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NEW QUESTION # 51
An engineer is tasked by the IT security team to pull audit trail logs from the last month. The engineer navigates to the audit trail section of the FlashArray GUI, but sees the audit trail only contains a maximum of 1000 records.
What step should the engineer take?
Answer: B
Explanation:
Local Array Limitations: The FlashArray GUI and CLI maintain a local buffer for audit logs (which track commands, logins, and configuration changes). However, this local storage is limited in size and record count (typically around 1000 records or a short timeframe) to ensure that logging does not consume excessive system resources on the controllers. Once the limit is reached, older records are overwritten (FIFO - First In, First Out).
Pure1 as the Historical Repository: Pure1 is Pure Storage's cloud-based management and monitoring platform. One of its primary functions is to act as a long-term repository for array data. FlashArrays "phone home" their audit logs to Pure1, where they are indexed and stored for much longer periods (typically up to one year or more, depending on the subscription level).
Auditing in Pure1: By logging into the Pure1 portal, an administrator can navigate to the Audits section. Unlike the local GUI, Pure1 allows users to filter by specific date ranges, specific arrays, and specific users across the entire fleet. This makes it the standard tool for security audits and compliance reporting.
Why Option A and C are incorrect: * Option A: While the CLI is powerful, it still pulls from the same limited local buffer as the GUI. If the record has been overwritten locally, the CLI cannot retrieve it.
Option C: Purity does not typically allow customers to modify "tunables" to increase log storage, as this could impact the stability or performance of the Purity Operating Environment.
NEW QUESTION # 52
An administrator is preparing an array pair for ActiveDR and is trying to calculate the total minimum bandwidth requirement.
What percent of bandwidth above the incoming write rate should be allocated to accommodate for unexpected write bursts and still maintain near-sync RPO?
Answer: A
Explanation:
ActiveDR Bandwidth Sizing: ActiveDR is a continuous, asynchronous replication technology designed to provide near-zero RPO. Because it streams data continuously rather than in discrete snapshot intervals, the bandwidth between the source and target arrays must be able to handle the application's write workload.
Handling Write Bursts: Application workloads are rarely flat; they have peaks and valleys. If you size the bandwidth exactly to the average change rate, any burst in write activity will cause the replication lag to increase, thereby increasing your RPO.
The 30% Rule: Pure Storage best practices and sizing guides recommend providing a 30% buffer (headroom) above the measured average write rate. This extra capacity ensures that during a high-IO period, the replication engine has enough "pipe" to catch up quickly and return to a near-sync state.
Calculation Example: If a workload generates an average of 100 MB/s of new unique data, the administrator should ensure at least 130 MB/s of usable, dedicated bandwidth is available between the sites.
Consequences of Under-sizing: If only 10% (Option A) is used, the array may struggle to recover from even minor bursts, leading to a consistently climbing RPO. 50% (Option B) is often considered safe but can be cost-prohibitive or overkill for standard networking budgets unless the workload is exceptionally volatile.
NEW QUESTION # 53
If an NFS client can mount the FA File export shares with the IP address, but not the fully qualified domain name, what is most likely causing the issue?
Answer: C
Explanation:
When an NFS client successfully mounts an export using the target's IP address, it proves that the fundamental network connectivity (routing, firewalls) and the storage protocol layer (NFS export policies, host access permissions) are functioning correctly.
However, if the exact same mount attempt fails when using the Fully Qualified Domain Name (FQDN) of the FlashArray file service, the issue lies entirely with name resolution. The Domain Name System (DNS) is responsible for translating human-readable FQDNs into the IP addresses required for network communication. If the client cannot reach the DNS server, or if the DNS server lacks the correct A or AAAA records for the FlashArray's file Virtual IP (VIP) addresses, the client won't be able to resolve the name to the IP, causing the mount command to fail.
Here is why the other options are incorrect:
Issue with the Active Directory (AD) controller (A): Active Directory is primarily used for directory services, user authentication, and authorization (such as mapping permissions for SMB or NFSv4). While AD environments usually include DNS, an "AD controller issue" in the context of storage protocols usually points to permission denials, not host name resolution failures. Furthermore, since the mount works via IP, basic access is already validated.
Issue with the OpenLDAP (C): Similar to AD, OpenLDAP provides directory services for user mappings (UID/GID) and authentication. It does not perform FQDN-to-IP resolution.
NEW QUESTION # 54
An application engineer reports seeing high latency in their application running in a VMware instance.
What is the best method to determine the source of the latency?
Answer: B
Explanation:
Within the Pure Storage ecosystem, the absolute best method to troubleshoot and pinpoint the exact source of VMware latency is to use VM Analytics (VM Topology) in Pure1.
VM Analytics is a feature built directly into Pure1 that maps the entire data path from the virtual machine all the way down to the physical FlashArray. It provides a visual topology map detailing the VM, Virtual Disk, ESXi Host, Datastore, and FlashArray Volume. By analyzing performance across this topology, an administrator can instantly identify exactly where the latency is being introduced. For example, you can clearly see if the latency spikes at the ESXi host layer (indicating compute contention) or the network layer, even if the FlashArray volume itself is reporting sub-millisecond latency at the storage level.
Here is why the other options are incorrect:
Analyze load metrics in Pure1 for each volume in the user's data path (C): Looking exclusively at volume-level metrics on the FlashArray will only tell you the latency from the array's perspective. If the latency is being caused by an overloaded ESXi host CPU or a saturated SAN fabric, the FlashArray metrics will look perfectly healthy, and you will fail to identify the source of the problem.
Analyze performance charts in vSphere for CPU, Memory, Network, and Storage Path for the user's data path (B): While vCenter performance charts are useful, they often lack deep storage-array-level context. Pure1's VM Topology is the "best" method because it correlates the vSphere stack data with the native FlashArray telemetry data in a single, unified view, making full-stack root cause analysis much faster.
NEW QUESTION # 55
The Load Meter in the Pure1 GUI shows a consistently high workload, averaging a 90% load over the past hour. The array also has high space usage of 85%.
What is the expected result?
Answer: A
Explanation:
Understanding the Load Meter: The Load Meter in Pure1 and Purity represents the percentage of the array's performance capacity currently being utilized. It takes into account CPU cycles, back-end metadata processing, and front-end I/O. A 90% load means the controllers are nearly saturated.
The Impact of Capacity on Load: As a FlashArray fills up (specifically beyond 80%), the Purity Operating Environment must work harder to find and organize free space. This "Garbage Collection" (GC) process becomes more intensive, which consumes more controller resources and contributes to a higher Load Meter reading.
Internal System QoS: To ensure the stability and integrity of the storage, Pure Storage uses Internal Quality of Service (QoS). This is an "always-on" feature that prioritizes critical system processes (like metadata updates, internal health checks, and data protection) over incoming host I/O during periods of extreme resource contention.
Graceful Performance Pacing: When the load is consistently high (like the 90% described), Purity may introduce small amounts of latency to the host I/O (often seen as "Wait" or "Queue" time) to "pace" the workload. This prevents the controllers from reaching a 100% "locked" state, ensuring the array remains responsive and healthy even under heavy pressure.
Why Option C is incorrect: While the array needs to reclaim space, prioritizing Space Reclamation (a background task) during a 90% performance load would likely push the controllers to 100% load, causing significant latency spikes or instability for the host. The system must balance reclamation with active production I/O.
NEW QUESTION # 56
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