemens’ Modular Intralogistics Platform illustrates how this approach improves data quality, system responsiveness, and operational agility.
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The Importance of Focus for Software and Cloud Vendors - Data Streaming with Apache Kafka and Flink
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  • 15 minute read

The Importance of Focus: Why Software Vendors Should Specialize Instead of Doing Everything (Example: Data Streaming)

As real-time technologies reshape IT architectures, software vendors face a critical decision: specialize deeply in one domain or build a broad, general-purpose stack. This blog examines why a focused approach—particularly in the world of data streaming—delivers greater innovation, scalability, and reliability. It compares leading platforms and strategies, from specialized providers like Confluent to generalist cloud ecosystems, and highlights the operational risks of fragmented tools. With data streaming emerging as its own software category, enterprises need clarity, consistency, and deep expertise. In this post, we argue that specialization—not breadth—is what powers mission-critical, real-time applications at global scale.
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  • 5 minute read

The Top 20 Problems with Batch Processing (and How to Fix Them with Data Streaming)

Batch processing introduces delays, complexity, and data quality issues that modern businesses can no longer afford. This article outlines the most common problems with batch workflows—ranging from outdated insights to compliance risks—and illustrates each with real-world examples. It also highlights how real-time data streaming offers a more reliable, scalable, and future-proof alternative.
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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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  • 11 minute read

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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How Data Streaming and AI Help Telcos - Top 5 Trends from MWC 2025
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  • 7 minute read

How Data Streaming and AI Help Telcos to Innovate: Top 5 Trends from MWC 2025

As the telecom and tech industries rapidly evolve, real-time data streaming is emerging as the backbone of digital transformation. For MWC 2025, McKinsey outlined five key trends defining the future: IT excellence, sustainability, 6G, generative AI, and AI-driven software development. This blog explores how data streaming powers each of these trends, enabling real-time observability, AI-driven automation, energy efficiency, ultra-low latency networks, and faster software innovation. From Dish Wireless’ cloud-native 5G network to Verizon’s edge AI deployments, leading companies are leveraging event-driven architectures to gain a competitive advantage. Whether you’re tackling network automation, sustainability challenges, or AI monetization, data streaming is the strategic enabler for 2025 and beyond. Read on to explore the latest use cases, industry insights, and how to future-proof your telecom strategy.
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Data Streaming with Apache Kafka and Flink as the Backbone for a B2B Data Marketplace
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  • 7 minute read

Data Streaming as the Technical Foundation for a B2B Marketplace

A B2B data marketplace empowers businesses to exchange, monetize, and leverage real-time data through self-service platforms featuring subscription management, usage-based billing, and secure data sharing. Built on data streaming technologies like Apache Kafka and Flink, these marketplaces deliver scalable, event-driven architectures for seamless integration, real-time processing, and compliance. By exploring successful implementations like AppDirect, this post highlights how organizations can unlock new revenue streams and foster innovation with modern data marketplace solutions.
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Data Streaming with Apache Kafka and Flink in the Media Industry at Netflix Disney Plus Hotstar and Reliance JioCinema
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  • 8 minute read

Data Streaming with Apache Kafka and Flink in the Media Industry: Disney+ Hotstar and JioCinema

The $8.5 billion merger of Disney+ Hotstar and Reliance’s JioCinema marks a transformative moment for India’s media industry, combining two of the most influential streaming platforms into a data streaming powerhouse. This blog explores how technologies like Apache Kafka and Flink power these platforms, enabling massive-scale content distribution, real-time analytics, and user engagement. With tools like MirrorMaker and Cluster Linking, the merger presents opportunities for seamless Kafka migrations, hybrid multi-cloud flexibility, and new innovations like multi-angle viewing and advanced personalization. The transparency of both platforms about their Kafka-based architectures highlights their technical leadership and the lessons they offer the data streaming community. The integration of their infrastructures sets the stage for redefining media streaming in India, offering exciting insights and benchmarks for organizations leveraging data streaming at scale.
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