Splunk Fundamentals 1 Practice Exam

What are the five stages of Splunk data bucket aging from most current to oldest?

1. Hot, warm, cold, frozen, thawed

2. Real-time, warm, cold, archival, deleted

3. Current, past, archived, deleted, restored

4. Active, passive, archived, deleted, recovered

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

The five stages of Splunk data bucket aging, ordered from the most current to the oldest, are indeed hot, warm, cold, frozen, and thawed. In this system, data begins in the hot state, where it is actively being ingested and is readily available for searching. Once the active indexing of data slows down or ceases, this data transitions to the warm stage. Warm buckets still allow for efficient searching, but they are stored in a less expensive manner than hot data. As data ages further, it moves into the cold bucket, where it is stored on disk and can be searched but may incur a slight delay in access compared to warm data. After a certain retention period, data in the cold state is moved to the frozen state. In this stage, data is often either deleted or archived depending on the organization's data retention policies. However, even in the frozen state, there is the possibility to restore it to a thawed state if it needs to be accessed later. This sequence highlights how Splunk optimizes storage based on the age and access frequency of data, ensuring efficient resource management and maintaining performance for actively used datasets. Other options provided do not accurately represent the states in Splunk's lifecycle management of data.