Manage your topic's configuration (partitions, replication factor, parameters), ACLs, quotas, users and get stats, without any effort with this library. It does not use the Kafka scripts and does not require ssh connection to the remote broker.

A real-time event pipeline around Kafka Ecosystem for Chicago Transit Authority.

This MLOps project productionizes a Deep Reinforcement Learning agent with a scalable, distributed data streaming infrastructure using Kafka and Ray. A thorough walkthrough of the code is described in this article on medium: https://ryanraymartin.medium.com/deep-reinforcement-learning-for-stock-trading-with-kafka-and-rllib-d738b9634675

A Kafka python library for Robotframework to test events(messages) in Kafka.

Detection of DDOS Attack using Kafka and Spark Streaming

Python prometheus client for kafka logsize(Prometheus基于kafka logsize监控)

Repo for a simple base python http server using Flask and Kafka-Python

Live sentiment analysis of tweets using Kafka

Learning Kafka Standalone and Distributed Mode

A scalable architecture for real-time log processing and visualization. Built with a Kafka-Spark ETL pipeline, DynamoDB for storing aggregate real-time metrics, and Python Dash for interactive dashboards. Designed for high-throughput log ingestion, real-time monitoring, and long-term storage.

Real-time data streaming project using Python, Pandas, and Confluent Kafka to publish and consume retail data through Kafka topics, demonstrating scalability and dynamic consumer behavior.

RealTimeIncrementalSync is a real-time data streaming system that fetches product updates from a MySQL database, serializes the data in Avro format, and streams it to Kafka. Kafka consumers deserialize the data and append it to JSON files, enabling real-time monitoring and analysis of product information.

Stream data between two databases . Supports both ddl and dml statements. Built on top of kafka and debezium in python

Building a streaming Kafka application to push live notifications for updates to views, likes, favorites and comments on Youtube videos.

Real-time data processing using Apache Kafka , Mongodb and PostgreSQL

EDA scalable, distributed backend system

The project's goal is to read data from sensors installed in heavy trucks and send it to Kafka. Apache Kafka is an application platform for distributed event storage and stream processing. Lastly, we are consuming data from Kafka to MongoDB

Stream Processing of website click data using Kafka and monitored and visualised using Prometheus and Grafana

A Real Time Stream Processing pipeline created with integration of Apache Spark, Kafka, Python and NodeJS . Application aims at capturing and analyzing the stream of fiscal transactions that are coming in.