This blog post discusses how to build a highly scalable, mission-critical microservice infrastructure with Apache Kafka, Kafka Streams, and Apache Mesos respectively in their vendor-supported platforms from Confluent and Mesosphere.
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 + Apache Mesos = Highly Scalable Microservices. Mission-critical deployments via DC/OS and Confluent on premise or public cloud.
I do a lot of presentations these days at meetups and conferences about how to leverage Apache Kafka and Kafka Streams to apply analytic models (built with H2O, TensorFlow, DeepLearning4J and other frameworks) to scalable, mission-critical environments. As many attendees have asked me, I created a video recording about this talk (focusing on live demos).
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.