The text details a project undertaken during the Confluent Hackathon '22, where the author explored using Apache Kafka and other technologies to monitor wildlife. Initially testing the concept by tracking animals in his backyard with a Raspberry Pi, camera, and TensorFlow Lite for real-time object classification, he expanded the project by integrating a webcam feed from a local zoo to capture more exotic animals. Data collected was sent to a Kafka cluster and processed using ksqlDB to analyze wildlife trends, and a dashboard was created using Kibana to visualize these trends. Additionally, a Telegram bot was set up to alert the author of rare animal sightings, such as teddy bears detected by the model. This project highlighted the potential of combining streaming platforms, machine learning, and open-source tools to innovate wildlife monitoring and address real-world challenges.