[ML] Re-enable sdk logging

sdk/ml/azure-ai-ml/README.md

@@ -94,9 +94,11 @@ See full SDK logging documentation with examples [here][sdk_logging_docs].
 
 ### Telemetry
 
-The Azure ML Python SDK includes a telemetry feature that collects usage and failure data about the SDK and sends it to Microsoft when you use the SDK.
+The Azure ML Python SDK includes a telemetry feature that collects usage and failure data about the SDK and sends it to Microsoft when you use the SDK in a Jupyter Notebook only.
+<u>Telemetry will **not** be collected for any use of the Python SDK outside of a Jupyter Notebook.</u>
+
 Telemetry data helps the SDK team understand how the SDK is used so it can be improved and the information about failures helps the team resolve problems and fix bugs.
-The SDK telemetry feature is enabled by default. To opt out of the telemetry feature, set the AZUREML_SDKV2_TELEMETRY_OPTOUT environment variable to 1 or true.
+The SDK telemetry feature is enabled by default for Jupyter Notebook usage. To opt out of the telemetry feature, set the AZUREML_SDKV2_TELEMETRY_OPTOUT environment variable to '1' or 'true'.
 
 ## Next steps
 

sdk/ml/azure-ai-ml/azure/ai/ml/_ml_client.py

@@ -31,6 +31,7 @@
 from azure.ai.ml._restclient.v2022_10_01_preview import AzureMachineLearningWorkspaces as ServiceClient102022Preview
 from azure.ai.ml._restclient.v2022_10_01 import AzureMachineLearningWorkspaces as ServiceClient102022
 from azure.ai.ml._scope_dependent_operations import OperationConfig, OperationsContainer, OperationScope
+from azure.ai.ml._telemetry.logging_handler import get_appinsights_log_handler
 from azure.ai.ml._user_agent import USER_AGENT
 from azure.ai.ml._utils._experimental import experimental
 from azure.ai.ml._utils._http_utils import HttpPipeline
@@ -215,12 +216,12 @@ def __init__(
         if registry_name:
             properties.update({"registry_name": registry_name})
 
-        # user_agent = None
-        # if "user_agent" in kwargs:
-        #     user_agent = kwargs.get("user_agent")
-        # app_insights_handler = get_appinsights_log_handler(user_agent, **{"properties": properties})
-        # app_insights_handler_kwargs = {"app_insights_handler": app_insights_handler}
-        app_insights_handler_kwargs = {}
+        user_agent = None
+        if "user_agent" in kwargs:
+            user_agent = kwargs.get("user_agent")
+
+        app_insights_handler = get_appinsights_log_handler(user_agent, **{"properties": properties})
+        app_insights_handler_kwargs = {"app_insights_handler": app_insights_handler}
 
         base_url = _get_base_url_from_metadata(cloud_name=cloud_name, is_local_mfe=True)
         self._base_url = base_url

sdk/ml/azure-ai-ml/azure/ai/ml/_telemetry/__init__.py

@@ -4,14 +4,14 @@
 
 __path__ = __import__("pkgutil").extend_path(__path__, __name__)
 
-# from .activity import ActivityType, log_activity, monitor_with_activity, monitor_with_telemetry_mixin
-# from .logging_handler import AML_INTERNAL_LOGGER_NAMESPACE, get_appinsights_log_handler
+from .activity import ActivityType, log_activity, monitor_with_activity, monitor_with_telemetry_mixin
+from .logging_handler import AML_INTERNAL_LOGGER_NAMESPACE, get_appinsights_log_handler
 
 __all__ = [
-    # "monitor_with_activity",
-    # "monitor_with_telemetry_mixin",
-    # "log_activity",
-    # "ActivityType",
-    # "get_appinsights_log_handler",
-    # "AML_INTERNAL_LOGGER_NAMESPACE",
+    "monitor_with_activity",
+    "monitor_with_telemetry_mixin",
+    "log_activity",
+    "ActivityType",
+    "get_appinsights_log_handler",
+    "AML_INTERNAL_LOGGER_NAMESPACE",
 ]

sdk/ml/azure-ai-ml/azure/ai/ml/_telemetry/activity.py

@@ -22,10 +22,10 @@
 
 from marshmallow import ValidationError
 
-from azure.ai.ml.exceptions import ErrorCategory, MlException
 from azure.core.exceptions import HttpResponseError
 
-from .._utils.utils import _is_user_error_from_exception_type, _is_user_error_from_status_code, _str_to_bool
+from azure.ai.ml._utils.utils import _is_user_error_from_exception_type, _is_user_error_from_status_code, _str_to_bool
+from azure.ai.ml.exceptions import ErrorCategory, MlException
 
 # Get environment variable IS_IN_CI_PIPELINE to decide whether it's in CI test
 IS_IN_CI_PIPELINE = _str_to_bool(os.environ.get("IS_IN_CI_PIPELINE", "False"))