FAAA_004 Free Learning Cram, FAAA_004 Exam Answers
FAAA_004 Free Learning Cram, FAAA_004 Exam Answers
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Pure Storage FAAA_004 Exam Syllabus Topics:
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Pure Storage FlashArray Architect Associate Sample Questions (Q10-Q15):
NEW QUESTION # 10
Which Pure Storage offering allows customers to own their array hardware while paying for storage on a subscription basis?
- A. Evergreen//One
- B. Evergreen//Flex
- C. Cloud Block Store
- D. Evergreen//Foundation
Answer: B
Explanation:
The Evergreen//Flex offering allows customers to own their array hardware while paying for storage on a subscription 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.
Reference:
Pure Storage Evergreen//Forever Documentation: "Understanding Evergreen//Flex" Pure Storage Whitepaper: "Maximizing Value with Evergreen Subscriptions" Pure Storage Knowledge Base: "How Evergreen//Flex Works"
NEW QUESTION # 11
Which FlashArray feature allows snapshots to be sent to a public cloud target?
- A. ActiveCluster
- B. Cloud Block Store
- C. CloudSnap
Answer: C
Explanation:
The FlashArray feature that allows snapshots to be sent to a public cloud target is CloudSnap .
Why This Matters:
CloudSnap:
CloudSnap is a feature that offloads snapshots to cloud storage providers like AWS S3 or Azure Blob.
It provides a cost-effective and scalable solution for storing backups or archival data in the cloud, ensuring offsite protection and long-term retention.
Public Cloud Integration:
By leveraging public cloud storage, customers can reduce on-premises storage costs while maintaining secure and accessible backups.
Why Not the Other Options?
A . 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 sending snapshots to a public cloud target.
C . ActiveCluster:
ActiveCluster provides synchronous replication between two sites for high availability. It does not involve offloading snapshots to the cloud.
Key Points:
CloudSnap: Offloads snapshots to public cloud storage for cost-effective and scalable backups.
Offsite Protection: Ensures data is securely stored in the cloud for disaster recovery or archival purposes.
Integration: Seamlessly integrates with popular cloud providers like AWS and Azure.
Reference:
Pure Storage FlashArray Documentation: "CloudSnap for Offsite Backups"
Pure Storage Whitepaper: "Cost-Effective Backup Strategies with FlashArray" Pure Storage Knowledge Base: "Using CloudSnap to Offload Snapshots"
NEW QUESTION # 12
A customer wants to add capacity to support a new Oracle workload. It has been determined that the application needs 398 TB of thick-provisioned storage from the host. The customer wants to purchase the minimum storage capacity to handle this workload.
How much capacity should the SE propose, assuming DRR is 3:1?
- A. 132 TB
- B. 21TB
- C. 186 TB
- D. 62 TB
Answer: A
Explanation:
To calculate the minimum storage capacity required to handle the Oracle workload, we need to account for the thick-provisioned storage requirement and the expected data reduction ratio (DRR).
Step-by-Step Calculation:
Logical Storage Requirement :
The application requires 398 TB of thick-provisioned storage from the host.
Data Reduction Ratio (DRR) :
The DRR is 3:1 , meaning the physical storage required is:
Recommendation :
The SE should propose 132 TB of physical storage, as it meets the requirement after accounting for data reduction.
Final Recommendation:
The correct answer is A. 132 TB .
Reference:
Capacity Planning Guide :
Pure Storage Capacity Planning
Provides guidance on calculating usable capacity based on data reduction ratios.
Thick vs. Thin Provisioning :
Provisioning Best Practices
Explains the differences between thick and thin provisioning.
NEW QUESTION # 13
A controller receives a write request.
If it generates a hash that is already recorded in the hash table, what happens next?
- A. The new block is compared to the existing block to confirm they are duplicates.
- B. The next incoming block is then hashed to see if it can be deduplicated.
- C. Deep level compression is then applied to the newly hashed block.
- D. Purity//FA will expand the block to see if it can deduplicate a larger dataset.
Answer: A
Explanation:
When a controller generates a hash for an incoming write request and finds that the hash already exists in the hash table, the next step is to compare the new block to the existing block to confirm they are duplicates .
Why This Matters:
Hash Collision Handling:
Hash functions can sometimes produce the same hash value for different data blocks (a "hash collision"). To ensure data integrity, the system must verify that the new block is identical to the existing block before deduplication occurs.
Data Integrity:
Comparing the blocks ensures that only true duplicates are deduplicated, preventing data corruption or loss due to hash collisions.
Why Not the Other Options?
A . The next incoming block is then hashed to see if it can be deduplicated:
Hashing the next block is unnecessary at this stage. The focus is on verifying whether the current block is a duplicate.
B . Deep level compression is then applied to the newly hashed block:
Compression is a separate process from deduplication and does not occur immediately after hashing.
D . Purity//FA will expand the block to see if it can deduplicate a larger dataset:
Expanding the block is not part of the deduplication process. Deduplication operates on individual blocks, not larger datasets.
Key Points:
Hash Table Lookup: Identifies potential duplicates based on hash values.
Block Comparison: Confirms that the new block matches the existing block to ensure data integrity.
Deduplication: Eliminates redundant data to optimize storage efficiency.
Reference:
Pure Storage FlashArray Documentation: "Understanding Deduplication in Purity//FA" Pure Storage Whitepaper: "Data Reduction Techniques in FlashArray" Pure Storage Knowledge Base: "How Deduplication Works in FlashArray"
NEW QUESTION # 14
A customer has presented two workloads that need to be replicated. One is a highly transactional database workload and the other is a VM datastore with tier one applications.
The customer has the following requirements:
* The database workload is highly reliant on storage performance The VM datastore requires zero downtime.
* The customer has advised the two FlashArrays will be 20 miles apart and they are worried that this could impact their internal SLAs.
What replication strategies should be advised for these workloads?
- A. ActiveDR should be used for both workloads.
- B. ActiveCluster should be used for the VM workloads and ActiveDR for the database workload.
- C. ActiveDR should be used for the VM workloads and ActiveCluster for the database workload.
- D. ActiveCluster should be used for both workloads.
Answer: B
Explanation:
To address the customer's requirements, we need to evaluate the replication strategies offered by Pure Storage FlashArray: ActiveCluster and ActiveDR , and how they align with the specific needs of the two workloads.
Workload Analysis:
Transactional Database Workload :
This workload is highly reliant on storage performance. Any replication strategy must ensure minimal latency and high availability to avoid impacting transactional throughput and response times.
The database workload typically benefits from synchronous replication to maintain consistency and performance across sites.
VM Datastore (Tier 1 Applications) :
This workload requires zero downtime, meaning it must remain accessible even in the event of a site failure. High availability and seamless failover are critical.
The VM datastore can tolerate some level of asynchronous replication as long as it does not compromise availability or recovery objectives.
Replication Strategies:
ActiveCluster :
ActiveCluster is a synchronous replication solution that provides active-active high availability across two FlashArrays. It ensures zero RPO (Recovery Point Objective) and zero RTO (Recovery Time Objective), making it ideal for workloads requiring continuous availability and zero downtime.
ActiveCluster is well-suited for the VM datastore workload because it guarantees seamless failover and high availability, meeting the zero-downtime requirement.
ActiveDR :
ActiveDR is an asynchronous replication solution designed for disaster recovery scenarios. It provides near-zero RPO (typically seconds to minutes) and allows for non-disruptive testing of failover scenarios.
ActiveDR is better suited for the transactional database workload because it minimizes the impact of latency over the 20-mile distance while still maintaining high performance and consistency.
Distance Consideration:
The 20-mile distance between the two FlashArrays introduces latency concerns. Synchronous replication (ActiveCluster) can handle this distance effectively for the VM datastore workload due to its tolerance for slightly higher latency. However, for the transactional database workload, the latency could degrade performance, making ActiveDR a better choice.
Final Recommendation:
Use ActiveCluster for the VM datastore workload to achieve zero downtime and high availability.
Use ActiveDR for the transactional database workload to balance performance and disaster recovery needs over the 20-mile distance.
Reference:
Pure Storage ActiveCluster Documentation :
Explains the synchronous replication capabilities and use cases for ActiveCluster.
Pure Storage ActiveCluster
Pure Storage ActiveDR Documentation :
Details the asynchronous replication features and disaster recovery use cases for ActiveDR.
Pure Storage ActiveDR
Pure Storage Best Practices for Replication :
Provides guidance on selecting the appropriate replication strategy based on workload requirements and distance considerations.
Pure Storage Replication Best Practices
Pure Storage Architectural Guides :
Covers architectural considerations for deploying ActiveCluster and ActiveDR in multi-site environments.
Pure Storage Architectural Guides
This approach ensures that both workloads meet their respective SLAs while addressing the customer's concerns about distance and performance.
NEW QUESTION # 15
......
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