diff --git a/python/ray/tune/logger.py b/python/ray/tune/logger.py
index c14936d29..fdc73ed2b 100644
--- a/python/ray/tune/logger.py
+++ b/python/ray/tune/logger.py
@@ -23,7 +23,7 @@ from ray.tune.result import (NODE_IP, TRAINING_ITERATION, TIME_TOTAL_S,
 logger = logging.getLogger(__name__)
 
 tf = None
-use_tf150_api = True
+VALID_SUMMARY_TYPES = [int, float, np.float32, np.float64, np.int32]
 
 
 class Logger(object):
@@ -135,34 +135,71 @@ class JsonLogger(Logger):
             cloudpickle.dump(self.config, f)
 
 
-def to_tf_values(result, path):
-    if use_tf150_api:
-        type_list = [int, float, np.float32, np.float64, np.int32]
+def tf2_compat_logger(config, logdir):
+    global tf
+    if "RLLIB_TEST_NO_TF_IMPORT" in os.environ:
+        logger.warning("Not importing TensorFlow for test purposes")
+        tf = None
+        raise RuntimeError("Not importing TensorFlow for test purposes")
     else:
-        type_list = [int, float]
+        import tensorflow as tf
+        use_tf2_api = (distutils.version.LooseVersion(tf.__version__) >=
+                       distutils.version.LooseVersion("1.14.0"))
+        if use_tf2_api:
+            tf = tf.compat.v2  # setting this for 1.14
+            return TF2Logger(config, logdir)
+        else:
+            return TFLogger(config, logdir)
+
+
+class TF2Logger(Logger):
+    def _init(self):
+        self._file_writer = tf.summary.create_file_writer(self.logdir)
+
+    def on_result(self, result):
+        with tf.device("/CPU:0"):
+            with self._file_writer.as_default():
+                step = result.get(
+                    TIMESTEPS_TOTAL) or result[TRAINING_ITERATION]
+
+                tmp = result.copy()
+                for k in [
+                        "config", "pid", "timestamp", TIME_TOTAL_S,
+                        TRAINING_ITERATION
+                ]:
+                    if k in tmp:
+                        del tmp[k]  # not useful to log these
+
+                flat_result = flatten_dict(tmp, delimiter="/")
+                path = ["ray", "tune"]
+                for attr, value in flat_result.items():
+                    if type(value) in VALID_SUMMARY_TYPES:
+                        tf.summary.scalar(
+                            "/".join(path + [attr]), value, step=step)
+        self._file_writer.flush()
+
+    def flush(self):
+        self._file_writer.flush()
+
+    def close(self):
+        self._file_writer.close()
+
+
+def to_tf_values(result, path):
     flat_result = flatten_dict(result, delimiter="/")
     values = [
         tf.Summary.Value(tag="/".join(path + [attr]), simple_value=value)
-        for attr, value in flat_result.items() if type(value) in type_list
+        for attr, value in flat_result.items()
+        if type(value) in VALID_SUMMARY_TYPES
     ]
     return values
 
 
 class TFLogger(Logger):
     def _init(self):
-        try:
-            global tf, use_tf150_api
-            if "RLLIB_TEST_NO_TF_IMPORT" in os.environ:
-                logger.warning("Not importing TensorFlow for test purposes")
-                tf = None
-            else:
-                import tensorflow
-                tf = tensorflow
-                use_tf150_api = (distutils.version.LooseVersion(tf.VERSION) >=
-                                 distutils.version.LooseVersion("1.5.0"))
-        except ImportError:
-            logger.warning("Couldn't import TensorFlow - "
-                           "disabling TensorBoard logging.")
+        logger.info(
+            "Initializing TFLogger instead of TF2Logger. We recommend "
+            "migrating to TF2.0. This class will be removed in the future.")
         self._file_writer = tf.summary.FileWriter(self.logdir)
 
     def on_result(self, result):
@@ -220,7 +257,7 @@ class CSVLogger(Logger):
         self._file.close()
 
 
-DEFAULT_LOGGERS = (JsonLogger, CSVLogger, TFLogger)
+DEFAULT_LOGGERS = (JsonLogger, CSVLogger, tf2_compat_logger)
 
 
 class UnifiedLogger(Logger):
@@ -250,9 +287,9 @@ class UnifiedLogger(Logger):
         for cls in self._logger_cls_list:
             try:
                 self._loggers.append(cls(self.config, self.logdir))
-            except Exception:
-                logger.warning("Could not instantiate {} - skipping.".format(
-                    str(cls)))
+            except Exception as exc:
+                logger.warning("Could not instantiate {}: {}.".format(
+                    cls.__name__, str(exc)))
         self._log_syncer = get_log_syncer(
             self.logdir,
             remote_dir=self.logdir,