Minimizing Cost of Azure Synapse Analytics Dedicated SQL Pool During Idle Times

Optimizing Cost for Azure Synapse Analytics Dedicated SQL Pool

Question

You have a dedicated SQL pool in Azure Synapse Analytics that is only used actively every night for eight hours.

You need to minimize the cost of the dedicated SQL pool as much as possible during idle times. The solution must ensure that the data remains intact.

What should you do on the dedicated SQL pool?

Answers

Explanations

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A. B. C. D.

B

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-manage-compute-overview

The best solution for minimizing the cost of the dedicated SQL pool in Azure Synapse Analytics during idle times while ensuring that the data remains intact is to pause the pool.

Option A, scaling down the data warehouse units (DWUs), reduces the cost of the pool, but it may not be the best solution in this case since the pool is only active for eight hours every night. If the pool is scaled down during idle times, it may take longer to process the data when it is active again, and this may negatively impact the performance of the pool.

Option C, creating a user-defined restore point, is not relevant to minimizing the cost of the pool during idle times. User-defined restore points are used for recovering data to a previous state in case of data loss or corruption, and they do not affect the cost of the pool.

Option D, deleting the pool, is not a viable solution since the pool is used every night for eight hours. Deleting the pool would result in the loss of data, and it would require creating a new pool from scratch, which would be time-consuming and costly.

Therefore, the best solution for minimizing the cost of the dedicated SQL pool in Azure Synapse Analytics during idle times while ensuring that the data remains intact is to pause the pool. Pausing the pool will stop the compute resources and suspend the billing for the pool until it is resumed. When the pool is resumed, it will pick up from where it left off, and the data will remain intact. This option is efficient and cost-effective since it allows for the temporary suspension of the compute resources when they are not needed, which reduces the cost of the pool.