fix(tests): Replace deprecated ml.t2.medium in integ fixtures (#6284)

SageMaker hosting rejects the T2 family on CreateEndpointConfig
('Deprecated instance type "T2"'), which makes
test_multi_data_model_deploy_pretrained_models_update_endpoint fail
deterministically on every master-v2 integ run.

The alternative_cpu_instance_type fixture now returns ml.c5.xlarge in
all regions (the value it already used for NO_T2_REGIONS), and the
lineage static-endpoint helper deploys on ml.m5.xlarge. Both still
differ from cpu_instance_type, which is what the update-endpoint
assertion relies on.

---
X-AI-Prompt: fix pre-existing V2 integ failure caused by deprecated ml.t2 instance type
X-AI-Tool: Kiro

Author: jam-jee

tests/conftest.py

@@ -58,8 +58,6 @@
     "ap-south-1",  # no p3 availability
 ]
 
-NO_T2_REGIONS = ["eu-north-1", "ap-east-1", "me-south-1"]
-
 FRAMEWORKS_FOR_GENERATED_VERSION_FIXTURES = (
     "chainer",
     "coach_mxnet",
@@ -666,12 +664,11 @@ def ec2_instance_type(cpu_instance_type):
 
 @pytest.fixture(scope="session")
 def alternative_cpu_instance_type(sagemaker_session, request):
-    region = sagemaker_session.boto_session.region_name
-    if region in NO_T2_REGIONS:
-        # T3 is not supported by hosting yet
-        return "ml.c5.xlarge"
-    else:
-        return "ml.t2.medium"
+    # SageMaker hosting no longer accepts the T2 family (CreateEndpointConfig
+    # rejects it with 'Deprecated instance type "T2"'). ml.c5.xlarge is
+    # available in every region and differs from cpu_instance_type, which is
+    # all the update-endpoint tests need.
+    return "ml.c5.xlarge"
 
 
 @pytest.fixture(scope="session")

tests/integ/sagemaker/lineage/conftest.py

@@ -885,7 +885,7 @@ def _deploy_static_endpoint(execution_arn, sagemaker_session):
             model_package_arn=model_package_arn,
             sagemaker_session=sagemaker_session,
         )
-        model_package.deploy(1, "ml.t2.medium", endpoint_name=STATIC_ENDPOINT_NAME)
+        model_package.deploy(1, "ml.m5.xlarge", endpoint_name=STATIC_ENDPOINT_NAME)
         time.sleep(120)
     except ClientError as e:
         if e.response["Error"]["Code"] == "ValidationException":