Regenerate client from commit 7affb98 of spec repo

Author: ci.datadog-api-spec

.generator/schemas/v1/openapi.yaml

@@ -6683,6 +6683,9 @@ components:
         A pipeline can contain Nested Pipelines and Processors whereas a Nested Pipeline
         can only contain Processors.'
       properties:
+        description:
+          description: A description of the pipeline.
+          type: string
         filter:
           $ref: '#/components/schemas/LogsFilter'
         is_enabled:
@@ -6697,6 +6700,12 @@ components:
           items:
             $ref: '#/components/schemas/LogsProcessor'
           type: array
+        tags:
+          description: A list of tags associated with the pipeline.
+          items:
+            description: A single tag using the format `key:value`.
+            type: string
+          type: array
         type:
           $ref: '#/components/schemas/LogsPipelineProcessorType'
       required:

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

@@ -0,0 +1 @@
+"2026-03-18T17:10:40.108Z"

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

@@ -0,0 +1,110 @@
+{
+  "log": {
+    "_recordingName": "Logs Pipelines/Create a pipeline with nested pipeline processor returns \"OK\" response",
+    "creator": {
+      "comment": "persister:fs",
+      "name": "Polly.JS",
+      "version": "6.0.5"
+    },
+    "entries": [
+      {
+        "_id": "43e467db3052c3f2f66c542643a0e3a7",
+        "_order": 0,
+        "cache": {},
+        "request": {
+          "bodySize": 392,
+          "cookies": [],
+          "headers": [
+            {
+              "_fromType": "array",
+              "name": "accept",
+              "value": "application/json"
+            },
+            {
+              "_fromType": "array",
+              "name": "content-type",
+              "value": "application/json"
+            }
+          ],
+          "headersSize": 574,
+          "httpVersion": "HTTP/1.1",
+          "method": "POST",
+          "postData": {
+            "mimeType": "application/json",
+            "params": [],
+            "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\"]}"
+          },
+          "queryString": [],
+          "url": "https://api.datadoghq.com/api/v1/logs/config/pipelines"
+        },
+        "response": {
+          "bodySize": 497,
+          "content": {
+            "mimeType": "application/json",
+            "size": 497,
+            "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"
+          },
+          "cookies": [],
+          "headers": [
+            {
+              "name": "content-type",
+              "value": "application/json"
+            }
+          ],
+          "headersSize": 703,
+          "httpVersion": "HTTP/1.1",
+          "redirectURL": "",
+          "status": 200,
+          "statusText": "OK"
+        },
+        "startedDateTime": "2026-03-18T17:10:40.116Z",
+        "time": 270
+      },
+      {
+        "_id": "9d46b7bdff78f8c6c944e3cd37cf4ca4",
+        "_order": 0,
+        "cache": {},
+        "request": {
+          "bodySize": 0,
+          "cookies": [],
+          "headers": [
+            {
+              "_fromType": "array",
+              "name": "accept",
+              "value": "*/*"
+            }
+          ],
+          "headersSize": 533,
+          "httpVersion": "HTTP/1.1",
+          "method": "DELETE",
+          "queryString": [],
+          "url": "https://api.datadoghq.com/api/v1/logs/config/pipelines/GyYNpCrVQtOB3KhqJSpOOA"
+        },
+        "response": {
+          "bodySize": 3,
+          "content": {
+            "mimeType": "application/json",
+            "size": 3,
+            "text": "{}\n"
+          },
+          "cookies": [],
+          "headers": [
+            {
+              "name": "content-type",
+              "value": "application/json"
+            }
+          ],
+          "headersSize": 678,
+          "httpVersion": "HTTP/1.1",
+          "redirectURL": "",
+          "status": 200,
+          "statusText": "OK"
+        },
+        "startedDateTime": "2026-03-18T17:10:40.392Z",
+        "time": 482
+      }
+    ],
+    "pages": [],
+    "version": "1.2"
+  }
+}

features/v1/logs_pipelines.feature

@@ -98,6 +98,13 @@ Feature: Logs Pipelines
     When the request is sent
     Then the response status is 200 OK
 
+  @team:DataDog/event-platform-experience
+  Scenario: Create a pipeline with nested pipeline processor returns "OK" response
+    Given new "CreateLogsPipeline" request
+    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"}
+    When the request is sent
+    Then the response status is 200 OK
+
   @team:DataDog/event-platform-experience
   Scenario: Create a pipeline with schema processor
     Given new "CreateLogsPipeline" request

services/logs_pipelines/src/v1/models/LogsPipelineProcessor.ts

@@ -12,6 +12,10 @@ import { LogsProcessor } from "./LogsProcessor";
  * A pipeline can contain Nested Pipelines and Processors whereas a Nested Pipeline can only contain Processors.
  */
 export class LogsPipelineProcessor {
+  /**
+   * A description of the pipeline.
+   */
+  "description"?: string;
   /**
    * Filter for logs.
    */
@@ -28,6 +32,10 @@ export class LogsPipelineProcessor {
    * Ordered list of processors in this pipeline.
    */
   "processors"?: Array<LogsProcessor>;
+  /**
+   * A list of tags associated with the pipeline.
+   */
+  "tags"?: Array<string>;
   /**
    * Type of logs pipeline processor.
    */
@@ -47,6 +55,10 @@ export class LogsPipelineProcessor {
    * @ignore
    */
   static readonly attributeTypeMap: AttributeTypeMap = {
+    description: {
+      baseName: "description",
+      type: "string",
+    },
     filter: {
       baseName: "filter",
       type: "LogsFilter",
@@ -63,6 +75,10 @@ export class LogsPipelineProcessor {
       baseName: "processors",
       type: "Array<LogsProcessor>",
     },
+    tags: {
+      baseName: "tags",
+      type: "Array<string>",
+    },
     type: {
       baseName: "type",
       type: "LogsPipelineProcessorType",