In your environment, ephemeral storage is configured for temporary data used by a critical analytics application. The results are transferred to persistent storage. The ephemeral storage is due for removal. Which approach best addresses the removal of these short-lived volumes while preserving the final results?
Check that the final data is properly stored, then remove any unneeded short-lived capacity from automation and resource definitions
Convert short-lived capacity to the same storage class used for final results to align with existing storage practices
Maintain these volumes temporarily until confirming all data is properly transferred
Keep short-lived and permanent capacity active simultaneously until data transfer is complete
Verifying that important results are in more permanent locations, then removing unneeded short-lived segments, reduces resource bloat and potential data leaks. Extending the lifespan of ephemeral storage wastes capacity and goes against recommended lifecycle methods. Moving short-lived capacity to a class used for permanent data adds control overhead. Keeping both capacities active could lead to confusion over when volumes are safe to remove.
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What is ephemeral storage?
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What is the difference between ephemeral and persistent storage?
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Why is it important to verify data transfer before removing ephemeral volumes?