MQTT and Apache Kafka are a perfect combination for end-to-end IoT integration from edge to data center. This post discusses two different approaches and refers to implementations on Github using Apache Kafka, Kafka Connect, Confluent MQTT Proxy and Mosquitto.
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.
Apache Kafka + KSQL Live Demo using CSV, JSON, Apache Avro. 10min live demo to get introduced to KSQL – the streaming SQL engine for Apache Kafka. Write and deploy SQL queries for stream processing instead of source code.
Apache Kafka + Kafka Streams + Apache Mesos = Highly Scalable Microservices. Mission-critical deployments via DC/OS and Confluent on premise or public cloud.
Apache Kafka Streams to build Real Time Streaming Microservices. Apply Machine Learning / Deep Learning using Spark, TensorFlow, H2O.ai, etc. to add AI. Embed Kafka Streams into Java App, Docker, Kubernetes, Mesos, anything else.