diff --git a/CHANGELOG.md b/CHANGELOG.md
index d1a2e19679..c9dff0862a 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -102,6 +102,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
     * Some configuration errors that were previously raised as `MisconfigurationException`s will now be raised as `ProcessRaisedException` (torch>=1.8) or as `Exception` (torch<1.8)
 
 
+- Changed the info message for finalizing ddp-spawn worker processes to a debug-level message ([#10864](https://github.com/PyTorchLightning/pytorch-lightning/pull/10864))
+
+
 - Removed duplicated file extension when uploading model checkpoints with `NeptuneLogger` ([#11015](https://github.com/PyTorchLightning/pytorch-lightning/pull/11015))
 
 
diff --git a/pytorch_lightning/plugins/training_type/ddp_spawn.py b/pytorch_lightning/plugins/training_type/ddp_spawn.py
index b5373e2202..ee7a1efa28 100644
--- a/pytorch_lightning/plugins/training_type/ddp_spawn.py
+++ b/pytorch_lightning/plugins/training_type/ddp_spawn.py
@@ -38,6 +38,7 @@ from pytorch_lightning.utilities.distributed import distributed_available
 from pytorch_lightning.utilities.distributed import group as _group
 from pytorch_lightning.utilities.distributed import (
     init_dist_connection,
+    rank_zero_debug,
     rank_zero_only,
     ReduceOp,
     sync_ddp_if_available,
@@ -219,7 +220,7 @@ class DDPSpawnPlugin(ParallelPlugin):
         return [self.root_device.index]
 
     def _collect_rank_zero_results(self, trainer: "pl.Trainer", results: Any) -> Optional["_SpawnOutput"]:
-        rank_zero_warn("cleaning up ddp environment...")
+        rank_zero_debug("Finalizing the DDP spawn environment.")
         checkpoint_callback = trainer.checkpoint_callback
         best_model_path = checkpoint_callback.best_model_path if checkpoint_callback else None
 
diff --git a/pytorch_lightning/plugins/training_type/tpu_spawn.py b/pytorch_lightning/plugins/training_type/tpu_spawn.py
index 4050f71fc0..4afb61705c 100644
--- a/pytorch_lightning/plugins/training_type/tpu_spawn.py
+++ b/pytorch_lightning/plugins/training_type/tpu_spawn.py
@@ -30,10 +30,10 @@ from pytorch_lightning.plugins.precision import PrecisionPlugin
 from pytorch_lightning.plugins.training_type.ddp_spawn import _FakeQueue, _SpawnOutput, DDPSpawnPlugin
 from pytorch_lightning.trainer.connectors.data_connector import DataConnector
 from pytorch_lightning.trainer.states import TrainerFn
-from pytorch_lightning.utilities import _TPU_AVAILABLE, find_shared_parameters, rank_zero_warn, set_shared_parameters
+from pytorch_lightning.utilities import _TPU_AVAILABLE, find_shared_parameters, set_shared_parameters
 from pytorch_lightning.utilities.apply_func import move_data_to_device
 from pytorch_lightning.utilities.data import has_len
-from pytorch_lightning.utilities.distributed import rank_zero_only, ReduceOp
+from pytorch_lightning.utilities.distributed import rank_zero_debug, rank_zero_only, ReduceOp
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.model_helpers import is_overridden
 from pytorch_lightning.utilities.seed import reset_seed
@@ -174,7 +174,7 @@ class TPUSpawnPlugin(DDPSpawnPlugin):
             rendezvous(name)
 
     def _collect_rank_zero_results(self, trainer: "pl.Trainer", results: Any) -> Optional["_SpawnOutput"]:
-        rank_zero_warn("cleaning up tpu spawn environment...")
+        rank_zero_debug("Finalizing the TPU spawn environment.")
         checkpoint_callback = trainer.checkpoint_callback
         best_model_path = checkpoint_callback.best_model_path if checkpoint_callback else None