Pure Storage FAAA_004 問題集 練習問題・模擬試験｜日本語版＆英語版対応

Explanation: To calculate the additional capacity required for the SQL workload on the FlashArray, we need to account for the Data Reduction Ratio (DRR). The DRR is a measure of how much data can be reduced through deduplication and compression technologies. In this case, the expected DRR for the SQL workload is 3.85. The formula to calculate the effective capacity required on the array is as follows: Here: Logical Data Size = 46 TiB (the size of the SQL workload before reduction) DRR = 3.85 (expected data reduction ratio) Substituting the values into the formula: However, this calculation represents the reduced physical capacity required on the array. Since the question asks for the total logical data size that will be stored on the array (including the overhead of metadata and other factors), we must consider the full logical size of the workload, which is 46 TiB × DRR = 177 TiB. Thus, the SQL workload will take up 177 TiB of logical space on the array. Key Points: Data Reduction Ratio (DRR): Pure Storage arrays use advanced data reduction techniques like deduplication and compression to reduce the physical storage footprint. However, the logical size of the workload remains unchanged. Logical vs. Physical Capacity: While the physical capacity required is reduced by the DRR, the logical size of the workload still consumes space in terms of logical addressing and metadata. Reference: Pure Storage FlashArray//X Documentation: "Understanding Data Reduction and Capacity Planning" Pure Storage Best Practices Guide: "Capacity Management and Workload Sizing" Pure1 Support Portal: Knowledge Base Articles on DRR and Logical Capacity Calculation

Explanation: The customer has a cloud-first strategy and does not wish to own additional capital assets, meaning they are looking for a solution that operates entirely within the public cloud without requiring on-premises hardware. Additionally, their primary goal is to reduce cloud storage costs while managing a large volume of database data (100 TB). Cloud Block Store (CBS) is the ideal solution for this requirement. CBS is a software-defined block storage solution that runs natively in the public cloud (e.g., AWS or Azure). It provides enterprise-grade storage features like deduplication, compression, and thin provisioning, which help optimize storage usage and reduce costs. By leveraging CBS, the customer can efficiently manage their database workloads in the cloud while minimizing storage expenses. Why Not the Other Options? A. Evergreen//Flex: This is a subscription-based model for on-premises FlashArray hardware. Since the customer does not want to own any additional capital assets, this option does not align with their cloud-first strategy. B. Evergreen//Forever: Similar to Evergreen//Flex, this is an on-premises solution that involves hardware ownership, which does not meet the customer's requirements. D. Portworx DBaaS: While Portworx is a containerized storage solution for databases, it is primarily designed for Kubernetes environments and does not directly address the need to reduce cloud storage costs for traditional database workloads. Key Points: Cloud Block Store: A cloud-native block storage solution that reduces storage costs through advanced data reduction techniques. Cloud-First Strategy: CBS aligns perfectly with the customer's desire to avoid capital expenditures and operate entirely within the public cloud. Reference: Pure Storage Cloud Block Store Documentation: "Deploying and Managing Cloud Block Store in Azure" Pure Storage Whitepaper: "Optimizing Cloud Costs with Cloud Block Store" Pure Storage Best Practices Guide: "Database Workloads in the Public Cloud"

Explanation: The customer requires a disaster recovery (DR) solution that allows them to replicate data from their on-premises environment to the public cloud. They also need failover and fallback capabilities, meaning they must be able to switch operations to the cloud during a disaster and revert back to on-premises once the issue is resolved. Snapshot replication between a FlashArray on-premises and Cloud Block Store (CBS) is the best solution for this use case. CBS integrates seamlessly with on-premises FlashArrays, enabling efficient replication of snapshots to the cloud. This feature supports failover and fallback operations, ensuring business continuity in the event of a disaster. Why Not the Other Options? B. Purity//FA CloudSnap periodic offload of snapshots to AWS: While CloudSnap allows periodic offloading of snapshots to AWS S3 for backup purposes, it does not provide the real-time replication and failover/fallback capabilities required for DR. C. ActiveCluster FC replication between a FlashArray on site and Evergreen//One: ActiveCluster is designed for synchronous replication between two FlashArrays in different locations, but it does not support replication to the public cloud. Key Points: Snapshot Replication: Enables efficient and reliable replication of data between on-premises FlashArrays and Cloud Block Store. Failover and Fallback: CBS supports these capabilities, ensuring minimal downtime during a disaster. Integration with FlashArray: CBS is specifically designed to work with FlashArray, providing a seamless DR solution. Reference: Pure Storage Cloud Block Store Documentation: "Disaster Recovery with Cloud Block Store" Pure Storage Best Practices Guide: "Replication and Failover in Hybrid Cloud Environments" Pure Storage Whitepaper: "Hybrid Cloud Architectures with FlashArray and Cloud Block Store"