What feature allows users to perform searches across multiple indexes?

The ability to perform searches across multiple indexes is primarily facilitated by Data Models. Data Models in Splunk are structured representations of data that help users build reports and perform searches on large datasets efficiently. They provide a way to define and extract relevant pieces of information from various underlying data sources, including multiple indexes, and present them in a unified format.

While other options may relate to searching capabilities, they serve different purposes. For instance, Search Head Clustering consolidates search requests to distribute workload but does not inherently merge data from multiple indexes in the same way that Data Models do. Distributed Search enables users to execute searches across different Splunk servers, but it is primarily about search architecture rather than data organization. Index Clustering pertains to data management, focusing on the replication and backup of indexed data, without necessarily simplifying cross-index searches.

By utilizing Data Models, users can effectively analyze data from various sources, leading to comprehensive insights across multiple indexes within their Splunk environment.