What increases when implementing multiple pipeline sets in a Splunk environment?

When implementing multiple pipeline sets in a Splunk environment, forwarder throughput increases because multiple pipeline sets allow for the simultaneous processing of data. This results in enhanced data ingestion capabilities, as each pipeline can handle a portion of the incoming data stream concurrently. By distributing the workload across multiple pipelines, the overall throughput of data being forwarded can improve significantly, enabling the system to handle larger volumes of data more efficiently.

This increase in forwarder throughput is particularly beneficial in environments where high data volumes need to be processed swiftly, such as in large enterprises or during peak data influx periods. By maximizing the resources of the forwarders and utilizing multiple pipelines, the system can ensure that data is ingested without bottlenecks, leading to better performance and faster availability of indexed data in Splunk.

In contrast, while multiple pipeline sets provide various benefits, they may indeed add complexity to system administration, but the primary focus of the question centers on throughput improvements.