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Jetstream Data Products

Jetstream writes analysis results and enrollments information to BigQuery. Statistics data and metadata gets exported to GCS to make it accessible to the Experimenter console.

BigQuery Datasets#

Results Datasets#

The datasets that back the Experimenter results dashboards are available in BigQuery in the mozanalysis dataset in moz-fx-data-experiments. Technical documentation is available in the Mozilla data docs.

Monitoring Datasets#

Datasets used for monitoring the operation of Jetstream are part of the monitoring dataset in moz-fx-data-experiments.

Error Logs#

Jetstream logs errors and warning encountered during its analysis runs to monitoring.logs. This datasets is used as basis for the Jetstream error dashboard and for setting up alerts.

The logs table has the following schema:

Column nameTypeDescription
timestampTIMESTAMPTimestamp of when the log event was recorded
experimentSTRINGExperiment slug for which event was recorded
messageSTRINGLog message
log_levelSTRINGLog level: ERROR, WARNING
exceptionSTRINGRaised exception object
filenameSTRINGName the Jetstream code file the exception was raised
func_nameSTRINGName the Jetstream function the exception was raised
exception_typeSTRINGClass name the exception raised

Query Cost#

The monitoring.query_cost_v1 dataset contains the cost of each query run when analysing experiments. The dataset is updated daily and scrapes the cost information from the BigQuery logs. The query for determining the costs is part of bigquery-etl. The dataset is basis for the jetstream cost monitoring dashboard and alerts set up to send notifications when an analysis query exceeds a certain threshold.

The query_cost_v1 table has the following schema:

Column nameTypeDescription
submission_timestampTIMESTAMPTimestamp of when the query was executed
destination_tableSTRINGName of the table query was writing data to
querySTRINGSQL of the executed query
total_bytes_processedINT64Number of bytes the query processed
cost_usdFLOATCost of the query in USD based on BigQuery pricing

Experimenter Experiments#

For monitoring Nimbus experiments, some common failure cases are exposed as part of the Experiments Enrollments Grafana dashboard. These monitoring rules will require access to collected experiments enrollment data which is available in monitoring.experimenter_experiments_v1. This dataset is part of bigquery-etl and updated every 10 minutes by fetching data from the Experimenter API.

GCS Data Export#

Jetstream exports statistics data and metadata of analysed experiments to the mozanalysis GCS bucket.

Statistics Data#

After each analysis run has completed, Jetstream exports the statistics results of each experiments to the statistics sub-directory as JSON. The JSON files follow the naming format:


Each file contains a JSON object for every row in the corresponding statistics table. The JSON files are pulled in by Experimenter and used for visualizing results on the Experimenter results page.


Metadata of analyzed experiments contains information about all metrics and outcomes that are computed during any analysis period. Metadata is written to JSON files into the metadata sub-directory with the following naming schema:


Each JSON metadata file contains the following information:

"metrics": {
"metric_slug": {
"friendly_name": "Friendly metric name",
"description": "Metric description defined in mozanalysis or jetstream-config",
"bigger_is_better": true
// ...
"outcomes": {
"outcome_slug": {
"slug": "outcome_slug",
"friendly_name": "Friendly outcome name",
"description": "Outcome description defined in jetstream-config",
"metrics": [ // metrics computed as part of outcome
// commit hash of outcome version that was used in analysis
"commit_hash": "74e45eb4c3bf4ea7f1d65f888a70bfa0f6a86c1e"
// ...

Metadata of metrics and outcomes is used to show names, descriptions and whether larger numbers are better in the Experimenter results.