diff --git a/data-processing-lib/python/src/data_processing/runtime/pure_python/transform_orchestrator.py b/data-processing-lib/python/src/data_processing/runtime/pure_python/transform_orchestrator.py
index 710adb62c9..8692da29e3 100644
--- a/data-processing-lib/python/src/data_processing/runtime/pure_python/transform_orchestrator.py
+++ b/data-processing-lib/python/src/data_processing/runtime/pure_python/transform_orchestrator.py
@@ -9,9 +9,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 ################################################################################
-
+import os
 import time
 import traceback
+import psutil
 from datetime import datetime
 from multiprocessing import Pool
 from typing import Any
@@ -24,12 +25,31 @@
     PythonTransformRuntimeConfiguration,
 )
 from data_processing.transform import AbstractBinaryTransform, TransformStatistics
-from data_processing.utils import get_logger
+from data_processing.utils import GB, get_logger
 
 
 logger = get_logger(__name__)
 
 
+@staticmethod
+def _execution_resources() -> dict[str, Any]:
+    """
+    Get Execution resource
+    :return: tuple of cpu/memory usage
+    """
+    # Getting loadover15 minutes
+    load1, load5, load15 = psutil.getloadavg()
+    # Getting memory used
+    mused = round(psutil.virtual_memory()[3] / GB, 2)
+    return {
+        "cpus": round((load15/os.cpu_count()) * 100, 1),
+        "gpus": 0,
+        "memory": mused,
+        "object_store": 0,
+    }
+
+
+
 def orchestrate(
     data_access_factory: DataAccessFactoryBase,
     runtime_config: PythonTransformRuntimeConfiguration,
@@ -43,6 +63,7 @@ def orchestrate(
     :return: 0 - success or 1 - failure
     """
     start_ts = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    start_time = time.time()
     logger.info(f"orchestrator {runtime_config.get_name()} started at {start_ts}")
     # create statistics
     statistics = TransformStatistics()
@@ -118,6 +139,7 @@ def orchestrate(
             "job_input_params": input_params
             | data_access_factory.get_input_params()
             | execution_config.get_input_params(),
+            "execution_stats": _execution_resources() | {"execution time, min": round((time.time() - start_time) / 60.0, 3)},
             "job_output_stats": stats,
         }
         logger.debug(f"Saving job metadata: {metadata}.")