First step is to export your usage data to BigQuerry. If you have this feature already enabled, you can skip this step.
Finish the settings and save. From this point, Google will start saving your usage data daily into the selected BigQuery dataset.
Once you have your billing export ready, you can connect our application with your dataset via the service account.
At this point, our app will run, generate the Machine learning model of your data monthly, and compare the daily data with it. Anomalies found will be sent to the app and a webhook will be triggered for each newly found anomaly.
Please note, that at the beginning of the usage of our app due to a lack of historical data, the model is not able to check anomalies correctly. This usually gets better each week with maximum precision after a month or so.
You can configure how sensitive should the detection be.
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