Data integration and processing in Industrial IoT (IIoT, aka Industry 4.0 or Automation Industry). Apache Kafka, its ecosystem (Kafka Connect, KSQL) and Apache PLC4X are a great open source choice to implement this integration end to end in a scalable, reliable and flexible way.
Machine Learning / Deep Learning models can be used in different ways to do predictions. Natively in the application or hosted in a remote model server. Then you combine stream processing with RPC / Request-Response paradigm. This blog post shows examples of stream processing vs. RPC model serving using Java, Apache Kafka, Kafka Streams, gRPC and TensorFlow Serving.
See how stream processing / streaming analytics frameworks (e.g. Apache Spark, Apache Flink, Amazon Kinesis) and products (e.g. TIBCO StreamBase, Software AG’s Apama, IBM InfoSphere Streams) are categorized and compared. Besides, understand how stream processing is related to Big Data platforms such as Apache Hadoop and machine learning (e.g. R, SAS, MATLAB).
“Cloud Computing Architected – Solution Design Handbook” by John Rhoton and Risto Haukioja was published by Recursive Press in May 2011.
This book is a great addition to other books about cloud computing.
The Cloud-Camp was a free „Unconference“, which took place one day before the SOA / Cloud Symposium 2010 in Berlin, Germany. You can find more information about Cloud Camps at http://www.cloudcamp.org.
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