diff --git a/examples/trainercontroller_configs/epoch-level-training-loss-below-threshold-log-config.yaml b/examples/trainercontroller_configs/epoch-level-training-loss-below-threshold-log-config.yaml
new file mode 100644
index 000000000..53c8a1777
--- /dev/null
+++ b/examples/trainercontroller_configs/epoch-level-training-loss-below-threshold-log-config.yaml
@@ -0,0 +1,14 @@
+controller_metrics:
+  - name: training_loss_window
+    class: HistoryBasedMetric
+    arguments:
+      window_size: 1
+controllers:
+  - name: epoch_level_stop_on_training_loss_below_threshold
+    triggers:
+      - on_step_end
+    rule: len(training_loss_window["training_loss"]["loss"]) == training_loss_window["window_size"] and training_loss_window["training_loss"]["loss"][0] < 2.2 and training_loss_window["training_loss"]["epoch"][0] > 2
+    config:
+      trigger_log_level: warning
+    operations:
+      - hfcontrols.should_training_stop
\ No newline at end of file
diff --git a/tuning/trainercontroller/callback.py b/tuning/trainercontroller/callback.py
index ebb661b3f..2c5ddfcdf 100644
--- a/tuning/trainercontroller/callback.py
+++ b/tuning/trainercontroller/callback.py
@@ -59,11 +59,14 @@
 CONTROLLER_CONFIG_KEY = "config"
 CONTROLLER_PATIENCE_CONFIG_KEY = "patience"
 CONTROLLER_TRIGGERS_KEY = "triggers"
+CONTROLLER_CONFIG_TRIGGER_LOG_LEVEL = "trigger_log_level"
 CONTROLLER_OPERATIONS_KEY = OPERATIONS_KEY
 
-# Default operations / metrics to register
+# Default values
 DEFAULT_OPERATIONS = {"operations": [{"name": "hfcontrols", "class": "HFControls"}]}
 DEFAULT_METRICS = {}
+DEFAULT_CONFIG = {}
+DEFAULT_TRIGGER_LOG_LEVEL = "debug"
 
 # pylint: disable=too-many-instance-attributes
 class TrainerControllerCallback(TrainerCallback):
@@ -250,15 +253,14 @@ def _take_control_actions(self, event_name: str, **kwargs):
                     continue
                 if rule_succeeded:
                     for operation_action in control_action.operation_actions:
-                        logger.info(
-                            "Taking [%s] action in controller [%s]",
-                            operation_action.action,
-                            control_action.name,
-                        )
                         operation_action.instance.act(
                             action=operation_action.action,
                             event_name=event_name,
                             tc_metrics=self.metrics,
+                            control_name=control_action.name,
+                            log_level=control_action.config[
+                                CONTROLLER_CONFIG_TRIGGER_LOG_LEVEL
+                            ],
                             **kwargs,
                         )
 
@@ -303,6 +305,7 @@ def on_init_end(
         kwargs["state"] = state
         kwargs["control"] = control
 
+        log_levels = logging.get_log_levels_dict()
         # Check if there any metrics listed in the configuration
         if (
             CONTROLLER_METRICS_KEY not in self.trainer_controller_config
@@ -399,8 +402,24 @@ def on_init_end(
                         ),
                         operation_actions=[],
                     )
+                    config_log_level_str = DEFAULT_TRIGGER_LOG_LEVEL
                     if CONTROLLER_CONFIG_KEY in controller:
                         control.config = controller[CONTROLLER_CONFIG_KEY]
+                        config_log_level_str = control.config.get(
+                            CONTROLLER_CONFIG_TRIGGER_LOG_LEVEL, config_log_level_str
+                        )
+                        if config_log_level_str not in log_levels:
+                            logger.warning(
+                                "Incorrect trigger log-level [%s] specified in the config."
+                                " Defaulting to 'debug' level",
+                                config_log_level_str,
+                            )
+                            config_log_level_str = DEFAULT_TRIGGER_LOG_LEVEL
+                    else:
+                        control.config = DEFAULT_CONFIG
+                    control.config[CONTROLLER_CONFIG_TRIGGER_LOG_LEVEL] = log_levels[
+                        config_log_level_str
+                    ]
                     if CONTROLLER_PATIENCE_CONFIG_KEY in controller:
                         control.patience = PatienceControl(
                             **controller[CONTROLLER_PATIENCE_CONFIG_KEY]
diff --git a/tuning/trainercontroller/operations/operation.py b/tuning/trainercontroller/operations/operation.py
index baa220c17..6e6d764fb 100644
--- a/tuning/trainercontroller/operations/operation.py
+++ b/tuning/trainercontroller/operations/operation.py
@@ -3,6 +3,11 @@
 import inspect
 import re
 
+# Third Party
+from transformers.utils import logging
+
+logger = logging.get_logger(__name__)
+
 
 class Operation(metaclass=abc.ABCMeta):
     """Base class for operations"""
@@ -32,15 +37,27 @@ def validate(self, action: str) -> bool:
         """
         return action in self.valid_actions
 
-    def act(self, action: str, **kwargs):
+    def act(
+        self, action: str, event_name: str, control_name: str, log_level: int, **kwargs
+    ):
         """Validates the action and invokes it.
 
         Args:
             action: str. String depicting the action.
+            event_name: str. Event name triggering the act.
+            control_name: str. Name of the controller defining the act.
+            log_level: int. Log level for triggering the log.
             kwargs: List of arguments (key, value)-pairs.
         """
         if not self.validate(action):
             raise ValueError(f"Invalid operation {action}")
+        logger.log(
+            log_level,
+            "Taking [%s] action in controller [%s] triggered at event [%s]",
+            action,
+            control_name,
+            event_name,
+        )
         self.valid_actions[action](**kwargs)
 
     def get_actions(self) -> list[str]: