Splunk Core Certified User Practice Exam

What are the five data bucket ages in Splunk?

1. Hot, warm, cold, frozen, archived

2. Hot, warm, cold, frozen, thawed

3. Raw, warm, cold, deleted, archived

4. Live, old, archived, frozen, removed

The correct answer is: Hot, warm, cold, frozen, thawed

The correct choice highlights the five data bucket ages used in Splunk: hot, warm, cold, frozen, and thawed. In Splunk's architecture, data is ingested and categorized into these five stages. Initially, data is placed into the "hot" bucket, where it is actively written and indexed. As the data ages and becomes less frequently accessed, it transitions into the "warm" bucket, and then further into "cold" storage, where access is less frequent, but the data is still available for searches. "Frozen" data refers to the point at which Splunk removes data from its indexes, effectively making it no longer searchable. However, it can be preserved in a backup or alternative storage to adhere to retention policies. "Thawed" data refers to data that has been previously frozen but has now been restored to a searchable state. This progression of data storage ensures efficient resource management and provides flexibility in handling data retention and archiving policies. Understanding these bucket levels is crucial for effective Splunk management and optimizing both search performance and storage costs.