This blog post takes a look at cutting edge technologies like Apache Kafka, Kubernetes, Envoy, Linkerd and Istio to implement a cloud-native service mesh for a scalable, robust and observable microservice architecture.
This post shares a slide deck and video recording of the differences between an event-driven streaming platform like Apache Kafka and middleware like Message Queues (MQ), Extract-Transform-Load (ETL) and Enterprise Service Bus (ESB).
KSQL UDF for sensor analytics. Leverages the new API features of KSQL to build UDF / UDAF functions easily with Java to do continuous stream processing with Apache Kafka. Use Case: Connected Cars – Real Time Streaming Analytics using Deep Learning.
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.
Apache Kafka + KSQL Live Demo using CSV, JSON, Apache Avro. 10min live demo to get introduced to KSQL – the streaming SQL engine for Apache Kafka. Write and deploy SQL queries for stream processing instead of source code.
KSQL is the open source, Apache 2.0 licensed streaming SQL engine on top of Apache Kafka. This post shows a deep dive (slides + video recording) including its relation to Kafka Connect and Kafka Streams, concepts, architecture and deployment options.
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