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

Confluent

The Internet of Things (IoT) is getting more and more traction as valuable use cases come to light. Microservices, Apache Kafka, and Domain-Driven Design (DDD) covers this in more detail. Long-term storage and buffering. A key challenge, however, is integrating devices and machines to process the data in real time and at scale.

IoT 20
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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

This can either be built natively around the Kafka ecosystem, or you could use Kafka just for ingestion into another storage and processing cluster such as HDFS or AWS S3 with Spark. Some examples of model deployment in Kafka environments are: Analytic models (TensorFlow, Keras, H2O and Deeplearning4j) embedded in Kafka Streams microservices.

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

Confluent

Apache Kafka is an event streaming platform that combines messages, storage, and data processing. 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.