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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

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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Zeebe.io?—?a horizontally scalable distributed workflow engine

Bernd Rucker

Nothing will ever be changed once it is written, it is like a journal in accounting. Currently this is the only supported storage option (other options like e.g. Apache Cassandra are regularly discussed, but not on the roadmap so far). I tackled idempotency briefly in 3 common pitfalls of microservices integration?—?and

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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.

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Journey to Event Driven – Part 2: Programming Models for the Event-Driven Architecture

Confluent

Do I need to use a microservices framework? Distributed object (RPC sync), service-oriented architecture (SOA), enterprise service bus (ESB), event-driven architecture (EDA), reactive programming to microservices and now FaaS have each built on the learnings of the previous. Event-driven architecture. Comparing persistence models.

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

Confluent

Microservices, Apache Kafka, and Domain-Driven Design (DDD) covers this in more detail. Apache Kafka is an event streaming platform that combines messaging, storage, and processing of data to build highly scalable, reliable, secure, and real-time infrastructure. Long-term storage and buffering. High throughput. Large scale.

IoT 20
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How we built a highly scalable distributed state machine

Bernd Rucker

like a journal in accounting. Storage Zeebe writes the log to disk and RocksDB also flushes its state to disk. We regularly discuss making storage logic pluggable?—?for I contrasted this to traditional workflow engine architectures using a RDMS in part 1 of this blog post. Nothing will ever be changed once its written?—?like