Capacity is overloaded during the day by heavy background jobs. What is a sensible response?
Why B is the answer
Schedule heavy jobs for quieter hours
Spreading demand lowers peak use before you consider a larger capacity.
In detail
- Moving heavy jobs to quieter hours reduces peak load.
- Check for quiet hours in the metrics app first.
Use case
An illustrative scenario, not a real incident.
Heavy transformations run at noon, beside busy reports. Moving them to the evening lowers the daytime peak with no new spending.
See it in different ways
flowchart TD
A["Monitor hub"] --> B{"Which item failed?"}
B -->|"Pipeline"| C["Activity error output"]
B -->|"Notebook"| D["Spark logs"]
B -->|"Capacity pressure"| E["Capacity Metrics app"]mindmap
root((Monitoring))
Activities
Monitor hub
Capacity
Capacity Metrics app
Warehouse
Query insights
Spark
Logs
Copy step
Run detailsflowchart TD
Q{"Can heavy jobs wait?"}
Q -->|"Yes"| A0["Reschedule them"]
Q -->|"No"| A1["Consider a larger capacity"]Key point: Move heavy work before you scale up.
Why the other options are wrong
- A. Delete the semantic models
- Deleting models loses reports.
- C. Add more sensitivity labels to each item
- Labels have no effect on load.
- D. Disable all of the shortcuts
- Shortcuts are not the cause.