Shortening the updating and inputting of accurate and real-time stock data is crucial for smooth retail business operations at PT XYZ. The existing system had low availability, lacked scalability, and incurred high costs in managing inventory in real time. Implementing real-time stock streamline with automatic scaling and Google Cloud Pub/Sub can help achieve this goal. This system utilizes Google Cloud Pub/Sub as a message delivery platform to distribute stock information from sender to receiver in real-time. Auto-scaling is used to automatically increase or decrease the number of servers processing stock data based on demand. The system is designed using Python and integrated through libraries with the Google Cloud Platform. The results of this research prove that the system is capable of providing optimal performance and scalability with high availability, good security, and cost savings.