Update

docs/website/docs/running-in-production/monitoring.md

@@ -68,6 +68,26 @@ Normalized data for the following tables:
 - players_profiles: 4 row(s)
 ```
 
+To load these info back to the destination you can use the following:
+```python
+# Create a pipeline with the specified name, destination, and dataset
+# Run the pipeline
+
+# Get the trace of the last run of the pipeline
+# The trace contains timing information on extract, normalize, and load steps
+trace = pipeline.last_trace
+
+# Load the trace information into a table named "_trace" in the destination
+pipeline.run([trace], table_name="_trace")
+```
+This process loads several additional tables to the destination, which provide insights into
+the extract, normalize, and load steps. Information on the number of rows loaded for each table,
+along with the `load_id`, can be found in the `_trace__steps__extract_info__table_metrics` table.
+The `load_id` is an epoch timestamp that indicates when the loading was completed. Here's graphical
+representation of the rows loaded with `load_id` for different tables:
+
+![image](https://storage.googleapis.com/dlt-blog-images/docs_monitoring_count_of_rows_vs_load_id.jpg)
+
 ### Data load time
 Data loading time for each table can be obtained by using the following command: