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A simple Python-based distributed workflow engine
Python bindings for RocksDB used by faust-streaming
Simple integration of FastAPI with Faust Python Stream Processing Fork
The goal of this project is aimed at optimizing Bank Marketing Model through building an event streaming pipeline around Apache Kafka and its ecosystem that communicates with a Machine learning model microservice. Utilizing this to display the likelihood and status of Bank Customers in real time.
Projects completed in the Udacity Data Streaming Nanodegree program. Tech used: Apache Kafka, Kafka Connect, KSQL, Faust Stream Processing, Spark Structured Streaming
Django with Kafka, Debezium, and Faust for Email Sending using Change Data Capture
This project cover latest skills to process data in real-time by building fluency in modern data engineering tools, such as Apache Spark, Kafka, Spark Streaming, and Kafka Streaming.
An end-to-end, web event stream processing pipeline