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Question 31 - D-PWF-DS-23 discussion

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An architect das configured a PowerFlex solution to use a tine granularity storage pool based on a customer's Initial request After validating the design against a LiveOptlcs output they modified the granularity of the configuration to medium What did the architect accomplish with this change'

A.
Improved performance
Answers
A.
Improved performance
B.
Belter distribution of data blocks
Answers
B.
Belter distribution of data blocks
C.
Increased effective capacity
Answers
C.
Increased effective capacity
Suggested answer: A

Explanation:

By changing the granularity of the PowerFlex storage pool from fine to medium, the architect improved the performance of the system. Medium Granularity (MG) storage pools are recommended for environments where I/O performance and low latency are critical, such as Virtual Desktop Infrastructure (VDI) deployments1.

Here's a detailed explanation of the change:

Fine Granularity (FG): FG storage pools are designed for space efficiency and enable features like inline compression, which can reduce the size of volume data depending on its compressibility. However, this can come at the cost of performance due to the overhead of compression and the smaller space allocation block size2.

Medium Granularity (MG): MG storage pools, on the other hand, provide supreme I/O performance with the least latency to virtual machines and applications. They use a larger space allocation block size of 1 MB, which is more efficient for I/O operations compared to the 4 KB block size used in FG storage pools1.

Performance Improvement: By switching to an MG storage pool, the architect ensured that the storage volumes provide better I/O performance and lower latency, which is essential for applications that require fast and responsive storage access1.

This change aligns with the best practices for PowerFlex storage provisioning, where the selection of granularity is based on the specific performance and space efficiency needs of the customer's workload1.

asked 16/09/2024
Latonya Ganison
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