True or False: Splunk Cloud Indexers utilize distributed data ingestion for efficient processing.

Splunk Cloud Indexers do indeed utilize distributed data ingestion, which allows for efficient processing of large volumes of data across multiple indexers. This distribution of workload helps to optimize performance, ensuring that data is ingested swiftly and effectively. By leveraging a distributed architecture, Splunk can manage significant amounts of incoming data seamlessly, allowing for scalability and improved reliability.

This inherent capability of distributing data ingestion is crucial for environments where data volume and speed are vital, such as in real-time analytics. The architecture is designed to ensure that data is processed in parallel, reducing bottlenecks and enhancing overall system throughput. As a result, the ability of Splunk Cloud Indexers to utilize this distributed approach is a fundamental aspect of its design and functionality.