diff --git a/litellm/__init__.py b/litellm/__init__.py
index 65b1b3465..43f91fe58 100644
--- a/litellm/__init__.py
+++ b/litellm/__init__.py
@@ -68,6 +68,7 @@ callbacks: List[Union[Callable, _custom_logger_compatible_callbacks_literal]] =
 langfuse_default_tags: Optional[List[str]] = None
 langsmith_batch_size: Optional[int] = None
 argilla_batch_size: Optional[int] = None
+datadog_use_v1: Optional[bool] = False  # if you want to use v1 datadog logged payload
 argilla_transformation_object: Optional[Dict[str, Any]] = None
 _async_input_callback: List[Callable] = (
     []
diff --git a/litellm/integrations/datadog/datadog.py b/litellm/integrations/datadog/datadog.py
index a100c2863..c5454a273 100644
--- a/litellm/integrations/datadog/datadog.py
+++ b/litellm/integrations/datadog/datadog.py
@@ -182,12 +182,20 @@ class DataDogLogger(CustomBatchLogger):
             verbose_logger.debug(
                 "Datadog: Logging - Enters logging function for model %s", kwargs
             )
-            dd_payload = self.create_datadog_logging_payload(
-                kwargs=kwargs,
-                response_obj=response_obj,
-                start_time=start_time,
-                end_time=end_time,
-            )
+            if litellm.datadog_use_v1 is True:
+                dd_payload = self._create_v0_logging_payload(
+                    kwargs=kwargs,
+                    response_obj=response_obj,
+                    start_time=start_time,
+                    end_time=end_time,
+                )
+            else:
+                dd_payload = self.create_datadog_logging_payload(
+                    kwargs=kwargs,
+                    response_obj=response_obj,
+                    start_time=start_time,
+                    end_time=end_time,
+                )
 
             response = self.sync_client.post(
                 url=self.intake_url,
@@ -355,3 +363,88 @@ class DataDogLogger(CustomBatchLogger):
         No user has asked for this so far, this might be spammy on datatdog. If need arises we can implement this
         """
         return
+
+    def _create_v0_logging_payload(
+        self,
+        kwargs: Union[dict, Any],
+        response_obj: Any,
+        start_time: datetime.datetime,
+        end_time: datetime.datetime,
+    ) -> DatadogPayload:
+        """
+        Note: This is our V1 Version of DataDog Logging Payload
+
+
+        (Not Recommended) If you want this to get logged set `litellm.datadog_use_v1 = True`
+        """
+        import json
+
+        litellm_params = kwargs.get("litellm_params", {})
+        metadata = (
+            litellm_params.get("metadata", {}) or {}
+        )  # if litellm_params['metadata'] == None
+        messages = kwargs.get("messages")
+        optional_params = kwargs.get("optional_params", {})
+        call_type = kwargs.get("call_type", "litellm.completion")
+        cache_hit = kwargs.get("cache_hit", False)
+        usage = response_obj["usage"]
+        id = response_obj.get("id", str(uuid.uuid4()))
+        usage = dict(usage)
+        try:
+            response_time = (end_time - start_time).total_seconds() * 1000
+        except Exception:
+            response_time = None
+
+        try:
+            response_obj = dict(response_obj)
+        except Exception:
+            response_obj = response_obj
+
+        # Clean Metadata before logging - never log raw metadata
+        # the raw metadata can contain circular references which leads to infinite recursion
+        # we clean out all extra litellm metadata params before logging
+        clean_metadata = {}
+        if isinstance(metadata, dict):
+            for key, value in metadata.items():
+                # clean litellm metadata before logging
+                if key in [
+                    "endpoint",
+                    "caching_groups",
+                    "previous_models",
+                ]:
+                    continue
+                else:
+                    clean_metadata[key] = value
+
+        # Build the initial payload
+        payload = {
+            "id": id,
+            "call_type": call_type,
+            "cache_hit": cache_hit,
+            "start_time": start_time,
+            "end_time": end_time,
+            "response_time": response_time,
+            "model": kwargs.get("model", ""),
+            "user": kwargs.get("user", ""),
+            "model_parameters": optional_params,
+            "spend": kwargs.get("response_cost", 0),
+            "messages": messages,
+            "response": response_obj,
+            "usage": usage,
+            "metadata": clean_metadata,
+        }
+
+        make_json_serializable(payload)
+        json_payload = json.dumps(payload)
+
+        verbose_logger.debug("Datadog: Logger - Logging payload = %s", json_payload)
+
+        dd_payload = DatadogPayload(
+            ddsource=os.getenv("DD_SOURCE", "litellm"),
+            ddtags="",
+            hostname="",
+            message=json_payload,
+            service="litellm-server",
+            status=DataDogStatus.INFO,
+        )
+        return dd_payload