Real-time equipment monitoring is essential in industries such as manufacturing and power generation, where machine performance directly affects operations. Utilizing IoT sensors, companies can stream and analyze data in real time, tracking metrics like temperature, vibration, and pressure to proactively address issues before they lead to equipment failure. This tutorial demonstrates how to build a real-time monitoring system using MQTT, Redpanda, and Snowflake to track machine temperature in a manufacturing setting with three factories. The system involves setting up an MQTT broker for data reception, using Redpanda Connect to ingest and forward data to Snowflake for storage and visualization on a dashboard. The process includes generating simulated temperature data with MQTT.js and visualizing it in Snowflake, enhancing operational efficiency and safety by ensuring machines operate within safe parameters. Additionally, the tutorial explores extending the monitoring system with machine learning for predictive analytics, using Redpanda Connect's integration with AI services for tasks such as prediction analysis and anomaly detection, thereby optimizing maintenance schedules and enhancing decision-making capabilities.