diff --git a/datareservoirio/_logging.py b/datareservoirio/_logging.py
index cc90fe2a..b9deb117 100644
--- a/datareservoirio/_logging.py
+++ b/datareservoirio/_logging.py
@@ -27,6 +27,24 @@ def _ensure_azure_monitor_configured(connection_string, logger_name):
                 _configured_loggers[cache_key] = True
 
 
+@lru_cache(maxsize=1)
+def get_metric_logger() -> logging.Logger:
+    logger = logging.getLogger(__name__ + "_metric_appinsight")
+    if os.getenv(ENV_VAR_ENABLE_APP_INSIGHTS) is not None:
+        enable_app_insights = os.environ[ENV_VAR_ENABLE_APP_INSIGHTS].lower()
+        if enable_app_insights == "true" or enable_app_insights == "1":
+            # Prevent messages from being passed directly to ancestor logger handlers,
+            # since ancestor logger levels and filters are not considered during propagation.
+            # https://docs.python.org/3.12/library/logging.html#logging.Logger.propagate
+            logger.propagate = False
+            logger.setLevel(logging.DEBUG)
+            _ensure_azure_monitor_configured(
+                connection_string=environment._application_insight_connectionstring,
+                logger_name=__name__ + "_metric_appinsight",
+            )
+    return logger
+
+
 @lru_cache(maxsize=1)
 def get_exceptions_logger() -> logging.Logger:
     exceptions_logger = logging.getLogger(__name__ + "_exception_logger")
diff --git a/datareservoirio/client.py b/datareservoirio/client.py
index 22c7ca4c..742be274 100644
--- a/datareservoirio/client.py
+++ b/datareservoirio/client.py
@@ -1,11 +1,9 @@
 import logging
-import os
 import time
 import warnings
 from collections import defaultdict
 from concurrent.futures import ThreadPoolExecutor
-from datetime import datetime
-from functools import lru_cache, wraps
+from functools import wraps
 from operator import itemgetter
 from urllib.parse import urlencode
 from uuid import uuid4
@@ -13,7 +11,7 @@
 import numpy as np
 import pandas as pd
 import requests
-from azure.monitor.opentelemetry import configure_azure_monitor
+from opentelemetry import trace
 from tenacity import (
     retry,
     retry_if_exception_type,
@@ -23,34 +21,13 @@
 )
 from tqdm.auto import tqdm
 
-from datareservoirio._constants import ENV_VAR_ENABLE_APP_INSIGHTS
-
-from ._logging import _ensure_azure_monitor_configured, log_decorator
+from ._logging import get_metric_logger, log_decorator
 from ._utils import function_translation, period_translation
 from .globalsettings import environment
 from .storage import Storage
 
 log = logging.getLogger(__name__)
 
-
-@lru_cache(maxsize=1)
-def metric() -> logging.Logger:
-    logger = logging.getLogger(__name__ + "_metric_appinsight")
-    if os.getenv(ENV_VAR_ENABLE_APP_INSIGHTS) is not None:
-        enable_app_insights = os.environ[ENV_VAR_ENABLE_APP_INSIGHTS].lower()
-        if enable_app_insights == "true" or enable_app_insights == "1":
-            # Prevent messages from being passed directly to ancestor logger handlers,
-            # since ancestor logger levels and filters are not considered during propagation.
-            # https://docs.python.org/3.12/library/logging.html#logging.Logger.propagate
-            logger.propagate = False
-            logger.setLevel(logging.DEBUG)
-            _ensure_azure_monitor_configured(
-                connection_string=environment._application_insight_connectionstring,
-                logger_name=__name__ + "_metric_appinsight",
-            )
-    return logger
-
-
 # Default values to push as start/end dates. (Limited by numpy.datetime64)
 _END_DEFAULT = 9214646400000000000  # 2262-01-01
 _START_DEFAULT = 0  # 1970-01-01
@@ -328,30 +305,34 @@ def _timer(metric_name="Timer"):
         def decorator(func):
             @wraps(func)
             def wrapper(self, series_id, start=None, end=None, **kwargs):
-                start_time = time.perf_counter()
-                result = func(self, series_id, start=start, end=end, **kwargs)
-                end_time = time.perf_counter()
-                elapsed_time = end_time - start_time
-                start_date_as_str = None
-                end_date_as_str = None
-                if start:
-                    start_date_as_str = pd.to_datetime(
-                        start, dayfirst=True, unit="ns", utc=True
-                    ).isoformat()
-                if end:
-                    end_date_as_str = pd.to_datetime(
-                        end, dayfirst=True, unit="ns", utc=True
-                    ).isoformat()
-                number_of_samples = len(result)
-                properties = {
-                    "series_id": series_id,
-                    "start": start_date_as_str,
-                    "end": end_date_as_str,
-                    "elapsed": elapsed_time,
-                    "number-of-samples": number_of_samples,
-                }
-                metric().info(metric_name, extra=properties)
-                return result
+                metric_logger = get_metric_logger()
+                tracer = trace.get_tracer(metric_logger.name)
+                with tracer.start_as_current_span(metric_name):
+
+                    start_time = time.perf_counter()
+                    result = func(self, series_id, start=start, end=end, **kwargs)
+                    end_time = time.perf_counter()
+                    elapsed_time = end_time - start_time
+                    start_date_as_str = None
+                    end_date_as_str = None
+                    if start:
+                        start_date_as_str = pd.to_datetime(
+                            start, dayfirst=True, unit="ns", utc=True
+                        ).isoformat()
+                    if end:
+                        end_date_as_str = pd.to_datetime(
+                            end, dayfirst=True, unit="ns", utc=True
+                        ).isoformat()
+                    number_of_samples = len(result)
+                    properties = {
+                        "series_id": series_id,
+                        "start": start_date_as_str,
+                        "end": end_date_as_str,
+                        "elapsed": elapsed_time,
+                        "number-of-samples": number_of_samples,
+                    }
+                    metric_logger.info(metric_name, extra=properties)
+                    return result
 
             return wrapper