Add timezone section

- Clarified the behaviour of ZenML regarding timezone-aware and naive datetime inputs for scheduled runs.
- Added detailed examples demonstrating how to set schedules using local and UTC timezones.
- Included reminders about the interpretation of cron expressions in relation to system timezones.

This update aims to help users avoid confusion with scheduled pipeline timings, ensuring they understand how to manage timezones effectively.

Author: strickvl

docs/book/user-guide/tutorials/managing-scheduled-pipelines.md

@@ -215,7 +215,7 @@ python run.py # or whatever you named your script
 > corresponding schedule in your orchestrator (Vertex AI in this example). You
 > can do this through the Google Cloud Console or using the orchestrator's API
 > (see below for code example).
-> ZenML's delete command may not always completely remove the underlying
+> ZenML's delete command never removes the underlying
 > orchestrator schedule.
 
 ## Step 4.1: Delete Schedule on GCP
@@ -322,6 +322,48 @@ for schedule in vertex_schedules:
 
 Here are some practical fixes for issues you might encounter with your scheduled pipelines:
 
+### Issue: Timezone Confusion with Scheduled Runs
+
+A common issue with scheduled pipelines is timezone confusion. Here's how ZenML handles timezone information:
+
+1. **If you provide a timezone-aware datetime**, ZenML will use it as is
+2. **If you provide a datetime without timezone information**, ZenML assumes it's in your local timezone and converts it to UTC for storage and communication with orchestrators
+
+For cloud orchestrators like Vertex AI, Kubeflow, and Airflow, schedules typically run in the orchestrator's timezone, which is usually UTC. This can lead to confusion if you expect a schedule to run at 9 AM in your local timezone but it runs at 9 AM UTC instead.
+
+To ensure your schedule runs at the expected time:
+
+```python
+from datetime import datetime, timezone
+import pytz
+from zenml.config.schedule import Schedule
+
+# Option 1: Explicitly use your local timezone (recommended)
+local_tz = pytz.timezone('America/Los_Angeles')  # Replace with your timezone
+local_time = local_tz.localize(datetime(2025, 1, 1, 9, 0))  # 9 AM in your timezone
+schedule = Schedule(
+    name="local-time-schedule",
+    cron_expression="0 9 * * *",
+    start_time=local_time  # ZenML will convert to UTC internally
+)
+
+# Option 2: Use UTC explicitly for clarity
+utc_time = datetime(2025, 1, 1, 17, 0, tzinfo=timezone.utc)  # 5 PM UTC = 9 AM PST
+schedule = Schedule(
+    name="utc-time-schedule",
+    cron_expression="0 17 * * *",  # Using UTC time in cron expression
+    start_time=utc_time
+)
+
+# To verify how ZenML interprets your times:
+from zenml.utils.time_utils import to_utc_timezone, to_local_tz
+print(f"Schedule will start at: {schedule.start_time} (as stored by ZenML)")
+print(f"In UTC that's: {to_utc_timezone(schedule.start_time)}")
+print(f"In your local time that's: {to_local_tz(schedule.start_time)}")
+```
+
+Remember that cron expressions themselves don't have timezone information - they're interpreted in the timezone of the system executing them (which for cloud orchestrators is usually UTC).
+
 ### Issue: Schedule Doesn't Run at the Expected Time
 
 If your pipeline doesn't run when scheduled: