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Add include_percentiles field in Logs Custom Metrics (#896)
Co-authored-by: ci.datadog-api-spec <[email protected]> Co-authored-by: api-clients-generation-pipeline[bot] <54105614+api-clients-generation-pipeline[bot]@users.noreply.github.com>
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-30
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17 files changed

+344
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‎.apigentools-info

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@@ -4,13 +4,13 @@
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"spec_versions": {
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"v1": {
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"apigentools_version": "1.6.4",
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"regenerated": "2022-11-21 18:48:14.323887",
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"spec_repo_commit": "9015efdd"
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"regenerated": "2022-11-21 20:01:55.034154",
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"spec_repo_commit": "4ca2c235"
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},
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"v2": {
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"apigentools_version": "1.6.4",
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"regenerated": "2022-11-21 18:48:14.335707",
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"spec_repo_commit": "9015efdd"
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"regenerated": "2022-11-21 20:01:55.048203",
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"spec_repo_commit": "4ca2c235"
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}
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}
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}

‎.generator/schemas/v2/openapi.yaml

Lines changed: 20 additions & 1 deletion
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@@ -5012,6 +5012,8 @@ components:
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properties:
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aggregation_type:
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$ref: '#/components/schemas/LogsMetricComputeAggregationType'
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include_percentiles:
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$ref: '#/components/schemas/LogsMetricComputeIncludePercentiles'
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path:
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description: The path to the value the log-based metric will aggregate on
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(only used if the aggregation type is a "distribution").
@@ -5030,6 +5032,13 @@ components:
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x-enum-varnames:
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- COUNT
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- DISTRIBUTION
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LogsMetricComputeIncludePercentiles:
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description: 'Toggle to include or exclude percentile aggregations for distribution
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metrics.
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Only present when the `aggregation_type` is `distribution`.'
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example: true
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type: boolean
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LogsMetricCreateAttributes:
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description: The object describing the Datadog log-based metric to create.
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properties:
@@ -5121,6 +5130,8 @@ components:
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properties:
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aggregation_type:
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$ref: '#/components/schemas/LogsMetricResponseComputeAggregationType'
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include_percentiles:
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$ref: '#/components/schemas/LogsMetricComputeIncludePercentiles'
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path:
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description: The path to the value the log-based metric will aggregate on
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(only used if the aggregation type is a "distribution").
@@ -5182,6 +5193,8 @@ components:
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LogsMetricUpdateAttributes:
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description: The log-based metric properties that will be updated.
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properties:
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compute:
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$ref: '#/components/schemas/LogsMetricUpdateCompute'
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filter:
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$ref: '#/components/schemas/LogsMetricFilter'
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group_by:
@@ -5190,6 +5203,12 @@ components:
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$ref: '#/components/schemas/LogsMetricGroupBy'
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type: array
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type: object
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LogsMetricUpdateCompute:
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description: The compute rule to compute the log-based metric.
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properties:
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include_percentiles:
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$ref: '#/components/schemas/LogsMetricComputeIncludePercentiles'
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type: object
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LogsMetricUpdateData:
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description: The new log-based metric properties.
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properties:
@@ -5978,7 +5997,7 @@ components:
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format: date-time
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type: string
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include_percentiles:
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description: 'Toggle to turn on/off percentile aggregations for distribution
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description: 'Toggle to include or exclude percentile aggregations for distribution
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metrics.
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Only present when the `metric_type` is `distribution`.'

‎cassettes/v2/Logs-Metrics_3185148095/Create-a-log-based-metric-returns-OK-response_2853166544/frozen.json

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"2022-11-21T15:36:05.545Z"

‎cassettes/v2/Logs-Metrics_3185148095/Create-a-log-based-metric-returns-OK-response_2853166544/recording.har

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@@ -8,11 +8,11 @@
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@@ -32,17 +32,17 @@
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"postData": {
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"mimeType": "application/json",
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"params": [],
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"text": "{\"data\":{\"attributes\":{\"compute\":{\"aggregation_type\":\"count\"}},\"id\":\"Test-Create_a_log_based_metric_returns_OK_response-1652349142\",\"type\":\"logs_metrics\"}}"
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"text": "{\"data\":{\"attributes\":{\"compute\":{\"aggregation_type\":\"distribution\",\"include_percentiles\":true,\"path\":\"@duration\"}},\"id\":\"Test-Create_a_log_based_metric_returns_OK_response-1669044965\",\"type\":\"logs_metrics\"}}"
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},
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"queryString": [],
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"url": "https://api.datadoghq.com/api/v2/logs/config/metrics"
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},
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"response": {
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"bodySize": 192,
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"content": {
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"mimeType": "application/json",
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"size": 192,
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"text": "{\"data\":{\"attributes\":{\"filter\":{\"query\":\"*\"},\"group_by\":[],\"compute\":{\"aggregation_type\":\"count\"}},\"type\":\"logs_metrics\",\"id\":\"Test_Create_a_log_based_metric_returns_OK_response_1652349142\"}}"
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"text": "{\"data\":{\"attributes\":{\"filter\":{\"query\":\"*\"},\"group_by\":[],\"compute\":{\"path\":\"@duration\",\"include_percentiles\":true,\"aggregation_type\":\"distribution\"}},\"type\":\"logs_metrics\",\"id\":\"Test_Create_a_log_based_metric_returns_OK_response_1669044965\"}}\n"
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@@ -51,17 +51,17 @@
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"httpVersion": "HTTP/1.1",
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"request": {
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"httpVersion": "HTTP/1.1",
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"method": "DELETE",
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"queryString": [],
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"url": "https://api.datadoghq.com/api/v2/logs/config/metrics/Test_Create_a_log_based_metric_returns_OK_response_1652349142"
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"url": "https://api.datadoghq.com/api/v2/logs/config/metrics/Test_Create_a_log_based_metric_returns_OK_response_1669044965"
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‎cassettes/v2/Logs-Metrics_3185148095/Update-a-log-based-metric-with-include_percentiles-field-returns-OK-response_1255547678/frozen.json

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"2022-11-21T19:49:25.214Z"

‎cassettes/v2/Logs-Metrics_3185148095/Update-a-log-based-metric-with-include_percentiles-field-returns-OK-response_1255547678/recording.har

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"log": {
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"_recordingName": "Logs Metrics/Update a log-based metric with include_percentiles field returns \"OK\" response",
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"url": "https://api.datadoghq.com/api/v2/logs/config/metrics"
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"url": "https://api.datadoghq.com/api/v2/logs/config/metrics/Test_Update_a_log_based_metric_with_include_percentiles_field_returns_OK_response_1669060165"
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‎examples/v2/logs-metrics/CreateLogsMetric.ts

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Original file line numberDiff line numberDiff line change
@@ -14,7 +14,9 @@ const params: v2.LogsMetricsApiCreateLogsMetricRequest = {
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type: "logs_metrics",
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attributes: {
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compute: {
17-
aggregationType: "count",
17+
aggregationType: "distribution",
18+
includePercentiles: true,
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path: "@duration",
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},
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},
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},

‎examples/v2/logs-metrics/UpdateLogsMetric_1901534424.ts

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/**
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* Update a log-based metric with include_percentiles field returns "OK" response
3+
*/
4+
5+
import { client, v2 } from "@datadog/datadog-api-client";
6+
7+
const configuration = client.createConfiguration();
8+
const apiInstance = new v2.LogsMetricsApi(configuration);
9+
10+
// there is a valid "logs_metric_percentile" in the system
11+
const LOGS_METRIC_PERCENTILE_DATA_ID = process.env
12+
.LOGS_METRIC_PERCENTILE_DATA_ID as string;
13+
14+
const params: v2.LogsMetricsApiUpdateLogsMetricRequest = {
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body: {
16+
data: {
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type: "logs_metrics",
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attributes: {
19+
compute: {
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includePercentiles: false,
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},
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},
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},
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},
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metricId: LOGS_METRIC_PERCENTILE_DATA_ID,
26+
};
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apiInstance
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.updateLogsMetric(params)
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.then((data: v2.LogsMetricResponse) => {
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console.log(
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"API called successfully. Returned data: " + JSON.stringify(data)
33+
);
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})
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.catch((error: any) => console.error(error));

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