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api-clients-generation-pipeline[bot]ci.datadog-api-spec
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Add tags and description fields to the logs nested pipeline type LogsPipelineProcessor (#3742)
Co-authored-by: ci.datadog-api-spec <packages@datadoghq.com>
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‎.generator/schemas/v1/openapi.yaml‎

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@@ -6236,6 +6236,9 @@ components:
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A pipeline can contain Nested Pipelines and Processors whereas a Nested Pipeline can only contain Processors.
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properties:
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description:
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description: A description of the pipeline.
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type: string
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filter:
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$ref: "#/components/schemas/LogsFilter"
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is_enabled:
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items:
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$ref: "#/components/schemas/LogsProcessor"
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type: array
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tags:
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description: A list of tags associated with the pipeline.
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items:
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description: A single tag using the format `key:value`.
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type: string
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type: array
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type:
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$ref: "#/components/schemas/LogsPipelineProcessorType"
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required:

‎cassettes/v1/Logs-Pipelines_3794283453/Create-a-pipeline-with-nested-pipeline-processor-returns-OK-response_1904318129/frozen.json‎

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"2026-03-18T17:10:40.108Z"

‎cassettes/v1/Logs-Pipelines_3794283453/Create-a-pipeline-with-nested-pipeline-processor-returns-OK-response_1904318129/recording.har‎

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{
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"log": {
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"_recordingName": "Logs Pipelines/Create a pipeline with nested pipeline processor returns \"OK\" response",
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"creator": {
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"comment": "persister:fs",
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"name": "Polly.JS",
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"version": "6.0.5"
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},
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"entries": [
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{
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"_id": "43e467db3052c3f2f66c542643a0e3a7",
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"_order": 0,
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"cache": {},
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"request": {
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"bodySize": 392,
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"cookies": [],
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"headers": [
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{
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"_fromType": "array",
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"name": "accept",
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"value": "application/json"
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},
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{
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"_fromType": "array",
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"name": "content-type",
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"value": "application/json"
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}
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],
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"headersSize": 574,
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"httpVersion": "HTTP/1.1",
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"method": "POST",
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"postData": {
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"mimeType": "application/json",
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"params": [],
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"text": "{\"description\":\"Pipeline containing nested processor with tags and description\",\"filter\":{\"query\":\"source:python\"},\"name\":\"testPipelineWithNested\",\"processors\":[{\"description\":\"This is a nested pipeline for production logs\",\"filter\":{\"query\":\"env:production\"},\"is_enabled\":true,\"name\":\"nested_pipeline_with_metadata\",\"tags\":[\"env:prod\",\"type:nested\"],\"type\":\"pipeline\"}],\"tags\":[\"team:test\"]}"
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},
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"queryString": [],
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"url": "https://api.datadoghq.com/api/v1/logs/config/pipelines"
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},
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"response": {
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"bodySize": 497,
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"content": {
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"mimeType": "application/json",
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"size": 497,
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"text": "{\"id\":\"GyYNpCrVQtOB3KhqJSpOOA\",\"type\":\"pipeline\",\"name\":\"testPipelineWithNested\",\"is_enabled\":false,\"is_read_only\":false,\"filter\":{\"query\":\"source:python\"},\"processors\":[{\"type\":\"pipeline\",\"name\":\"nested_pipeline_with_metadata\",\"is_enabled\":true,\"filter\":{\"query\":\"env:production\"},\"processors\":[],\"tags\":[\"env:prod\",\"type:nested\"],\"description\":\"This is a nested pipeline for production logs\"}],\"tags\":[\"team:test\"],\"description\":\"Pipeline containing nested processor with tags and description\"}\n"
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},
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"cookies": [],
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"headers": [
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{
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"name": "content-type",
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"value": "application/json"
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}
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],
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"headersSize": 703,
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"httpVersion": "HTTP/1.1",
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"redirectURL": "",
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"status": 200,
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"statusText": "OK"
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},
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"startedDateTime": "2026-03-18T17:10:40.116Z",
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"time": 270
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},
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{
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"_id": "9d46b7bdff78f8c6c944e3cd37cf4ca4",
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"_order": 0,
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"cache": {},
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"request": {
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"bodySize": 0,
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"cookies": [],
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"headers": [
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{
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"_fromType": "array",
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"name": "accept",
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"value": "*/*"
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}
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],
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"headersSize": 533,
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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/v1/logs/config/pipelines/GyYNpCrVQtOB3KhqJSpOOA"
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},
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"response": {
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"bodySize": 3,
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"content": {
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"mimeType": "application/json",
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"size": 3,
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"text": "{}\n"
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},
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"cookies": [],
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"headers": [
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{
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"name": "content-type",
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"value": "application/json"
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}
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],
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"headersSize": 678,
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"httpVersion": "HTTP/1.1",
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"redirectURL": "",
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"status": 200,
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"statusText": "OK"
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},
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"startedDateTime": "2026-03-18T17:10:40.392Z",
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"time": 482
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}
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],
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"pages": [],
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"version": "1.2"
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}
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}

‎examples/v1/logs-pipelines/CreateLogsPipeline_2599033345.ts‎

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/**
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* Create a pipeline with nested pipeline processor returns "OK" response
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*/
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import { client, v1 } from "@datadog/datadog-api-client";
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const configuration = client.createConfiguration();
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const apiInstance = new v1.LogsPipelinesApi(configuration);
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const params: v1.LogsPipelinesApiCreateLogsPipelineRequest = {
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body: {
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filter: {
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query: "source:python",
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},
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name: "testPipelineWithNested",
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processors: [
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{
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type: "pipeline",
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isEnabled: true,
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name: "nested_pipeline_with_metadata",
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filter: {
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query: "env:production",
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},
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tags: ["env:prod", "type:nested"],
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description: "This is a nested pipeline for production logs",
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},
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],
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tags: ["team:test"],
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description:
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"Pipeline containing nested processor with tags and description",
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},
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};
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apiInstance
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.createLogsPipeline(params)
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.then((data: v1.LogsPipeline) => {
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console.log(
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"API called successfully. Returned data: " + JSON.stringify(data)
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);
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})
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.catch((error: any) => console.error(error));

‎features/v1/logs_pipelines.feature‎

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When the request is sent
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Then the response status is 200 OK
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@team:DataDog/event-platform-experience
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Scenario: Create a pipeline with nested pipeline processor returns "OK" response
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Given new "CreateLogsPipeline" request
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And body with value {"filter": {"query": "source:python"}, "name": "testPipelineWithNested", "processors": [{"type": "pipeline", "is_enabled": true, "name": "nested_pipeline_with_metadata", "filter": {"query": "env:production"}, "tags": ["env:prod", "type:nested"], "description": "This is a nested pipeline for production logs"}], "tags": ["team:test"], "description": "Pipeline containing nested processor with tags and description"}
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When the request is sent
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Then the response status is 200 OK
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@team:DataDog/event-platform-experience
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Scenario: Create a pipeline with schema processor
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Given new "CreateLogsPipeline" request

‎packages/datadog-api-client-v1/models/LogsPipelineProcessor.ts‎

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* A pipeline can contain Nested Pipelines and Processors whereas a Nested Pipeline can only contain Processors.
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*/
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export class LogsPipelineProcessor {
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/**
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* A description of the pipeline.
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*/
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"description"?: string;
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/**
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* Filter for logs.
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*/
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* Ordered list of processors in this pipeline.
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*/
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"processors"?: Array<LogsProcessor>;
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/**
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* A list of tags associated with the pipeline.
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*/
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"tags"?: Array<string>;
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/**
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* Type of logs pipeline processor.
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*/
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* @ignore
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*/
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static readonly attributeTypeMap: AttributeTypeMap = {
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description: {
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baseName: "description",
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type: "string",
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},
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filter: {
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baseName: "filter",
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type: "LogsFilter",
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baseName: "processors",
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type: "Array<LogsProcessor>",
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},
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tags: {
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baseName: "tags",
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type: "Array<string>",
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},
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type: {
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baseName: "type",
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type: "LogsPipelineProcessorType",

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