Should I use Apache Camel or Apache Kafka for my next integration project? The question is very valid and comes up regularly. This blog post explores both open-source frameworks and explains the difference between application integration and event streaming. The comparison discusses when to use Kafka or Camel, when to combine them, when not to use them at all. A decision tree shows how you can quickly qualify out one for the other.
The oil & gas and mining industries require edge computing for low latency and zero trust use cases. Most IT architectures are hybrid with big data analytics in the cloud and safety-critical data processing in disconnected and often air-gapped environments. This blog post shares a panel discussion that explores the challenges, use cases, and hardware/software/network technologies to reduce cost and innovate. A key focus is on the open-source framework Apache Kafka, the de facto standard for processing data in motion at the edge and in the cloud.
Real-time beats slow data in most use cases across industries. The rise of event-driven architectures and data in motion powered by Apache Kafka enables enterprises to build real-time infrastructure and applications. This blog post explores why the Kafka API became the de facto standard API for event streaming like Amazon S3 for object storage, and the tradeoffs of these standards and corresponding frameworks, products, and cloud services.
TOP 5 Event Streaming Architectures and Use Cases for 2021: Edge deployments, hybrid and multi-cloud architectures, service mesh-based microservices, streaming machine learning, and cybersecurity.
Apache Kafka became the de facto standard for event streaming across the globe and industries. Machine Learning (ML)…
Event Streaming is happening all over the world. This blog post explores real-life examples across industries for use…
Apache Kafka and Machine Learning for Real Time Supply Chain Optimization: Integrate in real time with the legacy world and proprietary IIoT protocols (like Siemens S7, Modbus, Beckhoff ADS, OPC-UA, et al). You can process the data at scale and then ingest it into a modern database or analytic / machine learning framework.
Kafka Operator for Kubernetes – Confluent Operator to establish a Cloud-Native Apache Kafka Platform on Kubernetes (OpenShift, CloudFoundry, Hybrid Cloud).