diff --git a/sagemaker-serve/src/sagemaker/serve/bedrock_model_builder.py b/sagemaker-serve/src/sagemaker/serve/bedrock_model_builder.py
index dfa1ebbfc4..de5a158c9f 100644
--- a/sagemaker-serve/src/sagemaker/serve/bedrock_model_builder.py
+++ b/sagemaker-serve/src/sagemaker/serve/bedrock_model_builder.py
@@ -258,7 +258,9 @@ def _is_nova_model_for_telemetry(self) -> bool:
         func_name="BedrockModelBuilder.deploy",
         telemetry_params=[
             ("model_package", TelemetryParamType.ATTR_EXISTS),
+            ("_is_nova_model_for_telemetry", TelemetryParamType.ATTR_CALL),
             ("imported_model_kms_key_id", TelemetryParamType.KWARG_EXISTS),
+            ("reuse_resources", TelemetryParamType.KWARG_EXISTS),
         ],
     )
     def deploy(
diff --git a/sagemaker-serve/src/sagemaker/serve/model_builder.py b/sagemaker-serve/src/sagemaker/serve/model_builder.py
index 1973706a67..05df51fb93 100644
--- a/sagemaker-serve/src/sagemaker/serve/model_builder.py
+++ b/sagemaker-serve/src/sagemaker/serve/model_builder.py
@@ -3948,9 +3948,11 @@ def _reset_build_state(self):
         func_name="model_builder.build",
         telemetry_params=[
             ("mode", TelemetryParamType.ATTR_VALUE),
+            ("_is_nova_model_for_telemetry", TelemetryParamType.ATTR_CALL),
             ("network", TelemetryParamType.ATTR_EXISTS),
             ("source_code", TelemetryParamType.ATTR_EXISTS),
             ("inference_spec", TelemetryParamType.ATTR_EXISTS),
+            ("reuse_resources", TelemetryParamType.KWARG_EXISTS),
         ],
     )
     @runnable_by_pipeline
@@ -5326,9 +5328,11 @@ def _deploy_recommendation(
             ("mode", TelemetryParamType.ATTR_VALUE),
             ("instance_type", TelemetryParamType.ATTR_VALUE),
             ("_is_model_customization", TelemetryParamType.ATTR_CALL),
+            ("_is_nova_model_for_telemetry", TelemetryParamType.ATTR_CALL),
             ("network", TelemetryParamType.ATTR_EXISTS),
             ("compute", TelemetryParamType.ATTR_EXISTS),
             ("update_endpoint", TelemetryParamType.KWARG_EXISTS),
+            ("reuse_resources", TelemetryParamType.KWARG_EXISTS),
         ],
     )
     def deploy(
diff --git a/sagemaker-train/src/sagemaker/train/base_trainer.py b/sagemaker-train/src/sagemaker/train/base_trainer.py
index 10ec7c6a27..9af37e9e91 100644
--- a/sagemaker-train/src/sagemaker/train/base_trainer.py
+++ b/sagemaker-train/src/sagemaker/train/base_trainer.py
@@ -41,6 +41,8 @@
 from sagemaker.train.common_utils.notifications import enable_notifications, delete_notification_rule, list_notification_rules
 from sagemaker.train.common_utils.validator import validate_hyperpod_compute
 from sagemaker.train.common_utils.cloudwatch_metrics import fetch_and_plot_metrics, _get_smhp_log_group
+from sagemaker.core.telemetry.telemetry_logging import _telemetry_emitter, TelemetryParamType
+from sagemaker.core.telemetry.constants import Feature
 from sagemaker.train.defaults import TrainDefaults
 from sagemaker.train.model_trainer import ModelTrainer
 from sagemaker.train.utils import _get_unique_name
@@ -365,6 +367,13 @@ def _apply_recipe_to_hyperparameters(
 
         return final_hyperparameters
 
+    @_telemetry_emitter(
+        feature=Feature.MODEL_CUSTOMIZATION,
+        func_name="BaseTrainer.show_metrics",
+        telemetry_params=[
+            ("compute", TelemetryParamType.ATTR_TYPE),
+        ],
+    )
     def show_metrics(
         self,
         metrics: Optional[List[str]] = None,
@@ -627,6 +636,13 @@ def list_notification_rules(
             event_bus_arn=event_bus_arn,
         )
 
+    @_telemetry_emitter(
+        feature=Feature.MODEL_CUSTOMIZATION,
+        func_name="BaseTrainer.stream_logs",
+        telemetry_params=[
+            ("compute", TelemetryParamType.ATTR_TYPE),
+        ],
+    )
     def stream_logs(self, poll: int = 5, start_time: Optional[Any] = None, tail_lines: Optional[int] = None) -> None:
         """Stream CloudWatch logs in real-time (like ``kubectl logs -f``).
 
diff --git a/sagemaker-train/src/sagemaker/train/common_utils/telemetry_params.py b/sagemaker-train/src/sagemaker/train/common_utils/telemetry_params.py
index bf3e5765db..b9766e52c9 100644
--- a/sagemaker-train/src/sagemaker/train/common_utils/telemetry_params.py
+++ b/sagemaker-train/src/sagemaker/train/common_utils/telemetry_params.py
@@ -9,8 +9,10 @@
     ("kms_key_id", TelemetryParamType.ATTR_EXISTS),
     ("mlflow_resource_arn", TelemetryParamType.ATTR_EXISTS),
     ("stopping_condition", TelemetryParamType.ATTR_EXISTS),
+    ("notification_rule_arn", TelemetryParamType.ATTR_EXISTS),
     ("validation_dataset", TelemetryParamType.KWARG_EXISTS),
     ("wait", TelemetryParamType.KWARG_EXISTS),
+    ("dry_run", TelemetryParamType.KWARG_EXISTS),
 ]
 
 # Common params for all evaluators
@@ -20,4 +22,5 @@
     ("networking", TelemetryParamType.ATTR_EXISTS),
     ("kms_key_id", TelemetryParamType.ATTR_EXISTS),
     ("mlflow_resource_arn", TelemetryParamType.ATTR_EXISTS),
+    ("dry_run", TelemetryParamType.KWARG_EXISTS),
 ]
diff --git a/sagemaker-train/src/sagemaker/train/evaluate/base_evaluator.py b/sagemaker-train/src/sagemaker/train/evaluate/base_evaluator.py
index 1d05b80a08..21bed9e84b 100644
--- a/sagemaker-train/src/sagemaker/train/evaluate/base_evaluator.py
+++ b/sagemaker-train/src/sagemaker/train/evaluate/base_evaluator.py
@@ -35,6 +35,8 @@
     _is_nova_model,
 )
 from sagemaker.train.common_utils.cloudwatch_metrics import _get_smhp_log_group
+from sagemaker.core.telemetry.telemetry_logging import _telemetry_emitter, TelemetryParamType
+from sagemaker.core.telemetry.constants import Feature
 from sagemaker.train.common_utils.log_streamer import (
     LogStreamer,
     _format_timestamp,
@@ -1096,6 +1098,13 @@ def evaluate(self, dry_run: bool = False) -> Any:
         """
         raise NotImplementedError("Subclasses must implement evaluate method")
 
+    @_telemetry_emitter(
+        feature=Feature.MODEL_CUSTOMIZATION,
+        func_name="BaseEvaluator.stream_logs",
+        telemetry_params=[
+            ("compute", TelemetryParamType.ATTR_TYPE),
+        ],
+    )
     def stream_logs(self, poll: int = 5, start_time=None) -> None:
         """Stream CloudWatch logs for the latest evaluation execution.