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Microservices, Apache Kafka, and Domain-Driven Design

Confluent

Microservices have a symbiotic relationship with domain-driven design (DDD)—a design approach where the business domain is carefully modeled in software and evolved over time, independently of the plumbing that makes the system work. In these projects, microservice architectures use Kafka as an event streaming platform. Microservices.

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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

Some examples of model deployment in Kafka environments are: Analytic models (TensorFlow, Keras, H2O and Deeplearning4j) embedded in Kafka Streams microservices. Anomaly detection of IoT sensor data with a model embedded into a KSQL UDF. RPC communication between Kafka Streams application and model server (TensorFlow Serving).

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Real-Time Analytics and Monitoring Dashboards with Apache Kafka and Rockset

Confluent

Prior to Rockset, Shruti led product management for Oracle Cloud, with a focus on AI, IoT, and blockchain. Kai’s main area of expertise lies within the fields of big data analytics, machine learning, integration, microservices, Internet of Things, stream processing, and blockchain.

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Internet of Things (IoT) and Event Streaming at Scale with Apache Kafka and MQTT

Confluent

Different teams can develop, maintain, and change integration to devices and machines without being dependent on other sources or the sink systems that process and analyze the data. Microservices, Apache Kafka, and Domain-Driven Design (DDD) covers this in more detail.

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