# Monitor SDK metrics with Prometheus and Grafana > Set up Temporal SDK metrics with Prometheus and Grafana for monitoring Workers and Client performance. SDK metrics are emitted by SDK Clients used to start your Workers and to start, signal, or query your Workflow Executions. Unlike [Temporal Cloud metrics](/cloud/metrics/), which are exposed through a Prometheus HTTP API endpoint, SDK metrics require you to set up a Prometheus scrape endpoint in your application code for Prometheus to collect and aggregate. For a full list of available SDK metrics and their descriptions, see the [SDK metrics reference](/references/sdk-metrics). The process for setting up SDK metrics includes the following steps: 1. [Expose a metrics endpoint](#sdk-metrics-setup) in your application code where Prometheus can scrape SDK metrics. 2. [Configure Prometheus](#prometheus-configuration) to scrape your SDK metrics endpoints. 3. [Add an SDK metrics data source](#grafana-data-source-configuration) in Grafana. 4. [Set up dashboards](#grafana-dashboards-setup) to visualize SDK metrics. Set up your connections to Temporal Cloud using an SDK of your choice and have some Workflows running on Temporal Cloud. Ensure Prometheus and Grafana are installed. - [Go](/develop/go/client/temporal-client#connect-to-temporal-cloud) - [Java](/develop/java/client/temporal-client#connect-to-temporal-cloud) - [Python](/develop/python/client/temporal-client#connect-to-temporal-cloud) - [TypeScript](/develop/typescript/client/temporal-client#connect-to-temporal-cloud) - [.NET](/develop/dotnet/client/temporal-client#connect-to-temporal-cloud) ## Expose a metrics endpoint You must configure a Prometheus scrape endpoint for Prometheus to collect and aggregate your SDK metrics. Each language development guide has details on how to set this up. - [Go SDK](/develop/go/platform/observability#metrics) - [Java SDK](/develop/java/platform/observability#metrics) - [TypeScript SDK](/develop/typescript/platform/observability#metrics) - [Python](/develop/python/platform/observability#metrics) - [.NET](/develop/dotnet/platform/observability#metrics) For working examples of how to configure metrics in each SDK, see the metrics samples: - [Go SDK Samples](https://github.com/temporalio/samples-go/tree/main/metrics) - [Java SDK Samples](https://github.com/temporalio/samples-java/tree/main/core/src/main/java/io/temporal/samples/metrics) - [TypeScript SDK Samples](https://github.com/temporalio/samples-typescript/tree/main/interceptors-opentelemetry) - [Python SDK Samples](https://github.com/temporalio/samples-python/tree/main/custom_metric) - [.NET SDK Samples](https://github.com/temporalio/samples-dotnet/tree/main/src/OpenTelemetry/DotNetMetrics) Some examples use OpenTelemtry to instrument metrics. It is useful to use a [Prometheus exporter with OpenTelemetry](https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/exporter/prometheusexporter) to expose metrics for scraping. ## Configure Prometheus For Temporal SDKs, you must have Prometheus running and configured to listen on the scrape endpoints exposed in your application code. For this example, you can run Prometheus locally or as a Docker container. In either case, ensure that you set the listen targets to the ports where you expose your scrape endpoints. This configuration assumes the scrape endpoint is set to port 8077 as in the [SDK metrics setup](#sdk-metrics-setup) example. ```yaml global: scrape_interval: 30s # Set the scrape interval to every 30 seconds. Default is every 1 minute. #... # Set your scrape configuration targets to the ports exposed on your endpoints in the SDK. scrape_configs: - job_name: 'temporalsdkmetrics' metrics_path: /metrics scheme: http static_configs: - targets: # This is the scrape endpoint where Prometheus listens for SDK metrics. - localhost:8077 # You can have multiple targets here, provided they are set up in your application code. ``` See the [Prometheus documentation](https://prometheus.io/docs/introduction/first_steps/) for more details on how you can run Prometheus locally or using Docker. To check whether Prometheus is receiving metrics from your SDK target, go to [http://localhost:9090](http://localhost:9090) and navigate to **Status > Targets**. The status of your target endpoint defined in your configuration appears here. ## Add an SDK metrics data source in Grafana Depending on how you use Grafana, you can either install and run it locally, run it as a Docker container, or log in to Grafana Cloud to set up your data sources. If you have installed and are running Grafana locally, go to [http://localhost:3000](http://localhost:3000) and sign in. To add the SDK metrics Prometheus endpoint as a data source, do the following: 1. Go to **Configuration > Data sources**. 2. Select **Add data source > Prometheus**. 3. Enter a name for your SDK metrics data source, such as _Temporal SDK metrics_. 4. In the **HTTP** section, enter your Prometheus endpoint in the URL field. If running Prometheus locally as described in the examples in this article, enter `http://localhost:9090`. 5. For this example, enable **Skip TLS Verify** in the **Auth** section. 6. Click **Save and test** to verify that the data source is working. If you see issues in setting this data source, check whether the endpoints set in your SDKs are showing metrics. If you don't see your SDK metrics at the scrape endpoints defined, check whether your Workers and Workflow Executions are running. If you see metrics on the scrape endpoints, but Prometheus shows your targets are down, then there is an issue with connecting to the targets set in your SDKs. Verify your Prometheus configuration and restart Prometheus. If you're running Grafana as a container, you can set your SDK metrics Prometheus data source in your Grafana configuration. See the example Grafana configuration described in the [Prometheus and Grafana setup for open-source Temporal Service](/self-hosted-guide/monitoring#grafana) article. ## Set up Grafana dashboards To set up SDK metrics dashboards in Grafana, you can use the UI or configure them directly in your Grafana deployment. > **💡 Tip:** > > Temporal provides community-driven [example dashboards for Temporal SDKs](https://github.com/temporalio/dashboards/tree/master/sdk) that you can customize to meet your needs. > To import a dashboard in Grafana: 1. In the navigation bar, select **Dashboards** > **Import dashboard**. 2. You can either copy and paste the JSON from the [Temporal SDK sample dashboards](https://github.com/temporalio/dashboards/tree/master/sdk), or import the JSON files into Grafana. 3. Save the dashboard and review the metrics data in the graphs. To configure dashboards with the UI: 1. Go to **Create > Dashboard** and add an empty panel. 2. On the **Panel configuration** page, in the **Query** tab, select the "Temporal SDK metrics" data source that you configured earlier. 3. Expand the **Metrics browser** and select the metrics you want. A list of Worker performance metrics is described in the [Developer's Guide - Worker performance](/develop/worker-performance). All SDK-related metrics are listed in the [SDK metrics](/references/sdk-metrics) reference. 4. The graph should now display data based on your selected queries. Note that SDK metrics will only show if you have Workflow Execution data and running Workers. If you don't see SDK metrics, run your Worker and Workflow Executions, then monitor the dashboard.