The Performance page provides graphs and tables of data that enable you to assess the storage array's performance in several key areas.
Performance functions allow you to accomplish these tasks:
- View performance data in near real-time to help you determine whether a storage array is experiencing problems.
- Export performance data to construct a historical view of a storage array and identify when a problem started or what caused a problem.
- Select the objects, performance metrics, and time frame you want to view.
- Compare metrics.
You can view performance data in three formats:
- Real-time graphical
– Plots performance data on a graph in near real-time.
- Near real-time tabular
– Lists performance data in a table in near real-time.
- Exported CSV file – Allows you to save tabular performance data in a file of comma-separated values for further viewing and analysis.
Characteristics of performance data formats
Type of performance monitoring |
Sampling interval |
Length of time displayed |
Maximum number of objects displayed |
Ability to save data |
Real-time graphical, live
Real-time graphical, historical
|
10 sec (live)
5 min (historical)
Data points shown depend on selected time frame
|
Default time frame is 1 hour.
Choices: - 5 minutes
- 1 hour
- 8 hours
- 1 day
- 7 days
- 30 days
|
5 |
No |
Near real-time tabular (table view) |
10 sec -1 hr |
Most current value |
Unlimited |
Yes |
Comma-separated values (CSV) file |
Depends on selected time frame |
Depends on selected time frame |
Unlimited |
Yes |
Guidelines for viewing performance data
- Performance data collection is always on. There is no option to turn it off.
- Each time the sampling interval elapses, the storage array is queried and the data is updated.
- For graphical data, the 5-minute time frame supports 10-second updating averaged over 5 minutes. All other time frames are updated every 5 minutes, averaged over the selected time frame.
- Performance data in the graphical views is updated in real time. Performance data in the table view is updated in near real time.
- If a monitored object changes during the time data is collected, the object might not have a complete set of data points spanning the selected time frame. For example, volume sets can change as volumes are created, deleted, assigned, or unassigned; or drives can be added, removed, or failed.