HPE7-J02 Exam Questions

Detailed Explanatio n:

Rationale for Correct Answe r:

For competitive or 3rd-party (non-HPE) environments like Dell + VMware, HPE CloudPhysics is the correct tool. The Observer VM is deployed into vCenter to gather real-world workload metrics (CPU, memory, storage I/O). These analytics can then be used for SimpliVity HCI sizing.

Distractors:

A: NinjaOnline SimpliVity Sizer requires input metrics, but it cannot directly collect from 3rd-party environments.

B: InfoSight sizing applies to HPE arrays, not competitive storage.

D: InfoSight for SimpliVity only monitors existing HPE SimpliVity clusters.

Key Concept: CloudPhysics Observer gathers competitive workload metrics feeds into SimpliVity sizing.

Detailed Explanatio n:

Rationale for Correct Answe r:

In the exhibit, several paths show ''Standby'' and some appear ''Dead'', while only a subset is Active (0). This typically indicates that one storage controller may be missing or offline, which reduces redundancy and can cause performance degradation. In a healthy Peer Persistence environment, both controllers should present active and non-optimized paths.

Distractors:

A & B: Having multiple active paths does not inherently reduce performance; in fact, MPIO load balances traffic. The issue here is path failures, not excessive active paths.

Key Concept: MPIO pathing in HPE Peer Persistence and controller health.

Detailed Explanatio n:

Rationale for Correct Answe r:

After installing the HPE CSI driver and creating backend secrets, the next critical step is to define a StorageClass that references the backend driver and parameters. Without the StorageClass, Kubernetes cannot dynamically provision PersistentVolumes (PVs). Once the StorageClass is created, workloads can request storage using PersistentVolumeClaims (PVCs).

Distractors:

A: Helm repo update only refreshes Helm charts; it does not enable CSI provisioning.

B: A PVC requires a StorageClass to bind dynamically --- it cannot be created successfully beforehand.

C: Manually creating PVs is possible, but not the HPE best practice with CSI, which relies on StorageClass for dynamic provisioning.

Key Concept: Kubernetes CSI workflow: Secret StorageClass PVC Pod.

Detailed Explanatio n:

Rationale for Correct Answe r:

The exhibit shows a system delivering ~2.3 GB/s sequential read. For large-block sequential workloads, aggregate host link bandwidth (number speed of front-end ports) is the primary limiter. Increasing the count of 10/25 Gb iSCSI NICs adds parallel lanes, raising sustained read GB/s to the hosts. This is a recommended first step in HPE sizing before changing protocols.

Analysis of Incorrect Options (Distractors):

A: Adding an expansion shelf increases capacity, not front-end bandwidth.

C: Moving to 32 Gb FC can help, but simply adding more existing 10/25 Gb ports achieves the same goal without a protocol/adapter change and is the straightforward, supported scale-out path.

D: SCM (Storage Class Memory) targets latency/IOPS; it doesn't materially lift sequential GB/s if the link budget is the bottleneck.

Key Concept: Scale front-end connectivity to increase sequential throughput; capacity or media class changes won't fix a link-limited system.

Detailed Explanatio n:

Rationale for Correct Answe r:

Changing HA from Drive Level to Enclosure Level means the system must reserve additional capacity to tolerate the loss of an entire disk enclosure. This decreases usable capacity, as more parity/spare space is required. Performance remains similar, but capacity overhead increases.

Distractors:

A: Multiple enclosures exist in the config; option is valid.

B: Switched vs direct-connect is unrelated to HA settings.

C: Performance estimates are not directly reduced by HA level change; capacity is.

Key Concept: Enclosure HA = more reserve overhead less usable capacity.