Metrics

1. 1. 1. Why ? ###
      2. What ? ###
      3. 🎯 Roadmap for metrics harvesting ###

1. 1. 1. Reporting dashboard

An InfluxDB/Grafana stack has been set up to allow Open Food Facts team to be able to follow essential metrics. The dashboards can be viewed at https://metrics.openfoodfacts.org.

There is a read-only account, you can access the credentials on Slack to have access to it.

Metrics is different from monitoring (https://monitoring.openfoodfacts.org), we don't store on metrics.openfoodfacts.org infrastructure-related data.

We have 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:

• 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 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.

facets

Save metrics about Product Opener facets, using public facet API. The export is performed daily at night time by Robotoff by calling Product Opener API.

Current saved facets:

• ingredients-analysis
• data-quality
• ingredients
• states
• misc

Columns:

• country: the ISO 2-letter code of the country (ISO_3166-1 alpha-2), or "world" for metrics on the full database. Only a selected subset of country is available.
• facet: the name of the facet, it's the lower-case facet name with '-' replaced with '_' (ex: `data_quality` instead of `data-quality`)
• tag_name: name of the tag
• tag_id: identifier of the tag (ex: en:alcoholic-beverages-category-without-alcohol-value), this is the field you will probably have to use
• products: number of products with the given tag
• percent: % of products with the given tag over the total number of product for the country