IoT Integration with Kafka Connect, REST / HTTP, MQTT, OPC-UA – Lightboard Video
Kai Waehner
I just want to share my lightboard video recording. I talk about IoT integration and processing with Apache…
Apache Kafka vs. Middleware (MQ, ETL, ESB) – Slides + Video
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).
Apache Kafka + KSQL + TensorFlow for Data Scientists via Python + Jupyter Notebook
Streaming Processing with Apache Kafka and KSQL for Data Scientists via Python and Jupyter Notebooks to build analytic models with TensorFlow and Keras.
Deep Learning Example: Apache Kafka + Python + Keras + TensorFlow + Deeplearning4j
“Python + Keras + TensorFlow + DeepLearning4j + Apache Kafka + Kafka Streams” => New example added to my “Machine Learning + Kafka Streams Examples” Github project.
Big Data Spain: Talk about KSQL – The Streaming SQL Engine for Apache Kafka
KSQL – The Open Source Streaming SQL Engine for Apache Kafka => Slides from my talk at Big Data Spain 2018 are online. Check it out!
MQTT + Apache Kafka => Video Recording from Kafka Summit Available
Processing IoT Data from End to End with MQTT and Apache Kafka => Video recording of my talk at Kafka Summit SF 2018 is online.
Apache Kafka + MQTT = End-to-End IoT Integration (Code, Slides, Video)
MQTT and Apache Kafka are a perfect combination for end-to-end IoT integration from edge to data center. This post discusses two different approaches and refers to implementations on Github using Apache Kafka, Kafka Connect, Confluent MQTT Proxy and Mosquitto.
Deep Learning KSQL UDF for Streaming Anomaly Detection of MQTT IoT Sensor Data
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.
Apache Kafka vs. ESB / ETL / MQ
Read why enterprises leverage the open source ecosystem of Apache Kafka for successful integration of different legacy and modern applications instead of ESB, ETL or MQ.
Model Serving: Stream Processing vs. RPC / REST with Java, gRPC, Apache Kafka, TensorFlow
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.
