diff --git a/CHANGELOG.md b/CHANGELOG.md
index 7bfe08edb1..524540530b 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -333,8 +333,12 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed `is_global_zero` check in `training_epoch_loop` before `logger.save`. If you have a custom logger that implements `save` the Trainer will now call `save` on all ranks by default. To change this behavior add `@rank_zero_only` to your `save` implementation ([#12134](https://github.com/PyTorchLightning/pytorch-lightning/pull/12134))
 
 
+- Disabled tuner with distributed strategies ([#12179](https://github.com/PyTorchLightning/pytorch-lightning/pull/12179))
+
+
 - Marked `trainer.logger_connector` as protected ([#12195](https://github.com/PyTorchLightning/pytorch-lightning/pull/12195))
 
+
 ### Deprecated
 
 - Deprecated `training_type_plugin` property in favor of `strategy` in `Trainer` and updated the references ([#11141](https://github.com/PyTorchLightning/pytorch-lightning/pull/11141))
diff --git a/pytorch_lightning/tuner/tuning.py b/pytorch_lightning/tuner/tuning.py
index f64183a92b..b1a38bd276 100644
--- a/pytorch_lightning/tuner/tuning.py
+++ b/pytorch_lightning/tuner/tuning.py
@@ -17,6 +17,7 @@ import pytorch_lightning as pl
 from pytorch_lightning.trainer.states import TrainerStatus
 from pytorch_lightning.tuner.batch_size_scaling import scale_batch_size
 from pytorch_lightning.tuner.lr_finder import _LRFinder, lr_find
+from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.types import EVAL_DATALOADERS, TRAIN_DATALOADERS
 
 
@@ -43,6 +44,13 @@ class Tuner:
 
         self.trainer.strategy.connect(model)
 
+        is_tuning = self.trainer.auto_scale_batch_size or self.trainer.auto_lr_find
+        if self.trainer._accelerator_connector.is_distributed and is_tuning:
+            raise MisconfigurationException(
+                "`trainer.tune()` is currently not supported with"
+                f" `Trainer(strategy={self.trainer.strategy.strategy_name!r})`."
+            )
+
         # Run auto batch size scaling
         if self.trainer.auto_scale_batch_size:
             if isinstance(self.trainer.auto_scale_batch_size, str):
diff --git a/tests/tuner/test_auto_gpu_select.py b/tests/trainer/properties/test_auto_gpu_select.py
similarity index 100%
rename from tests/tuner/test_auto_gpu_select.py
rename to tests/trainer/properties/test_auto_gpu_select.py
diff --git a/tests/tuner/test_tuning.py b/tests/tuner/test_tuning.py
new file mode 100644
index 0000000000..aadacb6440
--- /dev/null
+++ b/tests/tuner/test_tuning.py
@@ -0,0 +1,27 @@
+# Copyright The PyTorch Lightning team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import pytest
+
+from pytorch_lightning import Trainer
+from pytorch_lightning.utilities.exceptions import MisconfigurationException
+from tests.helpers.boring_model import BoringModel
+
+
+def test_tuner_with_distributed_strategies():
+    """Test that an error is raised when tuner is used with multi-device strategy."""
+    trainer = Trainer(auto_scale_batch_size=True, devices=2, strategy="ddp", accelerator="cpu")
+    model = BoringModel()
+
+    with pytest.raises(MisconfigurationException, match=r"not supported with `Trainer\(strategy='ddp'\)`"):
+        trainer.tune(model)