# Integrate Confluent Cloud Metrics API with Third-Party Monitoring Tools Integrating directly with a third-party monitoring tool allows you to monitor Confluent Cloud alongside the rest of your applications. Confluent Cloud publishes the full list of available metrics at [Confluent Cloud Metrics Reference](https://api.telemetry.confluent.cloud/docs/descriptors/datasets/cloud). All metrics are accessible through the Metrics API `/query` endpoint, and any metrics marked as exportable are also available through the `/export` endpoint. If specific metrics from this list do not appear in your third-party monitoring tool, contact your monitoring vendor to request support for those metrics. ## Datadog Datadog provides an integration that connects to Confluent Cloud using a resource-scoped API key. After you select resources to monitor, Datadog displays metrics in an out-of-the-box dashboard within minutes. If you use Datadog, create your Confluent Cloud API key and follow [the instructions](https://docs.datadoghq.com/integrations/confluent_cloud/) from Datadog to get started. After configuring the integration, search the Datadog dashboards for “Confluent Cloud Overview,” the default Confluent Cloud dashboard at Datadog. Clone the default dashboard so that you can edit it to suit your needs. Datadog as a third-party integration in Confluent Cloud is an early access feature. For more information, see [Manage observability integrations](manage-observability-integrations.md#manage-observability-integrations). ## Dynatrace Dynatrace provides an extension that connects to Confluent Cloud using a resource-scoped API key. After you select resources to monitor, Dynatrace displays metrics in a prebuilt dashboard within minutes. If you use Dynatrace, create your Confluent Cloud API key and follow [the instructions](https://www.dynatrace.com/hub/detail/confluent-cloud-kafka/) to get started. ## Grafana Cloud Grafana Cloud provides an integration that connects to Confluent Cloud using a resource-scoped API key. After you select resources to monitor, Grafana Cloud displays metrics in an out-of-the-box dashboard within minutes. ### Set up Grafana Metrics Endpoint for the latest metrics The default [Grafana integration for Confluent Cloud](https://grafana.com/docs/grafana-cloud/integrations/integrations/integration-confluent-cloud/) doesn’t include metrics launched after the integration’s own last update. Use Metrics Endpoint in Grafana Cloud to access the latest Confluent Cloud metrics. A scrape job in Grafana is a configuration that tells Grafana Cloud’s Metrics Endpoint to collect, or scrape, metrics from a specified source, such as a Prometheus-compatible endpoint. These jobs define what to monitor, how often to collect data, and what to do with the data afterward. After you create a scrape job, no further management is required. Grafana Cloud automatically handles the scraping of metrics from Confluent Cloud into Grafana Cloud. #### Considerations - You must use an API key resource-scoped for resource management to communicate with the Metrics API. For more information, see [Create an API key to authenticate to the Metrics API](metrics-api.md#ccloud-add-metricsviewer-role-to-new-service-account). - API keys resource-scoped for Apache Kafka® clusters cause an authentication error. - This topic contains steps for a third-party tool that might change without notice. #### Get resource IDs for scrape jobs You must use Confluent Cloud resource IDs to create URLs for the scrape job. For more information, see [Discover resources and metrics with the Metrics API](metrics-api.md#ccloud-metrics-discovery) and the [Metrics API reference](https://api.telemetry.confluent.cloud/docs#tag/Version-2/paths/~1v2~1metrics~1%7Bdataset%7D~1export/get). For example, to scrape metrics of compute pools, you would use the resource ID for compute pools, which looks like this: `lfcp-examp2` Use the resource ID to create the scrape job URL: ```text https://api.telemetry.confluent.cloud/v2/metrics/cloud/export?resource.compute_pool.id=lfcp-examp2 ``` #### Create a scrape job A scrape job configures Grafana Cloud’s Metrics Endpoint to scrape metrics from a Confluent Cloud resource on a schedule. To create one, add a new connection in Grafana, configure the **Metrics Endpoint** integration, and enter your Confluent Cloud API key and secret as Basic authentication credentials, as described in the following steps. After you create the scrape job, you can modify it to scrape other resources or completely delete the scrape job by returning to **Metrics Endpoint**. Grafana integrations for Confluent Cloud use the API key and secret as a form of basic authentication. Use the Confluent Cloud API key as the username and the API secret as the password. To avoid transcription errors, copy the API key and secret from Confluent Cloud and paste them into the scrape job. If you encounter an error testing your connection, be sure that you have entered the right API credentials from your Confluent Cloud account.  To create scrape jobs: 1. In your Grafana instance, click **Connections** and then click **Add new connection**. 2. In **Search connections**, enter `Metrics Endpoint` and select the **Metrics Endpoint** integration. 3. In the **Metrics Endpoint** integration, click **Configuration details**. If you already have a scrape job, click **Add new scrape job**. 4. In **Scrape job name**, enter a name for your scrape job. 5. In **Scrape job URL**, enter a URL that contains the resource IDs that need to be scraped. 6. In **Scrape interval**, select an appropriate interval for scrapes. 7. In **Types of authentication credentials**, click **Basic**. 8. In **Basic username**, enter your Confluent Cloud API key. 9. In **Basic password**, enter your Confluent Cloud API secret. 10. To test the connection, click **Test Connection**. 11. To save your work, click **Save scrape job**. #### Create a dashboard A dashboard visualizes Confluent Cloud metrics that Grafana Cloud scrapes through the **Metrics Endpoint**.  To create dashboards: 1. In your Grafana instance, click **Dashboards** then click **New** and select **New dashboard**. 2. Click **Add visualization**. 3. To create a visualization, select a data source, metrics, and filters. ## Prometheus Prometheus servers can scrape the Confluent Cloud Metrics API directly by making use of the `export` endpoint. This endpoint returns the single most recent data point for each metric, for each distinct combination of labels. It returns this data in the Prometheus exposition or Open Metrics format. For more information, see [Export metric values](https://api.telemetry.confluent.cloud/docs?#tag/Version-2/paths/~1v2~1metrics~1{dataset}~1export/get). ## New Relic OpenTelemetry You can collect metrics about your Confluent Cloud-managed Kafka deployment with the New Relic OpenTelemetry collector. The collector is a component of OpenTelemetry that collects, processes, and exports telemetry data to New Relic, or any observability backend. For more information, see [Monitoring Confluent Cloud Kafka with OpenTelemetry Collector](https://github.com/newrelic/newrelic-opentelemetry-examples/tree/main/other-examples/collector/confluentcloud). ## Related content - [Discover resources and metrics with the Metrics API](metrics-api.md#ccloud-metrics-discovery) - [Metrics API reference](https://api.telemetry.confluent.cloud/docs#tag/Version-2/paths/~1v2~1metrics~1%7Bdataset%7D~1export/get) - [Grafana integration](https://grafana.com/docs/grafana-cloud/monitor-infrastructure/integrations/integration-reference/integration-confluent-cloud/)