114
edits
Changes
Jump to navigation
Jump to search
Created page with "An InfluxDB/Grafana stack has been set up to be able to follow essential metrics for Open Food Facts team. The dashboards can be viewed at https://metrics.openfoodfacts.org...."
An InfluxDB/Grafana stack has been set up to be able to follow essential metrics for Open Food Facts team.
The dashboards can be viewed at https://metrics.openfoodfacts.org.
This is different from monitoring
There is currently a single InfluxDB bucket (=similar to SQL database) ''off_metrics''.
There are two measurements (=similar to SQL table): ''facets'' and ''insights''.
=== insights ===
Save metrics about Robotoff ''product_insight'' PostgreSQL table. The export is performed daily at night time by Robotoff.
Columns:
* time: timestamp of the datapoint.
* annotation: annotation status of the insight, either 0, -1, 1 or <nil>.
* automatic_processing: whether the insight will be (or has been) automatically processed, either "True" or "False".
* predictor: the predictor of the insight (=model or method that generated the insight)
* reserved_barcode: either "False" or "True", if True the product barcode is a reserved barcode, mostly used for variable weight products
* type: the insight type, see [https://github.com/openfoodfacts/robotoff/blob/9598d29cc2a23b802ef6eff1c7c154607a6ccc93/robotoff/types.py#L51 InsightType] class in Robotoff codebase for a complete list.
* count: the number of insights with the previous characteristics.
* percent: the % of insights with the previous characteristics, over the total number of insights.
The dashboards can be viewed at https://metrics.openfoodfacts.org.
This is different from monitoring
There is currently a single InfluxDB bucket (=similar to SQL database) ''off_metrics''.
There are two measurements (=similar to SQL table): ''facets'' and ''insights''.
=== insights ===
Save metrics about Robotoff ''product_insight'' PostgreSQL table. The export is performed daily at night time by Robotoff.
Columns:
* time: timestamp of the datapoint.
* annotation: annotation status of the insight, either 0, -1, 1 or <nil>.
* automatic_processing: whether the insight will be (or has been) automatically processed, either "True" or "False".
* predictor: the predictor of the insight (=model or method that generated the insight)
* reserved_barcode: either "False" or "True", if True the product barcode is a reserved barcode, mostly used for variable weight products
* type: the insight type, see [https://github.com/openfoodfacts/robotoff/blob/9598d29cc2a23b802ef6eff1c7c154607a6ccc93/robotoff/types.py#L51 InsightType] class in Robotoff codebase for a complete list.
* count: the number of insights with the previous characteristics.
* percent: the % of insights with the previous characteristics, over the total number of insights.