diff --git a/docs/monitoring.md b/docs/monitoring.md
index 37ede476c187dce91004c3d4be86b1d39066fa6e..6816671ffbf461ff004eb131ff699b499f3e8c1b 100644
--- a/docs/monitoring.md
+++ b/docs/monitoring.md
@@ -173,6 +173,8 @@ follows:
 Note that in all of these UIs, the tables are sortable by clicking their headers,
 making it easy to identify slow tasks, data skew, etc.
 
+Note that the history server only displays completed Spark jobs. One way to signal the completion of a Spark job is to stop the Spark Context explicitly (`sc.stop()`), or in Python using the `with SparkContext() as sc:` to handle the Spark Context setup and tear down, and still show the job history on the UI.
+
 # Metrics
 
 Spark has a configurable metrics system based on the