You have previously deployed an ML model into gcp video

Full Certification Question

You have previously deployed an ML model into production, and as part of your ongoing maintenance, you collect all the raw requests directed to your model prediction service on a monthly basis. Subsequently, you select a subset of these requests for evaluation by a human labeling service to assess your model's performance. Over the course of a year, you have observed that your model's performance exhibits varying patterns: at times, there is a significant degradation in performance within a month, while in other instances, it takes several months before any noticeable decrease occurs. It's important to note that utilizing the labeling service incurs significant costs, but you also want to avoid substantial performance drops. In light of these considerations, you aim to establish an optimal retraining frequency for your model. This approach should enable you to maintain a consistently high level of performance while simultaneously minimizing operational costs. What steps should you take to achieve this?