This article showcases Paolo Bergantino's journey in deploying a time-series database solution using TimescaleDB for AROYA, a cannabis production platform. Initially, AROYA used a combination of AWS services and a custom solution that was adequate but had performance issues with growing data volumes. Paolo recognized the need for a more scalable solution and researched various time-series databases, ultimately choosing TimescaleDB due to its continuous aggregates feature, which allowed for efficient compression and reduced storage needs. The deployment process involved optimizing bucket sizes, compressing data, and creating views to improve performance. With the new solution, AROYA has been able to ingest billions of readings monthly without compromising performance, and Paolo credits TimescaleDB with delivering a solid foundation for their infrastructure. The article highlights the importance of monitoring, load testing, and vigilance in ensuring the success of such deployments.