---
title: Create a log-based metric
description: Datadog, the leading service for cloud-scale monitoring.
breadcrumbs: Docs > API Reference > Logs Metrics
---

# Create a log-based metric{% #create-a-log-based-metric %}
Copy pageCopied
{% tab title="v2" %}

| Datadog site      | API endpoint                                                  |
| ----------------- | ------------------------------------------------------------- |
| ap1.datadoghq.com | POST https://api.ap1.datadoghq.com/api/v2/logs/config/metrics |
| ap2.datadoghq.com | POST https://api.ap2.datadoghq.com/api/v2/logs/config/metrics |
| app.datadoghq.eu  | POST https://api.datadoghq.eu/api/v2/logs/config/metrics      |
| app.ddog-gov.com  | POST https://api.ddog-gov.com/api/v2/logs/config/metrics      |
| us2.ddog-gov.com  | POST https://api.us2.ddog-gov.com/api/v2/logs/config/metrics  |
| app.datadoghq.com | POST https://api.datadoghq.com/api/v2/logs/config/metrics     |
| us3.datadoghq.com | POST https://api.us3.datadoghq.com/api/v2/logs/config/metrics |
| us5.datadoghq.com | POST https://api.us5.datadoghq.com/api/v2/logs/config/metrics |

### Overview

Create a metric based on your ingested logs in your organization. Returns the log-based metric object from the request body when the request is successful. This endpoint requires the `logs_generate_metrics` permission.

### Request

#### Body Data (required)

The definition of the new log-based metric.

{% tab title="Model" %}

| Parent field | Field                              | Type     | Description                                                                                                                                |
| ------------ | ---------------------------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
|              | data [*required*]             | object   | The new log-based metric properties.                                                                                                       |
| data         | attributes [*required*]       | object   | The object describing the Datadog log-based metric to create.                                                                              |
| attributes   | compute [*required*]          | object   | The compute rule to compute the log-based metric.                                                                                          |
| compute      | aggregation_type [*required*] | enum     | The type of aggregation to use. Allowed enum values: `count,distribution`                                                                  |
| compute      | include_percentiles                | boolean  | Toggle to include or exclude percentile aggregations for distribution metrics. Only present when the `aggregation_type` is `distribution`. |
| compute      | path                               | string   | The path to the value the log-based metric will aggregate on (only used if the aggregation type is a "distribution").                      |
| attributes   | filter                             | object   | The log-based metric filter. Logs matching this filter will be aggregated in this metric.                                                  |
| filter       | query                              | string   | The search query - following the log search syntax.                                                                                        |
| attributes   | group_by                           | [object] | The rules for the group by.                                                                                                                |
| group_by     | path [*required*]             | string   | The path to the value the log-based metric will be aggregated over.                                                                        |
| group_by     | tag_name                           | string   | Eventual name of the tag that gets created. By default, the path attribute is used as the tag name.                                        |
| data         | id [*required*]               | string   | The name of the log-based metric.                                                                                                          |
| data         | type [*required*]             | enum     | The type of the resource. The value should always be logs_metrics. Allowed enum values: `logs_metrics`                                     |

{% /tab %}

{% tab title="Example" %}

```json
{
  "data": {
    "id": "ExampleLogsMetric",
    "type": "logs_metrics",
    "attributes": {
      "compute": {
        "aggregation_type": "distribution",
        "include_percentiles": true,
        "path": "@duration"
      }
    }
  }
}
```

{% /tab %}

### Response

{% tab title="200" %}
OK
{% tab title="Model" %}
The log-based metric object.

| Parent field | Field               | Type     | Description                                                                                                                                |
| ------------ | ------------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
|              | data                | object   | The log-based metric properties.                                                                                                           |
| data         | attributes          | object   | The object describing a Datadog log-based metric.                                                                                          |
| attributes   | compute             | object   | The compute rule to compute the log-based metric.                                                                                          |
| compute      | aggregation_type    | enum     | The type of aggregation to use. Allowed enum values: `count,distribution`                                                                  |
| compute      | include_percentiles | boolean  | Toggle to include or exclude percentile aggregations for distribution metrics. Only present when the `aggregation_type` is `distribution`. |
| compute      | path                | string   | The path to the value the log-based metric will aggregate on (only used if the aggregation type is a "distribution").                      |
| attributes   | filter              | object   | The log-based metric filter. Logs matching this filter will be aggregated in this metric.                                                  |
| filter       | query               | string   | The search query - following the log search syntax.                                                                                        |
| attributes   | group_by            | [object] | The rules for the group by.                                                                                                                |
| group_by     | path                | string   | The path to the value the log-based metric will be aggregated over.                                                                        |
| group_by     | tag_name            | string   | Eventual name of the tag that gets created. By default, the path attribute is used as the tag name.                                        |
| data         | id                  | string   | The name of the log-based metric.                                                                                                          |
| data         | type                | enum     | The type of the resource. The value should always be logs_metrics. Allowed enum values: `logs_metrics`                                     |

{% /tab %}

{% tab title="Example" %}

```json
{
  "data": {
    "attributes": {
      "compute": {
        "aggregation_type": "distribution",
        "include_percentiles": true,
        "path": "@duration"
      },
      "filter": {
        "query": "service:web* AND @http.status_code:[200 TO 299]"
      },
      "group_by": [
        {
          "path": "@http.status_code",
          "tag_name": "status_code"
        }
      ]
    },
    "id": "logs.page.load.count",
    "type": "logs_metrics"
  }
}
```

{% /tab %}

{% /tab %}

{% tab title="400" %}
Bad Request
{% tab title="Model" %}
API error response.

| Field                    | Type     | Description       |
| ------------------------ | -------- | ----------------- |
| errors [*required*] | [string] | A list of errors. |

{% /tab %}

{% tab title="Example" %}

```json
{
  "errors": [
    "Bad Request"
  ]
}
```

{% /tab %}

{% /tab %}

{% tab title="403" %}
Not Authorized
{% tab title="Model" %}
API error response.

| Field                    | Type     | Description       |
| ------------------------ | -------- | ----------------- |
| errors [*required*] | [string] | A list of errors. |

{% /tab %}

{% tab title="Example" %}

```json
{
  "errors": [
    "Bad Request"
  ]
}
```

{% /tab %}

{% /tab %}

{% tab title="409" %}
Conflict
{% tab title="Model" %}
API error response.

| Field                    | Type     | Description       |
| ------------------------ | -------- | ----------------- |
| errors [*required*] | [string] | A list of errors. |

{% /tab %}

{% tab title="Example" %}

```json
{
  "errors": [
    "Bad Request"
  ]
}
```

{% /tab %}

{% /tab %}

{% tab title="429" %}
Too many requests
{% tab title="Model" %}
API error response.

| Field                    | Type     | Description       |
| ------------------------ | -------- | ----------------- |
| errors [*required*] | [string] | A list of errors. |

{% /tab %}

{% tab title="Example" %}

```json
{
  "errors": [
    "Bad Request"
  ]
}
```

{% /tab %}

{% /tab %}

### Code Example

##### 
                          \## default
# 
 \# Curl command curl -X POST "https://api.datadoghq.com/api/v2/logs/config/metrics" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "DD-API-KEY: ${DD_API_KEY}" \
-H "DD-APPLICATION-KEY: ${DD_APP_KEY}" \
-d @- << EOF
{
  "data": {
    "attributes": {
      "compute": {
        "aggregation_type": "distribution",
        "include_percentiles": true,
        "path": "@duration"
      },
      "filter": {
        "query": "service:web* AND @http.status_code:[200 TO 299]"
      },
      "group_by": [
        {
          "path": "@http.status_code",
          "tag_name": "status_code"
        }
      ]
    },
    "id": "logs.page.load.count",
    "type": "logs_metrics"
  }
}
EOF 
                        
##### 

```go
// Create a log-based metric returns "OK" response

package main

import (
	"context"
	"encoding/json"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	body := datadogV2.LogsMetricCreateRequest{
		Data: datadogV2.LogsMetricCreateData{
			Id:   "ExampleLogsMetric",
			Type: datadogV2.LOGSMETRICTYPE_LOGS_METRICS,
			Attributes: datadogV2.LogsMetricCreateAttributes{
				Compute: datadogV2.LogsMetricCompute{
					AggregationType:    datadogV2.LOGSMETRICCOMPUTEAGGREGATIONTYPE_DISTRIBUTION,
					IncludePercentiles: datadog.PtrBool(true),
					Path:               datadog.PtrString("@duration"),
				},
			},
		},
	}
	ctx := datadog.NewDefaultContext(context.Background())
	configuration := datadog.NewConfiguration()
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewLogsMetricsApi(apiClient)
	resp, r, err := api.CreateLogsMetric(ctx, body)

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `LogsMetricsApi.CreateLogsMetric`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}

	responseContent, _ := json.MarshalIndent(resp, "", "  ")
	fmt.Fprintf(os.Stdout, "Response from `LogsMetricsApi.CreateLogsMetric`:\n%s\n", responseContent)
}
```

#### Instructions

First [install the library and its dependencies](https://docs.datadoghq.com/api/latest.md?code-lang=go) and then save the example to `main.go` and run following commands:
    DD_SITE="datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" go run "main.go"
##### 

```java
// Create a log-based metric returns "OK" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.LogsMetricsApi;
import com.datadog.api.client.v2.model.LogsMetricCompute;
import com.datadog.api.client.v2.model.LogsMetricComputeAggregationType;
import com.datadog.api.client.v2.model.LogsMetricCreateAttributes;
import com.datadog.api.client.v2.model.LogsMetricCreateData;
import com.datadog.api.client.v2.model.LogsMetricCreateRequest;
import com.datadog.api.client.v2.model.LogsMetricResponse;
import com.datadog.api.client.v2.model.LogsMetricType;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    LogsMetricsApi apiInstance = new LogsMetricsApi(defaultClient);

    LogsMetricCreateRequest body =
        new LogsMetricCreateRequest()
            .data(
                new LogsMetricCreateData()
                    .id("ExampleLogsMetric")
                    .type(LogsMetricType.LOGS_METRICS)
                    .attributes(
                        new LogsMetricCreateAttributes()
                            .compute(
                                new LogsMetricCompute()
                                    .aggregationType(LogsMetricComputeAggregationType.DISTRIBUTION)
                                    .includePercentiles(true)
                                    .path("@duration"))));

    try {
      LogsMetricResponse result = apiInstance.createLogsMetric(body);
      System.out.println(result);
    } catch (ApiException e) {
      System.err.println("Exception when calling LogsMetricsApi#createLogsMetric");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}
```

#### Instructions

First [install the library and its dependencies](https://docs.datadoghq.com/api/latest.md?code-lang=java) and then save the example to `Example.java` and run following commands:
    DD_SITE="datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" java "Example.java"
##### 

```python
"""
Create a log-based metric returns "OK" response
"""

from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.logs_metrics_api import LogsMetricsApi
from datadog_api_client.v2.model.logs_metric_compute import LogsMetricCompute
from datadog_api_client.v2.model.logs_metric_compute_aggregation_type import LogsMetricComputeAggregationType
from datadog_api_client.v2.model.logs_metric_create_attributes import LogsMetricCreateAttributes
from datadog_api_client.v2.model.logs_metric_create_data import LogsMetricCreateData
from datadog_api_client.v2.model.logs_metric_create_request import LogsMetricCreateRequest
from datadog_api_client.v2.model.logs_metric_type import LogsMetricType

body = LogsMetricCreateRequest(
    data=LogsMetricCreateData(
        id="ExampleLogsMetric",
        type=LogsMetricType.LOGS_METRICS,
        attributes=LogsMetricCreateAttributes(
            compute=LogsMetricCompute(
                aggregation_type=LogsMetricComputeAggregationType.DISTRIBUTION,
                include_percentiles=True,
                path="@duration",
            ),
        ),
    ),
)

configuration = Configuration()
with ApiClient(configuration) as api_client:
    api_instance = LogsMetricsApi(api_client)
    response = api_instance.create_logs_metric(body=body)

    print(response)
```

#### Instructions

First [install the library and its dependencies](https://docs.datadoghq.com/api/latest.md?code-lang=python) and then save the example to `example.py` and run following commands:
    DD_SITE="datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" python3 "example.py"
##### 

```ruby
# Create a log-based metric returns "OK" response

require "datadog_api_client"
api_instance = DatadogAPIClient::V2::LogsMetricsAPI.new

body = DatadogAPIClient::V2::LogsMetricCreateRequest.new({
  data: DatadogAPIClient::V2::LogsMetricCreateData.new({
    id: "ExampleLogsMetric",
    type: DatadogAPIClient::V2::LogsMetricType::LOGS_METRICS,
    attributes: DatadogAPIClient::V2::LogsMetricCreateAttributes.new({
      compute: DatadogAPIClient::V2::LogsMetricCompute.new({
        aggregation_type: DatadogAPIClient::V2::LogsMetricComputeAggregationType::DISTRIBUTION,
        include_percentiles: true,
        path: "@duration",
      }),
    }),
  }),
})
p api_instance.create_logs_metric(body)
```

#### Instructions

First [install the library and its dependencies](https://docs.datadoghq.com/api/latest.md?code-lang=ruby) and then save the example to `example.rb` and run following commands:
    DD_SITE="datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" rb "example.rb"
##### 

```rust
// Create a log-based metric returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_logs_metrics::LogsMetricsAPI;
use datadog_api_client::datadogV2::model::LogsMetricCompute;
use datadog_api_client::datadogV2::model::LogsMetricComputeAggregationType;
use datadog_api_client::datadogV2::model::LogsMetricCreateAttributes;
use datadog_api_client::datadogV2::model::LogsMetricCreateData;
use datadog_api_client::datadogV2::model::LogsMetricCreateRequest;
use datadog_api_client::datadogV2::model::LogsMetricType;

#[tokio::main]
async fn main() {
    let body = LogsMetricCreateRequest::new(LogsMetricCreateData::new(
        LogsMetricCreateAttributes::new(
            LogsMetricCompute::new(LogsMetricComputeAggregationType::DISTRIBUTION)
                .include_percentiles(true)
                .path("@duration".to_string()),
        ),
        "ExampleLogsMetric".to_string(),
        LogsMetricType::LOGS_METRICS,
    ));
    let configuration = datadog::Configuration::new();
    let api = LogsMetricsAPI::with_config(configuration);
    let resp = api.create_logs_metric(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}
```

#### Instructions

First [install the library and its dependencies](https://docs.datadoghq.com/api/latest.md?code-lang=rust) and then save the example to `src/main.rs` and run following commands:
    DD_SITE="datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run
##### 

```typescript
/**
 * Create a log-based metric returns "OK" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration();
const apiInstance = new v2.LogsMetricsApi(configuration);

const params: v2.LogsMetricsApiCreateLogsMetricRequest = {
  body: {
    data: {
      id: "ExampleLogsMetric",
      type: "logs_metrics",
      attributes: {
        compute: {
          aggregationType: "distribution",
          includePercentiles: true,
          path: "@duration",
        },
      },
    },
  },
};

apiInstance
  .createLogsMetric(params)
  .then((data: v2.LogsMetricResponse) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));
```

#### Instructions

First [install the library and its dependencies](https://docs.datadoghq.com/api/latest.md?code-lang=typescript) and then save the example to `example.ts` and run following commands:
    DD_SITE="datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" tsc "example.ts"
{% /tab %}