---
title: Crear una métrica basada en logs
description: Crea una métrica basada en los logs introducidos de tu organización.
breadcrumbs: Documentación > API > Crear una métrica basada en logs
---

> For the complete documentation index, see [llms.txt](https://dnd37xeb23o8n.cloudfront.net/jen.gilbert/astro-base/llms.txt).

# Crear una métrica basada en logs

## v2 (latest)

| Datadog site      | API endpoint                                                  |
| ----------------- | ------------------------------------------------------------- |
| 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 |
| app.datadoghq.eu  | POST https://api.datadoghq.eu/api/v2/logs/config/metrics      |
| 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 |
| uk1.datadoghq.com | POST https://api.uk1.datadoghq.com/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  |

### Overview

Crea una métrica basada en los logs introducidos de tu organización.
Devuelve el objeto de métrica basada en logs del cuerpo de la solicitud cuando dicha solicitud es satisfactoria.

This endpoint requires the `logs_generate_metrics` permission.

### Request

#### Body Data (required)

Definición de la nueva métrica basada en logs.

{% tabs %}
{% tab label="Model" %}
| Parent field | Field                         | Type     | Description                                                                                                                                |
| ------------ | ----------------------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
|              | data [*required*]             | object   | Cuerpo de la nueva métrica basada en logs.                                                                                                 |
| 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. Default: `*`.                                                                          |
| 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`. Default: `logs_metrics`.           |
{% /tab %}

{% tab label="Example" %}
```json
{
  "data": {
    "id": "ExampleLogsMetric",
    "type": "logs_metrics",
    "attributes": {
      "compute": {
        "aggregation_type": "distribution",
        "include_percentiles": true,
        "path": "@duration"
      }
    }
  }
}
```
{% /tab %}
{% /tabs %}

### Response

{% tabs %}
{% tab label="200" %}
OK

{% tabs %}
{% tab label="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`. Default: `logs_metrics`.           |
{% /tab %}

{% tab label="Example" %}
```json
{
  "data": {
    "attributes": {
      "compute": {
        "aggregation_type": "distribution",
        "include_percentiles": true,
        "path": "@duration"
      },
      "filter": {
        "query": "service:web-api 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 %}
{% /tabs %}
{% /tab %}

{% tab label="400" %}
Bad Request

{% tabs %}
{% tab label="Model" %}
API error response.

| Field               | Type     | Description       |
| ------------------- | -------- | ----------------- |
| errors [*required*] | [string] | A list of errors. |
{% /tab %}

{% tab label="Example" %}
```json
{
  "errors": [
    "Bad Request"
  ]
}
```
{% /tab %}
{% /tabs %}
{% /tab %}

{% tab label="403" %}
Not Authorized

{% tabs %}
{% tab label="Model" %}
API error response.

| Field               | Type     | Description       |
| ------------------- | -------- | ----------------- |
| errors [*required*] | [string] | A list of errors. |
{% /tab %}

{% tab label="Example" %}
```json
{
  "errors": [
    "Bad Request"
  ]
}
```
{% /tab %}
{% /tabs %}
{% /tab %}

{% tab label="409" %}
Conflict

{% tabs %}
{% tab label="Model" %}
API error response.

| Field               | Type     | Description       |
| ------------------- | -------- | ----------------- |
| errors [*required*] | [string] | A list of errors. |
{% /tab %}

{% tab label="Example" %}
```json
{
  "errors": [
    "Bad Request"
  ]
}
```
{% /tab %}
{% /tabs %}
{% /tab %}

{% tab label="429" %}
Too many requests

{% tabs %}
{% tab label="Model" %}
API error response.

| Field               | Type     | Description       |
| ------------------- | -------- | ----------------- |
| errors [*required*] | [string] | A list of errors. |
{% /tab %}

{% tab label="Example" %}
```json
{
  "errors": [
    "Bad Request"
  ]
}
```
{% /tab %}
{% /tabs %}
{% /tab %}
{% /tabs %}

### Code Example

{% tabs %}
{% tab label="Curl" %}
```bash
# Set your Datadog site and credentials
export DD_SITE="datadoghq.com" # Or us3.datadoghq.com, us5.datadoghq.com, datadoghq.eu, ap1.datadoghq.com, ap2.datadoghq.com, uk1.datadoghq.com, ddog-gov.com, us2.ddog-gov.com
# Use a Personal Access Token or Service Access Token
export DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>"

curl -X POST "https://api.${DD_SITE}/api/v2/logs/config/metrics" \
-H "Accept: application/json" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer ${DD_BEARER_TOKEN}" \
-d @- << EOF
{
  "data": {
    "id": "ExampleLogsMetric",
    "type": "logs_metrics",
    "attributes": {
      "compute": {
        "aggregation_type": "distribution",
        "include_percentiles": true,
        "path": "@duration"
      }
    }
  }
}
EOF
```
{% /tab %}

{% tab label="Go" %}
```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())
	ctx = context.WithValue(ctx, datadog.ContextAccessToken, os.Getenv("DD_BEARER_TOKEN"))
	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://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=go) and then save the example to `main.go` and run following commands:

```bash
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" go run "main.go"
```
{% /tab %}

{% tab label="Java" %}
```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();
    defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
    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://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=java) and then save the example to `Example.java` and run following commands:

```bash
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" java "Example.java"
```
{% /tab %}

{% tab label="Python" %}
```python
"""
Create a log-based metric returns "OK" response
"""

from os import environ
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()
configuration.access_token = environ["DD_BEARER_TOKEN"]
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://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=python) and then save the example to `example.py` and run following commands:

```bash
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" python3 "example.py"
```
{% /tab %}

{% tab label="Ruby" %}
```ruby
# Create a log-based metric returns "OK" response

require "datadog_api_client"
DatadogAPIClient.configure do |config|
  config.access_token = ENV["DD_BEARER_TOKEN"]
end
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://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=ruby) and then save the example to `example.rb` and run following commands:

```bash
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" rb "example.rb"
```
{% /tab %}

{% tab label="Rust" %}
```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://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=rust) and then save the example to `src/main.rs` and run following commands:

```bash
DD_SITE="datadoghq.com" DD_API_KEY="<API-KEY>" DD_APP_KEY="<APP-KEY>" cargo run
```
{% /tab %}

{% tab label="TypeScript" %}
```typescript
/**
 * Create a log-based metric returns "OK" response
 */

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

const configuration = client.createConfiguration({
  authMethods: {
    AuthZ: {
      accessToken: process.env.DD_BEARER_TOKEN as string,
    },
  },
});
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://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=typescript) and then save the example to `example.ts` and run following commands:

```bash
DD_SITE="datadoghq.com" DD_BEARER_TOKEN="<PERSONAL_ACCESS_TOKEN OR SERVICE_ACCESS_TOKEN>" tsc "example.ts"
```
{% /tab %}
{% /tabs %}