diff --git a/daprdocs/content/en/operations/observability/metrics/metrics-overview.md b/daprdocs/content/en/operations/observability/metrics/metrics-overview.md
index deb7882cb..25d8075e7 100644
--- a/daprdocs/content/en/operations/observability/metrics/metrics-overview.md
+++ b/daprdocs/content/en/operations/observability/metrics/metrics-overview.md
@@ -72,8 +72,9 @@ spec:
 
 ## Configuring metrics for error codes
 
-You can enable additional metrics for [Dapr API error codes](https://github.com/dapr/dapr/blob/master/docs/reference/api/error_codes/) by setting `spec.metrics.recordErrorCodes` to `true`. See the specific metrics described in the [Dapr development docs](https://github.com/dapr/dapr/blob/master/docs/development/dapr-metrics.md).
+You can enable additional metrics for [Dapr API error codes](https://github.com/dapr/dapr/blob/master/docs/reference/api/error_codes/) by setting `spec.metrics.recordErrorCodes` to `true`. Dapr APIs which communicate back to its caller may return standardized error codes. As described in the [Dapr development docs](https://github.com/dapr/dapr/blob/master/docs/development/dapr-metrics.md), a new metric called `error_code_total` will be recorded, which will allow monitoring of error codes triggered by application, code, and category. See [package errorcodes](https://github.com/dapr/dapr/blob/master/pkg/messages/errorcodes/errorcodes.go) for specific codes and categories.
 
+Example configuration:
 ```yaml
 apiVersion: dapr.io/v1alpha1
 kind: Configuration
@@ -86,6 +87,21 @@ spec:
     recordErrorCodes: true
 ```
 
+Example metric:
+```json
+{
+  app_id="publisher-app",
+  category="state",
+  dapr_io_enabled="true",
+  error_code="ERR_STATE_STORE_NOT_CONFIGURED",
+  instance="10.244.1.64:9090",
+  job="kubernetes-service-endpoints",
+  namespace="my-app",
+  node="my-node",
+  service="publisher-app-dapr"
+}
+```
+
 ## Optimizing HTTP metrics reporting with path matching
 
 When invoking Dapr using HTTP, metrics are created for each requested method by default. This can result in a high number of metrics, known as high cardinality, which can impact memory usage and CPU.