Flexible and Reproducible RF Calibration using Google Cloud Workflows

Radio frequency measurement device calibration is a critical but often complex multi-step process in metrology. Traditional approaches can be manual and lack standardization, hindering efficiency and reproducibility. This study addresses these challenges by proposing and demonstrating an automated RF calibration process orchestrated by workflow management systems. Google Cloud Workflows is selected for proof of concept of the suggested approach. The methodology involves defining a serverless workflow that manages the sequential invocation of external services for measurement data acquisition and subsequent uncertainty calculation. The results confirm the successful execution of this workflow, including robust input validation, correct data transfer between services, and effective error management. This research validates workflow orchestration platforms as viable tools for automating and simplifying RF calibration procedures, thereby enhancing reproducibility, reducing manual intervention, and contributing to the broader digitalization efforts in metrology. The declarative nature of the workflow definition offers a transparent and maintainable solution for managing complex calibration logic and integrating distinct services.