diff --git a/tests/utils/loggers/test_tensorboard.py b/tests/utils/loggers/test_tensorboard.py
index 709c437cf0..d9eec49885 100644
--- a/tests/utils/loggers/test_tensorboard.py
+++ b/tests/utils/loggers/test_tensorboard.py
@@ -11,20 +11,53 @@
 
 import tempfile
 import unittest
-from unittest.mock import Mock, patch
+from unittest.mock import MagicMock, Mock, patch
 
 from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
+from torchtnt.utils.anomaly_evaluation import ThresholdEvaluator
+from torchtnt.utils.loggers.anomaly_logger import TrackedMetric
 
 from torchtnt.utils.loggers.tensorboard import TensorBoardLogger
 
 
 class TensorBoardLoggerTest(unittest.TestCase):
-    def test_log(self: TensorBoardLoggerTest) -> None:
+
+    @patch(
+        "torchtnt.utils.loggers.anomaly_logger.AnomalyLogger.on_anomaly_detected",
+    )
+    def test_log(
+        self: TensorBoardLoggerTest, mock_on_anomaly_detected: MagicMock
+    ) -> None:
         with tempfile.TemporaryDirectory() as log_dir:
-            logger = TensorBoardLogger(path=log_dir)
-            for i in range(5):
-                logger.log("test_log", float(i) ** 2, i)
-            logger.close()
+            logger = TensorBoardLogger(
+                path=log_dir,
+                tracked_metrics=[
+                    TrackedMetric(
+                        name="test_log",
+                        anomaly_evaluators=[
+                            ThresholdEvaluator(min_val=25),
+                        ],
+                        evaluate_every_n_steps=2,
+                        warmup_steps=2,
+                    )
+                ],
+            )
+            warning_container = []
+            with patch(
+                "torchtnt.utils.loggers.anomaly_logger.logging.Logger.warning",
+                side_effect=warning_container.append,
+            ):
+                for i in range(5):
+                    logger.log("test_log", float(i) ** 2, i)
+                logger.close()
+
+            self.assertEqual(
+                warning_container,
+                [
+                    "Found anomaly in metric: test_log, with value: 16.0, using evaluator: ThresholdEvaluator"
+                ],
+            )
+            mock_on_anomaly_detected.assert_called_with("test_log", 16.0, 4)
 
             acc = EventAccumulator(log_dir)
             acc.Reload()
diff --git a/torchtnt/utils/loggers/tensorboard.py b/torchtnt/utils/loggers/tensorboard.py
index 3c26da30e9..a54f230566 100644
--- a/torchtnt/utils/loggers/tensorboard.py
+++ b/torchtnt/utils/loggers/tensorboard.py
@@ -11,16 +11,17 @@
 
 import atexit
 import logging
-from typing import Any, Dict, Mapping, Optional, Union
+from typing import Any, Dict, List, Mapping, Optional, Union
 
 from torch.utils.tensorboard import SummaryWriter
 from torchtnt.utils.distributed import get_global_rank
-from torchtnt.utils.loggers.logger import MetricLogger, Scalar
+from torchtnt.utils.loggers.anomaly_logger import AnomalyLogger, TrackedMetric
+from torchtnt.utils.loggers.logger import Scalar
 
 logger: logging.Logger = logging.getLogger(__name__)
 
 
-class TensorBoardLogger(MetricLogger):
+class TensorBoardLogger(AnomalyLogger):
     """
     Simple logger for TensorBoard.
 
@@ -28,6 +29,10 @@ class TensorBoardLogger(MetricLogger):
     will be written to.  If the environment variable `RANK` is defined,
     logger will only log if RANK = 0.
 
+    Metrics may be tracked for anomaly detection if they are configured in the
+    optional `tracked_metrics` argument. See :class:`torchtnt.utils.loggers.AnomalyLogger`
+    for more details.
+
     Note:
         If using this logger with distributed training:
 
@@ -38,6 +43,7 @@ class TensorBoardLogger(MetricLogger):
 
     Args:
         path (str): path to write logs to
+        tracked_metrics: Optional list of TrackedMetric objects to track for anomaly detection.
         *args: Extra positional arguments to pass to SummaryWriter
         **kwargs: Extra keyword arguments to pass to SummaryWriter
 
@@ -49,7 +55,14 @@ class TensorBoardLogger(MetricLogger):
         logger.close()
     """
 
-    def __init__(self: TensorBoardLogger, path: str, *args: Any, **kwargs: Any) -> None:
+    def __init__(
+        self: TensorBoardLogger,
+        path: str,
+        tracked_metrics: Optional[List[TrackedMetric]] = None,
+        *args: Any,
+        **kwargs: Any,
+    ) -> None:
+        super().__init__(tracked_metrics)
         self._writer: Optional[SummaryWriter] = None
         self._path: str = path
         self._rank: int = get_global_rank()
@@ -100,6 +113,8 @@ def log(self: TensorBoardLogger, name: str, data: Scalar, step: int) -> None:
         if self._writer:
             self._writer.add_scalar(name, data, global_step=step, new_style=True)
 
+        super().log(name, data, step)
+
     def log_text(self: TensorBoardLogger, name: str, data: str, step: int) -> None:
         """Add text data to summary.