Variables that impact product performance
Product performance is impacted by various factors, depending on your deployment size and scale. You can use the following information as a high-level guide for understanding the factors that can impact your deployment sizing and the approximate impact they are likely to have on product performance.
The following table lists the variables that can impact the product performance along with the levels of impact to each of the system resources.
Variables that impact product performance
| Variable | Impact on resources | ||||
|---|---|---|---|---|---|
| Processor1 | Memory2 | Storage3 | I/O4 | Comments | |
| Number of data collectors | Medium | Low | Medium | Medium | |
| Retention period | None | Medium | High | Low | |
| Number of tags defined for the data collectors | Medium | Low | Medium | Low | |
| Number of fields added to the Fields section available under the Filters panel on the Search tab. | High | None | None | Low | |
| Number of fields specified in data patterns | Low | None | Medium | None | |
| Number of unique field values in the Fields section available under the Filters panel on the Search tab. | Low | High | High | High | |
| Volume of data indexed per day | High | Low | High | High | |
| Number of managed hosts | Medium | Low | Low | Low | The Anomaly baseline job that is enabled is a function of the number of hosts. |
| Simple search commands (Search commands with nontabular output) | Low | Low | None | Low | |
| Advanced search commands ( timechart, stats, top, rare, and group) | Medium | Medium | None | Medium | Requires high CPU utilization by the Indexer and Search components. Avoid using high cardinality fields (fields with large number of unique values) in the |
| Number of concurrent users | High | High | None | High | If a large number of users are executing concurrent searches or loading dashboards, or if there are too many notifications set up for execution, you might find that your system has become too slow. If you execute a search string processing a large amount of search results and while it still processing the results, if you found what you were looking for, you can pause or stop the search from executing further results. For more information about pausing or stopping a search, see Getting started with search. |
| Number of notification alerts | Low | Low | None | Low | Notification alerts are meant for shorter time period searches. |
| Number of notification reports | Low | Low | None | Low | Notification reports are expected to range for medium time period searches. |
| Number of dashboards and dashlets | Medium | Medium | None | Medium | Performance overhead of a dashlet is the same as that of a manual run of the saved search used for creating the dashlet. |
| Anomaly Detection | High | Low | Medium | Medium | Impacts both Search and Indexer components |
| Indexer redundancy | Medium | Low | High | Medium | |
1 Processor utilization (CPU)
2 Memory utilization (RAM)
3 Storage utilization (disk space)
4 I/O transfer rate (disk read/write rate)
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