Add a new end point that allows the SPA recommendation to be called without the shard parameter

.generator/schemas/v2/openapi.yaml

@@ -42828,6 +42828,9 @@ components:
       description: Attributes of the SPA Recommendation resource. Contains recommendations
         for both driver and executor components.
       properties:
+        confidence_level:
+          format: double
+          type: number
         driver:
           $ref: '#/components/schemas/ComponentRecommendation'
         executor:
@@ -86625,13 +86628,79 @@ paths:
       x-unstable: '**Note**: This feature is in private beta. To request access, use
         the request access form in the [Service Level Objectives](https://docs.datadoghq.com/service_management/service_level_objectives/#slo-csv-export)
         docs.'
-  /api/v2/spa/recommendations/{service}/{shard}:
+  /api/v2/spa/recommendations/{service}:
     get:
-      description: Retrieve resource recommendations for a Spark job. The caller (Spark
-        Gateway or DJM UI) provides a service name and shard identifier, and SPA returns
-        structured recommendations for driver and executor resources.
+      description: This endpoint is currently experimental and restricted to Datadog
+        internal use only. Retrieve resource recommendations for a Spark job. The
+        caller (Spark Gateway or DJM UI) provides a service name and SPA returns structured
+        recommendations for driver and executor resources. The version with a shard
+        should be preferred, where possible, as it gives more accurate results.
       operationId: GetSPARecommendations
       parameters:
+      - description: The recommendation service should not use its metrics cache.
+        in: query
+        name: bypass_cache
+        schema:
+          type: string
+      - description: The service name for a spark job.
+        in: path
+        name: service
+        required: true
+        schema:
+          type: string
+      responses:
+        '200':
+          content:
+            application/json:
+              example:
+                data:
+                  attributes:
+                    driver:
+                      estimation:
+                        cpu:
+                          max: 1500
+                          p75: 1000
+                          p95: 1200
+                        ephemeral_storage: 896
+                        heap: 6144
+                        memory: 7168
+                        overhead: 1024
+                    executor:
+                      estimation:
+                        cpu:
+                          max: 2000
+                          p75: 1200
+                          p95: 1500
+                        ephemeral_storage: 512
+                        heap: 3072
+                        memory: 4096
+                        overhead: 1024
+                  id: dedupeactivecontexts:adp_dedupeactivecontexts_org2
+                  type: recommendation
+              schema:
+                $ref: '#/components/schemas/RecommendationDocument'
+          description: OK
+        '400':
+          $ref: '#/components/responses/BadRequestResponse'
+        '403':
+          $ref: '#/components/responses/NotAuthorizedResponse'
+        '429':
+          $ref: '#/components/responses/TooManyRequestsResponse'
+      security:
+      - AuthZ: []
+      summary: Get SPA Recommendations
+      tags:
+      - Spa
+      x-unstable: '**Note**: This endpoint is in preview and may change in the future.
+        It is not yet recommended for production use.'
+  /api/v2/spa/recommendations/{service}/{shard}:
+    get:
+      description: This endpoint is currently experimental and restricted to Datadog
+        internal use only. Retrieve resource recommendations for a Spark job. The
+        caller (Spark Gateway or DJM UI) provides a service name and shard identifier,
+        and SPA returns structured recommendations for driver and executor resources.
+      operationId: GetSPARecommendationsWithShard
+      parameters:
       - description: The shard tag for a spark job, which differentiates jobs within
           the same service that have different resource needs
         in: path
@@ -86645,6 +86714,11 @@ paths:
         required: true
         schema:
           type: string
+      - description: The recommendation service should not use its metrics cache.
+        in: query
+        name: bypass_cache
+        schema:
+          type: string
       responses:
         '200':
           content:
@@ -86683,11 +86757,13 @@ paths:
           $ref: '#/components/responses/NotAuthorizedResponse'
         '429':
           $ref: '#/components/responses/TooManyRequestsResponse'
-      summary: Get SPA Recommendations
+      security:
+      - AuthZ: []
+      summary: Get SPA Recommendations with a shard parameter
       tags:
       - Spa
-      x-unstable: '**Note**: This endpoint is in public beta and may change in the
-        future. It is not yet recommended for production use.'
+      x-unstable: '**Note**: This endpoint is in preview and may change in the future.
+        It is not yet recommended for production use.'
   /api/v2/spans/analytics/aggregate:
     post:
       description: 'The API endpoint to aggregate spans into buckets and compute metrics

examples/v2/spa/GetSPARecommendations.py

@@ -10,7 +10,6 @@
 with ApiClient(configuration) as api_client:
     api_instance = SpaApi(api_client)
     response = api_instance.get_spa_recommendations(
-        shard="shard",
         service="service",
     )
 

examples/v2/spa/GetSPARecommendationsWithShard.py

@@ -0,0 +1,17 @@
+"""
+Get SPA Recommendations with a shard parameter returns "OK" response
+"""
+
+from datadog_api_client import ApiClient, Configuration
+from datadog_api_client.v2.api.spa_api import SpaApi
+
+configuration = Configuration()
+configuration.unstable_operations["get_spa_recommendations_with_shard"] = True
+with ApiClient(configuration) as api_client:
+    api_instance = SpaApi(api_client)
+    response = api_instance.get_spa_recommendations_with_shard(
+        shard="shard",
+        service="service",
+    )
+
+    print(response)

src/datadog_api_client/configuration.py

@@ -392,6 +392,7 @@ def __init__(
                 "v2.get_slo_report": False,
                 "v2.get_slo_report_job_status": False,
                 "v2.get_spa_recommendations": False,
+                "v2.get_spa_recommendations_with_shard": False,
                 "v2.create_sca_resolve_vulnerable_symbols": False,
                 "v2.create_sca_result": False,
                 "v2.add_member_team": False,

src/datadog_api_client/v2/api/spa_api.py

@@ -3,10 +3,14 @@
 # Copyright 2019-Present Datadog, Inc.
 from __future__ import annotations
 
-from typing import Any, Dict
+from typing import Any, Dict, Union
 
 from datadog_api_client.api_client import ApiClient, Endpoint as _Endpoint
 from datadog_api_client.configuration import Configuration
+from datadog_api_client.model_utils import (
+    UnsetType,
+    unset,
+)
 from datadog_api_client.v2.model.recommendation_document import RecommendationDocument
 
 
@@ -23,12 +27,40 @@ def __init__(self, api_client=None):
         self._get_spa_recommendations_endpoint = _Endpoint(
             settings={
                 "response_type": (RecommendationDocument,),
-                "auth": ["apiKeyAuth", "appKeyAuth"],
-                "endpoint_path": "/api/v2/spa/recommendations/{service}/{shard}",
+                "auth": ["AuthZ"],
+                "endpoint_path": "/api/v2/spa/recommendations/{service}",
                 "operation_id": "get_spa_recommendations",
                 "http_method": "GET",
                 "version": "v2",
             },
+            params_map={
+                "bypass_cache": {
+                    "openapi_types": (str,),
+                    "attribute": "bypass_cache",
+                    "location": "query",
+                },
+                "service": {
+                    "required": True,
+                    "openapi_types": (str,),
+                    "attribute": "service",
+                    "location": "path",
+                },
+            },
+            headers_map={
+                "accept": ["application/json"],
+            },
+            api_client=api_client,
+        )
+
+        self._get_spa_recommendations_with_shard_endpoint = _Endpoint(
+            settings={
+                "response_type": (RecommendationDocument,),
+                "auth": ["AuthZ"],
+                "endpoint_path": "/api/v2/spa/recommendations/{service}/{shard}",
+                "operation_id": "get_spa_recommendations_with_shard",
+                "http_method": "GET",
+                "version": "v2",
+            },
             params_map={
                 "shard": {
                     "required": True,
@@ -42,6 +74,11 @@ def __init__(self, api_client=None):
                     "attribute": "service",
                     "location": "path",
                 },
+                "bypass_cache": {
+                    "openapi_types": (str,),
+                    "attribute": "bypass_cache",
+                    "location": "query",
+                },
             },
             headers_map={
                 "accept": ["application/json"],
@@ -51,22 +88,53 @@ def __init__(self, api_client=None):
 
     def get_spa_recommendations(
         self,
-        shard: str,
         service: str,
+        *,
+        bypass_cache: Union[str, UnsetType] = unset,
     ) -> RecommendationDocument:
         """Get SPA Recommendations.
 
-        Retrieve resource recommendations for a Spark job. The caller (Spark Gateway or DJM UI) provides a service name and shard identifier, and SPA returns structured recommendations for driver and executor resources.
+        This endpoint is currently experimental and restricted to Datadog internal use only. Retrieve resource recommendations for a Spark job. The caller (Spark Gateway or DJM UI) provides a service name and SPA returns structured recommendations for driver and executor resources. The version with a shard should be preferred, where possible, as it gives more accurate results.
+
+        :param service: The service name for a spark job.
+        :type service: str
+        :param bypass_cache: The recommendation service should not use its metrics cache.
+        :type bypass_cache: str, optional
+        :rtype: RecommendationDocument
+        """
+        kwargs: Dict[str, Any] = {}
+        if bypass_cache is not unset:
+            kwargs["bypass_cache"] = bypass_cache
+
+        kwargs["service"] = service
+
+        return self._get_spa_recommendations_endpoint.call_with_http_info(**kwargs)
+
+    def get_spa_recommendations_with_shard(
+        self,
+        shard: str,
+        service: str,
+        *,
+        bypass_cache: Union[str, UnsetType] = unset,
+    ) -> RecommendationDocument:
+        """Get SPA Recommendations with a shard parameter.
+
+        This endpoint is currently experimental and restricted to Datadog internal use only. Retrieve resource recommendations for a Spark job. The caller (Spark Gateway or DJM UI) provides a service name and shard identifier, and SPA returns structured recommendations for driver and executor resources.
 
         :param shard: The shard tag for a spark job, which differentiates jobs within the same service that have different resource needs
         :type shard: str
         :param service: The service name for a spark job
         :type service: str
+        :param bypass_cache: The recommendation service should not use its metrics cache.
+        :type bypass_cache: str, optional
         :rtype: RecommendationDocument
         """
         kwargs: Dict[str, Any] = {}
         kwargs["shard"] = shard
 
         kwargs["service"] = service
 
-        return self._get_spa_recommendations_endpoint.call_with_http_info(**kwargs)
+        if bypass_cache is not unset:
+            kwargs["bypass_cache"] = bypass_cache
+
+        return self._get_spa_recommendations_with_shard_endpoint.call_with_http_info(**kwargs)

src/datadog_api_client/v2/model/recommendation_attributes.py

@@ -3,11 +3,13 @@
 # Copyright 2019-Present Datadog, Inc.
 from __future__ import annotations
 
-from typing import TYPE_CHECKING
+from typing import Union, TYPE_CHECKING
 
 from datadog_api_client.model_utils import (
     ModelNormal,
     cached_property,
+    unset,
+    UnsetType,
 )
 
 
@@ -21,25 +23,38 @@ def openapi_types(_):
         from datadog_api_client.v2.model.component_recommendation import ComponentRecommendation
 
         return {
+            "confidence_level": (float,),
             "driver": (ComponentRecommendation,),
             "executor": (ComponentRecommendation,),
         }
 
     attribute_map = {
+        "confidence_level": "confidence_level",
         "driver": "driver",
         "executor": "executor",
     }
 
-    def __init__(self_, driver: ComponentRecommendation, executor: ComponentRecommendation, **kwargs):
+    def __init__(
+        self_,
+        driver: ComponentRecommendation,
+        executor: ComponentRecommendation,
+        confidence_level: Union[float, UnsetType] = unset,
+        **kwargs,
+    ):
         """
         Attributes of the SPA Recommendation resource. Contains recommendations for both driver and executor components.
 
+        :param confidence_level:
+        :type confidence_level: float, optional
+
         :param driver: Resource recommendation for a single Spark component (driver or executor). Contains estimation data used to patch Spark job specs.
         :type driver: ComponentRecommendation
 
         :param executor: Resource recommendation for a single Spark component (driver or executor). Contains estimation data used to patch Spark job specs.
         :type executor: ComponentRecommendation
         """
+        if confidence_level is not unset:
+            kwargs["confidence_level"] = confidence_level
         super().__init__(kwargs)
 
         self_.driver = driver

tests/v2/features/spa.feature

@@ -4,29 +4,49 @@ Feature: Spa
   insights to help optimize Spark job configurations.
 
   Background:
-    Given a valid "apiKeyAuth" key in the system
-    And a valid "appKeyAuth" key in the system
-    And an instance of "Spa" API
-    And operation "GetSPARecommendations" enabled
-    And new "GetSPARecommendations" request
+    Given an instance of "Spa" API
 
   @generated @skip @team:DataDog/data-and-analytics-processing
   Scenario: Get SPA Recommendations returns "Bad Request" response
-    Given request contains "shard" parameter from "REPLACE.ME"
+    Given operation "GetSPARecommendations" enabled
+    And new "GetSPARecommendations" request
     And request contains "service" parameter from "REPLACE.ME"
     When the request is sent
     Then the response status is 400 Bad Request
 
   @generated @skip @team:DataDog/data-and-analytics-processing
   Scenario: Get SPA Recommendations returns "OK" response
-    Given request contains "shard" parameter from "REPLACE.ME"
+    Given operation "GetSPARecommendations" enabled
+    And new "GetSPARecommendations" request
+    And request contains "service" parameter from "REPLACE.ME"
+    When the request is sent
+    Then the response status is 200 OK
+
+  @generated @skip @team:DataDog/data-and-analytics-processing
+  Scenario: Get SPA Recommendations with a shard parameter returns "Bad Request" response
+    Given operation "GetSPARecommendationsWithShard" enabled
+    And new "GetSPARecommendationsWithShard" request
+    And request contains "shard" parameter from "REPLACE.ME"
+    And request contains "service" parameter from "REPLACE.ME"
+    When the request is sent
+    Then the response status is 400 Bad Request
+
+  @generated @skip @team:DataDog/data-and-analytics-processing
+  Scenario: Get SPA Recommendations with a shard parameter returns "OK" response
+    Given operation "GetSPARecommendationsWithShard" enabled
+    And new "GetSPARecommendationsWithShard" request
+    And request contains "shard" parameter from "REPLACE.ME"
     And request contains "service" parameter from "REPLACE.ME"
     When the request is sent
     Then the response status is 200 OK
 
   @skip @team:DataDog/data-and-analytics-processing
   Scenario: GetSPARecommendations returns a JSON:API Recommendation with driver and executor estimations
-    Given request contains "service" parameter with value "dedupeactivecontexts"
+    Given new "GetSPARecommendations" request
+    And a valid "apiKeyAuth" key in the system
+    And a valid "appKeyAuth" key in the system
+    And operation "GetSPARecommendations" enabled
+    And request contains "service" parameter with value "dedupeactivecontexts"
     And request contains "shard" parameter with value "adp_dedupeactivecontexts_org2"
     When the request is sent
     Then the response status is 404 Not Found