Machine Learning and Real-Time Analytics in Apache Kafka Applications

What this post added

This post details two approaches for deploying machine learning models in Kafka applications: using model servers with RPC and embedding models directly into Kafka client applications. It provides code examples for both scenarios using TensorFlow and Kafka Streams, and discusses the trade-offs between the two methods. It also covers considerations for embedding models, such as performance and size, and briefly touches on cloud-native deployment with Kubernetes.