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Cloud

88 posts
The Importance of Focus for Software and Cloud Vendors - Data Streaming with Apache Kafka and Flink
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  • 800 views
  • 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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Data Streaming with Apache Kafka and Flink as the Backbone for a B2B Data Marketplace
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  • 844 views
  • 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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SaaS vs PaaS Cloud Service for Data Streaming with Apache Kafka and Flink
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  • 1.9K views
  • 6 minute read

Fully Managed (SaaS) vs. Partially Managed (PaaS) Cloud Services for Data Streaming with Kafka and Flink

The cloud revolution has reshaped how businesses deploy and manage data streaming with solutions like Apache Kafka and Flink. Distinctions between SaaS and PaaS models significantly impact scalability, cost, and operational complexity. Bring Your Own Cloud (BYOC) expands the options, giving businesses greater flexibility in cloud deployment. Misconceptions around terms like “serverless” highlight the need for deeper analysis to avoid marketing pitfalls. This blog explores deployment options, enabling informed decisions tailored to your data streaming needs.
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Intelligent Traffic System for Tolling with Dynamic Pricing and Enforcement with Apache Kafka
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  • 9 minute read

IoT and Data Streaming with Kafka for a Tolling Traffic System with Dynamic Pricing

In the rapidly evolving landscape of intelligent traffic systems, innovative software provides real-time processing capabilities, dynamic pricing and new customer experiences, particularly in the domains of tolling, payments and safety inspection. This blog post explores success stories from Quarterhill and DKV Mobility providing traffic and payment systems for tolls. Data streaming powered by Apache Kafka has been pivotal in the journey towards building intelligent traffic systems in the cloud.
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Fraud Prevention with Apache Kafka in Real Time in Financial Services and Banking
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  • 2.3K views
  • 4 minute read

Fraud Prevention in Under 60 Seconds with Apache Kafka: How A Bank in Thailand is Leading the Charge

In financial services, the ability to prevent fraud in real-time is not just a competitive advantage – it is a necessity. For one of the largest banks in Thailand Krungsri (Bank of Ayudhya), with its vast assets, loans, and deposits, the challenge of fraud prevention has taken center stage. This blog post explores how the bank is leveraging data streaming with Apache Kafka to detect and block fraudulent transactions in under 60 seconds to ensure the safety and trust of its customers.
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Apache Kafka Deployment Options - Serverless vs Self-Managed vs BYOC Bring Your Own Cloud
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  • 9 minute read

Deployment Options for Apache Kafka: Self-Managed, Fully-Managed / Serverless and BYOC (Bring Your Own Cloud)

BYOC (Bring Your Own Cloud) is an emerging deployment model for organizations looking to maintain greater control over their cloud environments. Unlike traditional SaaS models, BYOC allows businesses to host applications within their own VPCs to provide enhanced data privacy, security, and compliance. This approach leverages existing cloud infrastructure. It offers more flexibility for custom configurations, particularly for companies with stringent security needs. In the data streaming sector around Apache Kafka, BYOC is changing how platforms are deployed. Organizations get more control and adaptability for various use cases. But it is clearly NOT the right choice for everyone!
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Multi-Cloud Replication in Real-Time with Apache Kafka and Cluster Linking
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  • 5 minute read

Multi-Cloud Replication in Real-Time with Apache Kafka and Cluster Linking

Multiple Apache Kafka clusters are the norm; not an exception anymore. Hybrid integration and multi-cloud replication for migration or disaster recovery are common use cases. This blog post explores a real-world success story from financial services around the transition of a large traditional bank from on-premise data centers into the public cloud for multi-cloud data sharing between AWS and Azure.
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One Apache Kafka Cluster Type Does NOT Fit All Use Cases
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  • 4.5K views
  • 13 minute read

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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My Data Streaming Journey with Kafka and Flink - 7 Years at Confluent
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  • 4.8K views
  • 11 minute read

My Data Streaming Journey with Kafka & Flink: 7 Years at Confluent

Time flies… I joined Confluent seven years ago when Apache Kafka was mainly used by a few tech giants and the company had ~100 employees. This blog post explores my data streaming journey, including Kafka becoming a de facto standard for over 100,000 organizations, Confluent doing an IPO on the NASDAQ stock exchange, 5000+ customers adopting a data streaming platform, and emerging new design approaches and technologies like data mesh, GenAI, and Apache Flink. I look at the past, present and future of my personal data streaming journey. Both, from the evolution of technology trends and the journey as a Confluent employee that started in a Silicon Valley startup and is now part of a global software and cloud company.
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Snowflake and Apache Kafka Data Integration Anti Patterns Zero Reverse ETL
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  • 9 minute read

Snowflake Integration Patterns: Zero ETL and Reverse ETL vs. Apache Kafka

Snowflake is a leading cloud-native data warehouse. Integration patterns include batch data integration, Zero ETL and near real-time data ingestion with Apache Kafka. This blog post explores the different approaches and discovers its trade-offs. Following industry recommendations, it is suggested to avoid anti-patterns like Reverse ETL and instead use data streaming to enhance the flexibility, scalability, and maintainability of enterprise architecture.
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