Yes, I have some information on metrics tracking and the article [Airbyte Monitoring with dbt and Metabase](https://airbyte.com/blog/airbyte-monitoring-with-dbt-and-metabase). The article is about a non-production way of collecting metrics with dbt and Metabase by accessing Airbyte's Postgres DB. The source code is open on [airbytehq/open-data-stack](https://github.com/airbytehq/open-data-stack). This method is more exploratory for data analysts and data engineers, as opposed to the Prometheus method, which is more suitable for DevOps engineers in production. For more information on collecting metrics with Airbyte, you can refer to the [Collecting Metrics](https://docs.airbyte.com/operator-guides/collecting-metrics) documentation. Airbyte supports two ways to collect metrics: using Datadog or Open Telemetry. To get started, you need to fill in the

METRIC_CLIENT

field in the

.env

file and deploy a container/pod called

metrics-reporter

. Here's an example of how to set up the `metrics-reporter`:

airbyte-metrics:     image: airbyte/metrics-reporter:${VERSION}     container_name: airbyte-metrics     environment:     - METRIC_CLIENT=${METRIC_CLIENT}     - OTEL_COLLECTOR_ENDPOINT=${OTEL_COLLECTOR_ENDPOINT}

For more details on setting up Datadog or Open Telemetry, you can refer to the [Datadog](https://docs.airbyte.com/operator-guides/collecting-metrics#datadog) and [Open Telemetry](https://docs.airbyte.com/operator-guides/collecting-metrics#open-telemetry) sections in the documentation.