diff --git a/litellm/integrations/datadog.py b/litellm/integrations/datadog.py
new file mode 100644
index 000000000..d5adac1fc
--- /dev/null
+++ b/litellm/integrations/datadog.py
@@ -0,0 +1,141 @@
+#### What this does ####
+#    On success + failure, log events to Supabase
+
+import dotenv, os
+import requests
+
+dotenv.load_dotenv()  # Loading env variables using dotenv
+import traceback
+import datetime, subprocess, sys
+import litellm, uuid
+from litellm._logging import print_verbose, verbose_logger
+from datadog_api_client.v2 import ApiClient, Configuration
+from datadog import statsd, api as datadog_api, initialize as datadog_initialize
+
+# Define DataDog client
+
+from datadog_api_client import ApiClient, Configuration
+from datadog_api_client.v2.api.logs_api import LogsApi
+from datadog_api_client.v2.model.log import Log
+from datadog_api_client.v2.model import *
+from datadog_api_client.v2.models import *
+
+
+class DataDogLogger:
+    # Class variables or attributes
+    def __init__(
+        self,
+        **kwargs,
+    ):
+
+        try:
+            verbose_logger.debug(f"in init datadog logger")
+            pass
+
+        except Exception as e:
+            print_verbose(f"Got exception on init s3 client {str(e)}")
+            raise e
+
+    async def _async_log_event(
+        self, kwargs, response_obj, start_time, end_time, print_verbose, user_id
+    ):
+        self.log_event(kwargs, response_obj, start_time, end_time, print_verbose)
+
+    def log_event(
+        self, kwargs, response_obj, start_time, end_time, user_id, print_verbose
+    ):
+        try:
+            verbose_logger.debug(
+                f"datadog Logging - Enters logging function for model {kwargs}"
+            )
+            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()
+            except:
+                response_time = None
+
+            try:
+                response_obj = dict(response_obj)
+            except:
+                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,
+                "startTime": start_time,
+                "endTime": end_time,
+                "responseTime (seconds)": response_time,
+                "model": kwargs.get("model", ""),
+                "user": kwargs.get("user", ""),
+                "modelParameters": optional_params,
+                "spend": kwargs.get("response_cost", 0),
+                "messages": messages,
+                "response": response_obj,
+                "usage": usage,
+                "metadata": clean_metadata,
+            }
+
+            # Ensure everything in the payload is converted to str
+            for key, value in payload.items():
+                try:
+                    payload[key] = str(value)
+                except:
+                    # non blocking if it can't cast to a str
+                    pass
+            import json
+
+            payload = json.dumps(payload)
+
+            print_verbose(f"\ndd Logger - Logging payload = {payload}")
+
+            configuration = Configuration()
+            with ApiClient(configuration) as api_client:
+                api_instance = LogsApi(api_client)
+                body = HTTPLog(
+                    [
+                        HTTPLogItem(
+                            ddsource="litellm",
+                            message=payload,
+                            service="litellm-server",
+                        ),
+                    ]
+                )
+                response = api_instance.submit_log(body)
+
+            print_verbose(
+                f"Datadog Layer Logging - final response object: {response_obj}"
+            )
+        except Exception as e:
+            traceback.print_exc()
+            verbose_logger.debug(
+                f"Datadog Layer Error - {str(e)}\n{traceback.format_exc()}"
+            )
+            pass