Browsing Tag

Cloud

207 posts
Telecom OSS Modernization with Data Streaming using Apache Kafka and Flink for Cloud-Native BSS and OTT Integration
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  • 6.7K views
  • 7 minute read

Telecom OSS Modernization with Data Streaming: From Legacy Burden to Cloud-Native Agility

OSS is critical for service delivery in telecom, yet legacy platforms have become rigid and costly. They slow innovation just as 5G, cloud native networks and OTT partnerships demand agility. This article explores how a data streaming platform with Apache Kafka and Flink helps telcos modernize OSS step by step, cut costs, accelerate time to market and turn OSS into the real time backbone for AI and event driven operations.
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Amazon MSK Forces a Kafka Cluster Migration from ZooKeeper to KRaft
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  • 4 minute read

In-Place Kafka Cluster Upgrades from ZooKeeper to KRaft are Not Possible with Amazon MSK

The Apache Kafka community introduced KIP-500 to remove ZooKeeper and replace it with KRaft, a new built-in consensus layer. This was a major milestone. It simplified operations, improved scalability, and reduced complexity. Importantly, Kafka supports smooth, zero downtime migrations from ZooKeeper to KRaft, even for large, business critical clusters. But NOT with Amazon MSK…
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Connected Car Vehicle API and Data Streaming with Apache Kafka and Flink in the Automotive Industry
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  • 7 minute read

Streaming the Automotive Future: Real-Time Infrastructure for Vehicle Data

Connected vehicles are transforming the automotive industry into a software-driven, data-centric ecosystem. While APIs provide access to critical vehicle data, they fall short when it comes to real-time intelligence and scalability. This post explores how data streaming with Apache Kafka and Apache Flink turns raw API responses into reusable, governed data products that support real-time operations, analytics, and innovation. Learn how industry leaders are combining APIs and event streaming to build modern automotive platforms -where real-time data becomes a strategic asset.
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Synchronous Multi-Region Replication with Apache Kafka Confluent WarpStream for Zero Data Loss Disaster Recovery
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  • 8 minute read

Multi-Region Kafka using Synchronous Replication for Disaster Recovery with Zero Data Loss (RPO=0)

Apache Kafka is the backbone of real-time data streaming. Choosing the right deployment model – self-managed, fully managed, or bring-your-own-cloud (BYOC) – is a strategic decision. It affects performance, compliance, and cost. This article explains the most common Kafka deployment strategies and highlights the innovation of synchronous multi-region replication to achieve zero data loss (RPO=0). Alternatives like stretched Kafka clusters, Confluent Multi-Region Clusters (MRC), and WarpStream offer different paths to RPO=0. They support critical workloads with strong durability and high availability. For mission critical and regulated use cases, zero data loss is no longer a future goal. It is now achievable with the right architecture.
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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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  • 6 minute read

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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  • 8 minute read

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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The Rise of Kappa Architecture in the Age of Agentic AI with Data Streaming using Apache Kafka and Flink
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  • 9 minute read

The Rise of Kappa Architecture in the Era of Agentic AI and Data Streaming

The shift from Lambda to Kappa architecture reflects the growing demand for unified, real-time data pipelines that serve both analytical and operational needs. With the rise of Agentic AI and streaming-first systems, Kappa—powered by Apache Kafka and Apache Flink—delivers low-latency, event-driven infrastructure that supports modern applications, from scalable data products to autonomous AI agents. Open table formats and Shift Left principles further establish Kappa as the foundation for consistent, governed, and future-ready data platforms.
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Real-Time FinOps with Data Streaming using Apache Kafka and Flink
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  • 6.6K views
  • 6 minute read

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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