What method can enhance search performance in Splunk?

Utilizing indexed fields is a highly effective method for enhancing search performance in Splunk. When data is indexed, Splunk creates summaries of the data that allow it to retrieve relevant information quickly. Indexed fields are pre-defined fields created at the time of indexing, which significantly reduce the amount of data that needs to be searched through during queries.

When a search query utilizes indexed fields, Splunk can filter and access relevant data much faster than if it had to analyze all unindexed data or perform full-text searches. This leads to improvements in both search speed and efficiency, as the system can utilize the structured data embedded within the indexed fields for more precise querying.

In contrast, using wildcard characters in queries can slow down search performance because they can lead to broader searches that require Splunk to review more data than necessary. Running all searches at once can lead to resource contention and possibly overwhelm the system, while ignoring data retention policies can cause an accumulation of excessive data that hinders performance due to an overloaded index. Hence, indexed fields stand out as the most appropriate method to enhance search performance in Splunk.