Splunk Enterprise Certified Architect Practice Test 2025 - Free Splunk Practice Questions and Study Guide

Implementing data expiration policies is considered a recommended practice for Splunk indexers because it allows organizations to manage their storage resources efficiently by automatically deleting or archiving older data that is no longer needed for operational or analytical purposes. This practice helps in optimizing performance and reducing costs associated with data storage.

By setting appropriate expiration policies, you can ensure that your indexers do not become overwhelmed with unnecessary data, which can lead to degraded performance. It also enables compliance with data governance policies by ensuring that data is retained only as long as necessary and is disposed of securely at the end of its lifecycle.

The other choices suggest approaches that could lead to inefficient data management. For instance, indexing all data indefinitely can result in excessive storage use and performance issues. Using a single data index for all types of data may complicate data retrieval and management, and storing all data in cold storage may impede quick access to data that may still be relevant. Each of these approaches lacks the strategic structure that expiration policies provide, emphasizing the importance of having a well-defined data retention strategy.