Browsing Tag

kafka

210 posts
The Future of Data Streaming with Apache Flink for Agentic AI Supporting A2A and MCP
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  • 8 minute read

The Future of Data Streaming with Apache Flink for Agentic AI

Agentic AI is moving into production. Autonomous, tool-using, goal-driven systems that need real-time data and context. Apache Kafka and Flink provide the event-driven foundation to run these agents at scale. With the new Flink Agents project (FLIP-531), Flink will natively support long-running, system-triggered AI agents integrated with LLMs, tools, and emerging protocols like MCP and A2A. This marks a major step toward reliable, enterprise-grade Agentic AI.
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The Rise of Diskless Apache Kafka with Object Storage and No Brokers
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The Rise of Diskless Kafka: Rethinking Brokers, Storage, and the Kafka Protocol

Apache Kafka has evolved from a data lake pipeline into the backbone of real-time transactional systems. The shift from broker-based storage to Tiered Storage and now to Diskless Kafka using cloud object storage redefines Kafka’s role. This blog explores the business value, technical architecture, and use cases of running Kafka without brokers, using the Kafka protocol as the foundation for scalable, cost-efficient event streaming.
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Data Streaming and AI in the Automotive Industry at OEMs like Porsche Tesla BMW
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  • 13 minute read

Driving the Future: How Real-Time Data Streaming Is Powering Automotive Innovation

The automotive industry is rapidly shifting toward a software-defined, data-driven future. Real-time technologies like Apache Kafka and Apache Flink are now critical to powering connected vehicles, smart factories, autonomous platforms, and personalized mobility services. This blog explores how leading OEMs and suppliers use data streaming to drive digital transformation – from edge processing and AI to predictive maintenance and customer experience. As the industry moves toward intelligent, adaptive systems, event-driven architecture becomes a strategic foundation.
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Agentic AI with AWS Amazon Bedrock AgentCore and Data Streaming using Apache Kafka Flink and Confluent Cloud
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Building Agentic AI with Amazon Bedrock AgentCore and Data Streaming Using Apache Kafka and Flink

Agentic AI goes beyond chatbots. These are autonomous systems that observe, reason, and act—continuously and in real time. At AWS Summit New York 2025, Amazon launched Bedrock AgentCore to build and operate secure, scalable AI agents. But to run in production, agents also need real-time data, continuous context, and flexible integration. That’s where data streaming with Apache Kafka and Apache Flink comes in. Combined with open standards like MCP and A2A, they provide the event-driven foundation for always-on, enterprise-grade AI agents.
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FourKites Supply Chain Logistics Control Tower Powered by AI and Data Streaming with Confluent and Kafka
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Inside FourKites Logistics Platform: Data Streaming for AI and End-to-End Visibility in the Supply Chain

Global supply chains face constant disruption. Trade conflicts, wars, inflation, and shifting regulations are making logistics more unpredictable than ever. Traditional systems can’t keep up with the speed and complexity of today’s challenges. This blog post shows how FourKites, a leader in supply chain visibility, uses data streaming with Apache Kafka in the cloud, and AI to power real-time logistics. With over 3 million shipments tracked daily, FourKites delivers more than visibility — it enables fast, autonomous decisions at global scale.
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Real-Time FinOps with Data Streaming using Apache Kafka and Flink
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FinOps in Real Time: How Data Streaming Transforms Cloud Cost Management

FinOps bridges the gap between finance and engineering to control cloud spend in real time. However, many organizations still rely on delayed, batch-driven data pipelines that limit visibility and slow down decisions. This blog explores how Apache Kafka and Apache Flink enable real-time, governed FinOps by streaming cloud usage data as it happens. It covers the challenges of data governance, compliance, and cross-functional accountability—and how streaming architecture addresses them. Real-world examples from Bitvavo and SumUp show how financial services companies scale securely, build cost-aware teams, and improve agility using event-driven platforms.
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Open RAN and Data Streaming with Apache Kafka and Flink in Telecom Industry for Network Analytics and Observability
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Open RAN and Data Streaming: How the Telecom Industry Modernizes Network Infrastructure with Apache Kafka and Flink

Open RAN is transforming telecom by decoupling hardware and software to unlock flexibility, innovation, and cost savings. But to fully realize its potential, telcos need real-time data streaming for observability, automation, and AI. This post shows how Apache Kafka, Apache Flink, and a diskless data streaming platform like Confluent WarpStream help telco operators scale RAN data processing securely and cost-effectively.
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FinTech Alpian using Data Streaming and Agentic AI with Apache Kafka in Switzerland Regulated Market
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  • 6 minute read

Agentic AI and RAG in Regulated FinTech with Apache Kafka at Alpian Bank

Regulated FinTech is transforming financial services by combining compliance with innovation. This post explores how real-time data streaming with Apache Kafka and Flink enables modern architecture, personalization, and AI integration—while maintaining strict governance. Alpian, a fully licensed Swiss digital bank, showcases how Agentic AI, RAG, and domain-driven design work together in a compliant, cloud-only environment.
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Real Time AI for Mobile Gaming and eSports at MPL with Data Streaming using Apache Kafka and Flink
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How MPL Uses Data Streaming to Lead in Mobile Gaming and eSports

Mobile Premier League (MPL) is a leading mobile eSports skill-based gaming platform with over 90 million users. To meet the demands of real-time personalization, fraud detection, and user engagement, MPL transitioned from traditional batch processing to a modern data streaming architecture powered by Apache Kafka, Apache Flink, and Confluent Cloud. This blog explores the architectural shift, key use cases—including real-time Machine Learning inference and feature orchestration—and the business outcomes achieved, such as increased trust, lower operational costs, and improved player retention. The MPL success story highlights the value of a data streaming platform in building responsive, intelligent, and secure gaming platforms.
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Mainframe Modernization and Integration with Data Streaming using Apache Kafka IBM MQ IIDR CDC Precisely Qlik
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  • 14 minute read

Mainframe Integration with Data Streaming: Architecture, Business Value, Real-World Success

The mainframe is evolving—not fading. With cloud-native features, AI acceleration, and quantum-safe encryption, platforms like IBM z16 and z17 remain central to critical industries. But modern demands require real-time data access and system agility. Apache Kafka and Flink make this possible by streaming data bi-directionally between DB2, IMS, and MQ and cloud analytics platforms. This enables event-driven architectures without disrupting core systems. This post outlines proven strategies—offloading, integration, and replacement—and includes real-world examples across industries. The result: lower costs, faster innovation, and smarter use of legacy systems.
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