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).
Streaming Processing with Apache Kafka and KSQL for Data Scientists via Python and Jupyter Notebooks to build analytic models with TensorFlow and Keras.
Processing IoT Data from End to End with MQTT and Apache Kafka => Video recording of my talk at Kafka Summit SF 2018 is online.