Apache Kafka became the de facto standard for event streaming across the globe and industries. Machine Learning (ML)…
A digital twin is a virtual representation of something else. This can be a physical thing, process or…
Data integration and processing in Industrial IoT (IIoT, aka Industry 4.0 or Automation Industry). Apache Kafka, its ecosystem (Kafka Connect, KSQL) and Apache PLC4X are a great open source choice to implement this integration end to end in a scalable, reliable and flexible way.
Machine Learning / Deep Learning models can be used in different ways to do predictions. Natively in the application or hosted in a remote model server. Then you combine stream processing with RPC / Request-Response paradigm. This blog post shows examples of stream processing vs. RPC model serving using Java, Apache Kafka, Kafka Streams, gRPC and TensorFlow Serving.
I spoke at Voxxed Zurich 2018 about Apache Kafka as Event-Driven Open Source Streaming Platform. The talk includes…
I am happy that my first official Confluent blog post was published and want to link to it from by blog: How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka
Apache Kafka + Kafka Streams to Produductionize Neural Networks (Deep Learning). Models built with TensorFlow, DeepLearning4J, H2O. Slides from JavaOne 2017.
Case Study: How to Move from a (Middleware) Monolith to Cloud, Containers and Microservices leveraging Docker, Cloud Foundry, Kubernetes, Consul, Hystrix, API Management, and others cool things.
Comparison of Open Source IoT Integration Frameworks such as Eclipse Kura (+ Apache Camel), Node-RED, Flogo, Apache Nifi, StreamSets, and others… (slide and video recording)
Introduction to the Open Source IoT Integration Project Flogo to build very lightweight edge applications and microservices for cloud native containers / cloud platforms / serverless architectures.