Pass the Pure Storage FlashBlade Architect Professional FAAA_004 Questions and answers with ExamsMirror

TheEvergreen//Flexoffering allows customers toown their array hardwarewhile paying for storage on asubscription basis.

Why This Matters:

Evergreen//Flex:

This model combines the benefits of ownership with the flexibility of a subscription. Customers own the hardware outright but pay for storage capacity and services (e.g., maintenance, upgrades) on a subscription basis.

It provides predictable costs and access to Pure Storage's Evergreen architecture, ensuring long-term value and future-proofing.

Why Not the Other Options?

A. Evergreen//Foundation:

Evergreen//Foundation is a traditional purchase model where customers buy the hardware and software upfront. It does not involve a subscription-based payment structure.

B. Evergreen//One:

Evergreen//One is a fully managed subscription service where customers do not own the hardware. Instead, they lease the equipment and pay for storage as a service.

D. Cloud Block Store:

Cloud Block Store is a cloud-native block storage solution that runs in public clouds (e.g., AWS, Azure). It does not involve owning on-premises hardware.

Key Points:

Ownership:Customers retain ownership of the hardware.

Subscription Flexibility:Pay for storage and services on a subscription basis.

Predictable Costs:Aligns with budgeting and financial planning goals.

References:

Pure Storage Evergreen//Forever Documentation: "Understanding Evergreen//Flex"

Pure Storage Whitepaper: "Maximizing Value with Evergreen Subscriptions"

Pure Storage Knowledge Base: "How Evergreen//Flex Works"

The Pure Storage offering that can be deployed inAWSisCloud Block Store.

Why This Matters:

Cloud Block Store:

Cloud Block Store is acloud-native block storage solutionthat runs in public clouds like AWS and Azure.

It provides enterprise-grade storage features, including deduplication, compression, and thin provisioning, while seamlessly integrating with on-premises FlashArray environments.

Why Not the Other Options?

A. ObjectEngine:

ObjectEngine is a backup and recovery solution designed for rapid restores and backups. It is not a storage solution that can be deployed in AWS.

C. CloudSnap:

CloudSnap is a feature that offloads snapshots to cloud storage (e.g., AWS S3 or Azure Blob). It is not a standalone storage solution but rather a feature of FlashArray.

Key Points:

Cloud Block Store:Provides block storage in AWS with enterprise-grade features.

Integration:Seamlessly integrates with on-premises FlashArray environments for hybrid cloud architectures.

Scalability:Enables scalable and cost-effective storage in the cloud.

References:

Pure Storage Cloud Block Store Documentation: "Deploying Cloud Block Store in AWS"

Pure Storage Whitepaper: "Hybrid Cloud Architectures with FlashArray and Cloud Block Store"

Pure Storage Knowledge Base: "Cloud Block Store Use Cases and Deployment"

For anActiveCluster solution with Uniform Configuration, the architect should recommenddual connections from each controller through two fabricsto ensure high availability and redundancy in Fibre Channel connectivity.

Why This Matters:

Dual Connections:

Each controller should have dual connections to provide redundancy and fault tolerance. If one connection fails, the other ensures uninterrupted communication between the host and the array.

Two Fabrics:

Using two independent Fibre Channel fabrics (e.g., Fabric A and Fabric B) ensures that there is no single point of failure in the network infrastructure. This aligns with best practices for ActiveCluster deployments.

Why Not the Other Options?

B. A single connection from each controller through two fabrics:

A single connection per controller does not provide sufficient redundancy. If the connection fails, the host may lose access to the array.

C. Crossed connections from each controller through a single fabric:

Using a single fabric introduces a single point of failure. Additionally, "crossed connections" are not a standard or recommended configuration for ActiveCluster.

D. A single connection from each controller through a single fabric:

This configuration lacks both redundancy at the connection level and at the fabric level, making it highly vulnerable to failures.

Key Points:

Redundancy:Dual connections and two fabrics ensure fault tolerance and high availability.

Best Practices:Aligns with Pure Storage's recommendations for ActiveCluster deployments.

Uniform Configuration:Ensures consistent and reliable connectivity across all hosts in the cluster.

References:

Pure Storage FlashArray Documentation: "ActiveCluster Best Practices for Fibre Channel Connectivity"

Pure Storage Whitepaper: "Designing High-Availability Solutions with ActiveCluster"

Pure Storage Knowledge Base: "Configuring Host Connections for ActiveCluster"

The value 77.24 T in the context of Pure Storage FlashArray represents C. The guaranteed capacity.

Guaranteed Capacity is a feature of Pure Storage’s Evergreen subscription model. It reflects the effective capacity Pure Storage commits to the customer based on their typical data reduction ratios (deduplication, compression, and pattern removal). This value is calculated as:

Guaranteed Capacity=Physical Raw Capacity×Data Reduction Factor (DRF)Guaranteed Capacity=Physical Raw Capacity×Data Reduction Factor (DRF)

Pure typically guarantees a minimum DRF (e.g., 3:1 for many workloads), but actual savings often exceed this.

Why Not the Other Options?

A. Total usable space: This would include the total logical capacity after data reduction and overheads (RAID-HD, metadata), which is usually larger than the guaranteed capacity.

B. Total raw space: This refers to the physical capacity of drives (e.g., 100TB raw). The value shown (77.24T) is smaller than raw, so this is incorrect.

D. Total deduplicated space: Pure Storage combines dedupe, compression, and pattern removal into a single "data reduction" metric. Deduplication alone is not isolated in capacity reporting.

Official Reference:

Pure Storage documentation explicitly defines Guaranteed Capacity as the "logical capacity Pure commits to deliver, factoring in data reduction." This aligns with the Evergreen//Forever subscription model, where customers pay for usable capacity, not raw storage.

The customer is looking for a storage system that supports20 TB of file shares,800 TB of workloads, has alow cost per GB, and can utilizeCloudSnapin the future. The best recommendation isFlashArray//C.

Why This Matters:

FlashArray//C:

FlashArray//C is designed forcapacity-optimized workloads, making it ideal for use cases requiring large amounts of storage at a lower cost per GB compared to higher-performance arrays like FlashArray//X.

It supportsQLC flash technology, which provides high density and cost efficiency for less performance-intensive workloads.

CloudSnap is fully supported on FlashArray//C, enabling snapshots to be offloaded to public cloud storage for disaster recovery or archival purposes.

Why Not the Other Options?

A. FlashArray//X:

FlashArray//X is optimized for high-performance workloads, such as databases and mission-critical applications. While it supports CloudSnap, it is more expensive and not the most cost-effective solution for large-scale capacity needs.

C. Cloud Block Store:

Cloud Block Store is a cloud-native block storage solution that runs in public clouds (e.g., AWS, Azure). It does not meet the requirement for on-premises storage with file shares and CloudSnap utilization.

D. FlashBlade//S:

FlashBlade//S is designed for file and object storage but is typically used for high-performance, unstructured data workloads. It is more expensive than FlashArray//C and not necessary for this use case.

Key Points:

FlashArray//C:Provides high-density storage at a low cost per GB, ideal for large-scale workloads.

CloudSnap Support:Enables offloading snapshots to the cloud for disaster recovery or archival purposes.

Cost Efficiency:Balances performance and cost, making it suitable for file shares and large datasets.

References:

Pure Storage FlashArray//C Documentation: "Use Cases for FlashArray//C"

Pure Storage Whitepaper: "Optimizing Storage Costs with FlashArray//C"

Pure Storage Knowledge Base: "Choosing the Right FlashArray Model for Your Workload"

SE should recommend adding the 10 TB test/dev workload to the array while advising the admin to monitor performance and capacity. This recommendation assumes that the array has sufficient resources (e.g., available capacity, performance headroom) to handle the additional workload without requiring immediate upgrades or changes.

Why This Matters:

Current Array Capacity and Performance:

Pure Storage FlashArray is designed to efficiently handle workloads with advanced data reduction techniques (deduplication, compression, etc.) and high-performance NVMe storage.

If the array has sufficient unused capacity and performance headroom, adding a 10 TB test/dev workload is feasible without requiring hardware upgrades.

Monitoring:

After adding the workload, it is critical to monitor bothperformance metrics(e.g., latency, IOPS, throughput) andcapacity utilizationto ensure the array continues to meet SLAs and does not exceed its limits.

Why Not the Other Options?

A. Upgrade the controller to an //X90R3 to handle the additional workload:

Upgrading the controller is unnecessary unless the current controller is nearing its performance limits. Test/dev workloads are typically less demanding than production workloads, so this step would likely be premature.

B. Add more DirectFlash NVMe modules to the expansion shelf to handle the additional capacity:

Adding more NVMe modules is only necessary if the array is running out of physical capacity. If the array already has sufficient capacity, this step is not required.

C. Upgrade the 22 TB DirectFlash NVMe modules to a higher capacity to handle the additional workload:

Upgrading the NVMe modules to higher-capacity ones is a significant investment and is only justified if the array is consistently running out of capacity. For a 10 TB workload, this step is likely excessive.

Key Points:

Feasibility of Adding Workload:The array can likely handle the additional 10 TB workload without immediate upgrades.

Monitoring:Continuous monitoring ensures that performance and capacity remain within acceptable limits.

Cost Efficiency:Avoiding unnecessary upgrades or changes helps optimize costs while meeting the customer's needs.

References:

Pure Storage FlashArray Documentation: "Capacity Planning and Workload Sizing"

Pure Storage Whitepaper: "Best Practices for Managing Test/Dev Workloads"

Pure Storage Knowledge Base: "Adding Workloads to FlashArray Without Disruption"

The customer has the following requirements:

Business-critical workload that requires sub-millisecond response times

Synchronous replication configured to their secondary site

Offload snapshots to a third location where they do not have a FlashArray

The best solution to meet these needs isFlashArray//Xs with ActiveCluster and CloudSnap.

Why This Matters:

FlashArray//Xs:

FlashArray//X is optimized forhigh-performance workloads, delivering sub-millisecond response times required for business-critical applications.

ActiveCluster:

ActiveCluster providessynchronous replicationbetween two sites within a stretched cluster, ensuring zero RPO and near-zero RTO for high availability.

CloudSnap:

CloudSnap offloads snapshots to cloud storage (e.g., AWS S3 or Azure Blob), enabling disaster recovery or archival at a third location without requiring an additional FlashArray.

Why Not the Other Options?

B. FlashArray//Cs with ActiveDR and Snapshot Replication:

FlashArray//C is designed for capacity-optimized workloads and does not provide the sub-millisecond response times required for business-critical applications.

ActiveDR provides asynchronous replication, which does not meet the requirement for synchronous replication.

C. FlashArray//Cs with ActiveCluster and Snapshot Replication:

Again, FlashArray//C is not suitable for sub-millisecond response times. Additionally, snapshot replication to a third location is less efficient than CloudSnap for offloading data to the cloud.

Key Points:

FlashArray//Xs:Delivers the high performance required for business-critical workloads.

ActiveCluster:Ensures synchronous replication for high availability across two sites.

CloudSnap:Provides cost-effective offsite protection by offloading snapshots to the cloud.

References:

Pure Storage FlashArray Documentation: "ActiveCluster with CloudSnap"

Pure Storage Whitepaper: "Disaster Recovery Strategies with FlashArray"

Pure Storage Knowledge Base: "Using Protection Groups in Stretched Pods"

Thefastest way to duplicate volume data for a test/dev environmentis tomount the snapshot to a development host. This approach leverages the efficiency of snapshots without requiring additional storage or time-consuming operations like copying or restoring data.

Why This Matters:

Snapshots:

Snapshots are space-efficient, point-in-time copies of a volume that do not consume additional storage until changes are made to the original data.

Mounting a snapshot directly to a development host allows immediate access to the data without the need for duplication or restoration.

Speed and Efficiency:

Mounting a snapshot is significantly faster than creating a full copy or restoring from a backup, as it avoids the overhead of data movement or replication.

Why Not the Other Options?

A. Use a backup copy:

Restoring data from a backup is time-consuming and requires additional storage. It is not the fastest method for duplicating data.

B. Make a volume copy:

Creating a full volume copy consumes additional storage and takes longer than mounting a snapshot.

C. Restore from a volume snapshot:

Restoring from a snapshot involves writing data back to the original volume, which is slower than simply mounting the snapshot for read-only or writable access.

Key Points:

Snapshots:Provide fast, space-efficient access to data for test/dev environments.

Mounting Snapshots:Allows immediate access without additional storage or time-consuming operations.

Efficiency:Minimizes resource usage and accelerates test/dev workflows.

References:

Pure Storage FlashArray Documentation: "Using Snapshots for Test/Dev Environments"

Pure Storage Whitepaper: "Best Practices for Managing Test/Dev Workloads"

Pure Storage Knowledge Base: "Mounting Snapshots to Hosts"

TheDirectCompress Accelerator (DCA)is a hardware component introduced in certain FlashArray models to enhance inline data compression performance. To determine the minimally required FlashArray model that includes DCA, let's analyze the options:

Analysis of Options:

A. FlashArray//X70 R4:

TheFlashArray//X70 R4was the first model to include the DirectCompress Accelerator (DCA).

This makes it the minimally required model for DCA support.

B. FlashArray//X70 R3:

TheFlashArray//X70 R3does not include the DCA. It relies on software-based compression, which is less efficient than hardware-accelerated compression.

C. FlashArray//X90 R4:

TheFlashArray//X90 R4includes DCA but is a higher-tier model than the X70 R4. While it supports DCA, it is not the minimal requirement.

D. FlashArray//XL130:

TheFlashArray//XL130is a high-performance model that includes DCA, but it is overkill for this requirement and not the minimal model.

Recommendation:

The correct answer isA. FlashArray//X70 R4, as it is the first model to include the DirectCompress Accelerator (DCA).

References:

FlashArray Hardware Specifications:

FlashArray Models

Details the features and capabilities of each FlashArray model.

DirectCompress Accelerator Overview:

DirectCompress Accelerator

Explains the benefits and availability of DCA.

If a customer notices alow data reduction ratioupon initial data ingest, thePurity data reduction techniquethat will help increase the data reduction ratio over time isdeep deduplication and deep compression.

Why This Matters:

Deep Deduplication and Deep Compression:

Purity//FA (the operating system for FlashArray) appliesdeduplicationto eliminate duplicate data blocks andcompressionto reduce the size of unique data blocks.

These techniques are applied continuously as new data is written to the array. Over time, as more data is ingested and patterns emerge, the effectiveness of deduplication and compression increases, leading to a higher data reduction ratio.

For example, deduplication becomes more effective as the dataset grows and more duplicates are identified. Similarly, compression benefits from identifying repetitive patterns in larger datasets.

Why Not the Other Options?

B. Snapshot cleanup and garbage collection:

Snapshot cleanup and garbage collection are maintenance processes that reclaim space from deleted snapshots or unused data blocks. While these processes free up space, they do not directly contribute to increasing the data reduction ratio.

C. Capacity consolidation and cloning:

Capacity consolidation refers to combining workloads onto fewer arrays, and cloning creates space-efficient copies of volumes. While cloning leverages data reduction techniques, it does not inherently improve the overall data reduction ratio for existing data.

D. RAID-HA protection and AES-256 encryption:

RAID-HA (high availability) ensures data redundancy, and AES-256 encryption secures data. Neither of these features impacts the data reduction ratio.

Key Points:

Deep Deduplication and Compression:Continuously optimize storage efficiency as more data is ingested.

Data Reduction Ratio:Improves over time as deduplication identifies duplicates and compression reduces unique data.

Purity//FA Automation:These techniques are fully automated and do not require manual intervention.

References:

Pure Storage FlashArray Documentation: "Understanding Data Reduction in Purity//FA"

Pure Storage Whitepaper: "Maximizing Data Reduction with FlashArray"

Pure Storage Knowledge Base: "How Deduplication and Compression Work in FlashArray"