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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: HPE Storage Solutions Management | 20% | - Implement performance optimization strategies - Manage and monitor storage infrastructure using HPE tools - Configure quality of service (QoS) - Perform capacity planning and reporting |
| Topic 2: HPE Storage Solutions Integration | 30% | - Integrate HPE StoreOnce with backup software - Implement data protection and disaster recovery - Integrate HPE Nimble Storage with network environments - Integrate HPE Primera and HPE 3PAR with SAN infrastructure - Integrate with cloud providers (AWS, Azure, GCP) |
| Topic 3: Troubleshooting HPE Storage Solutions | 15% | - Diagnose storage connectivity issues - Resolve data protection and replication issues - Perform health checks and diagnostics - Troubleshoot performance bottlenecks |
| Topic 4: Architecting HPE Storage Solutions | 35% | - Design HPE Cloud Bank target solutions - Design HPE StoreOnce solutions for backup and recovery - Design HPEPrimera and HPE 3PAR StoreServ solutions - Design block, file, and object storage solutions - Design HPE Nimble Storage solutions |
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NEW QUESTION # 15
A customer has a diverse NoSQL big data and data analytics workload implementation. This workload runs on bare-metal servers to achieve the most efficient performance. The customer requires a new storage solution to meet their growing data needs. Which solution will be best for the customer?
Answer: B
Explanation:
For workloads like NoSQL databases (e.g., MongoDB, Cassandra), Big Data analytics (e.g., Hadoop, Spark), and high-throughput data lakes, the primary performance bottleneck is often the latency and bandwidth between the compute and the storage media. When a customer specifies they are running on bare-metal servers to achieve "most efficient performance," they are looking for a solution that minimizes the overhead of hypervisors and provides direct, high-speed access to storage. The HPE Alletra Storage Server 4000 series, and specifically the Alletra 4110, is purposefully engineered for this "Data-First" server-based storage market. The Alletra 4110 is a
1U, all-NVMe ultra-dense storage server that supports dual 4th or 5th Gen Intel Xeon Scalable processors and PCIe Gen5 throughput. Unlike traditional storage arrays that connect via a SAN, the Alletra 4110 functions as high-performance Software-Defined Storage (SDS) infrastructure. It is designed to run the application and the data storage on the same high-density nodes, or to act as a high-speed storage tier for bare-metal clusters.
NEW QUESTION # 16
What will occur when a new node is added to an existing HPE Alletra MP X10000 storage array?
Answer: B
Explanation:
The HPE Alletra MP X10000 is an object and file storage solution utilizing a Disaggregated Shared- Everything (DASE) architecture. A key differentiator of this disaggregated design is the stateless nature of the controller nodes and the centralized management of the data plane. When a cluster expansion occurs--such as adding a new controller node or an additional JBOF (Just a Bunch of Flash) storage shelf--the system is designed to automatically optimize the workload distribution. According to the HPE Alletra MP Architectural Guide, adding an additional JBOF or drives triggers an automatic rebalancing of the data stripes. Unlike older architectures where manual rebalancing services were required (such as in the 3PAR/B10000 block lineage), the X10000 uses a sophisticated hashing mechanism.
Specifically, data is distributed across DSPs (Data Storage Processors) which are virtualized management units. Upon the addition of hardware, these DSPs are rebalanced across the available compute and storage resources in a matter of seconds. Because the nodes are stateless and state is persisted only within the JBOFs, this rebalancing happens with minimal performance impact and no need for the massive "data movement" traditionally associated with expanding a RAID group. This ensures that as a customer scales from the minimum of 3 nodes up to 8 or more, the system always maintains an optimal load balance and utilizes all available flash bandwidth and compute cycles in parallel.
NEW QUESTION # 17
An HPE Partner is sizing an Alletra MP B10000 array for a customer using the HPE Ninja Sizer online tool.
When tuning the solution, the partner is not getting the best read and write performance from the array.
Use your cursor to place a + where the partner can click in the web GUI to begin to determine how to correct this Issue and appropriately size the solution for the customer.
Answer:
Explanation:
Explanation:
Performance Estimation
The HPE Ninja Sizer is a vital tool for storage architects to model the "Performance vs. Capacity" trade-offs of the HPE Alletra MP B10000 disaggregated architecture. In this scenario, the current configuration (as shown in the exhibit) consists of 4 nodes and 1 JBOF (with 8 drives of 15.36TB each).
To address poor read/write performance in Ninja Sizer, the partner must analyze the Performance Estimation pane. By clicking the chart/graph icon in the bottom right of the summary dashboard, the tool opens a detailed breakdown of the IOPS, throughput, and latency limits for the selected hardware. In a disaggregated shared-everything (DASE) architecture like the Alletra MP, performance is a direct function of the "node-to- drive" ratio. A configuration with only 8 drives (as seen in image_6491d0.png) may be "disk-bound," meaning the controllers have more compute power than the backend drive count can support in parallel.
By accessing the performance details, the partner can see if the bottleneck is at the node level (CPU/Cores) or the drive level (Flash bandwidth). To "correct this issue" and optimize the sizing, the partner would typically need to increase the drive count within the JBOF to allow for more parallel I/O streams or add additional JBOFs to scale the backend bandwidth. The Ninja Sizer provides real-time feedback; as the partner adds more
15.36TB drives, they will see the Performance Estimation bars move from yellow/red toward green, indicating an appropriately balanced solution that meets the customer's latency and throughput SLAs.
NEW QUESTION # 18
A customer wants to implement an HPE Morpheus life-cycle management solution at a single site with 1004 VMs using a redundant architecture and distributed services. Which statement is correct regarding the setup and operation of this solution?
Answer: A
Explanation:
When designing an HPE Morpheus environment for an enterprise-scale workload (such as 1,000+ VMs), a standalone "all-in-one" installation is insufficient for high availability (HA) and performance requirements.
Instead, a 3-node Distributed Architecture must be implemented to ensure redundancy across all critical service layers.
In a distributed, redundant Morpheus setup, the architecture is broken down into three primary tiers: the Application tier, the Database tier (MySQL/Percona), and the Messaging/Search tier (Elasticsearch and RabbitMQ). To achieve a basic redundant footprint, you require at least two Morpheus application nodes, three database nodes (for quorum), and a messaging cluster. According to the HPE Morpheus Architecture and Sizing Guide, a standard HA deployment starts with a minimum of six VMs to separate these functions.
However, for a production environment of this size, it is recommended to have a minimum of 10 VMs. This expanded footprint typically includes 3 App nodes, 3 Database nodes, and a 3-node cluster for Elasticsearch
/RabbitMQ, plus a dedicated load balancer or management node, ensuring that the loss of any single host does not impact the management plane's availability.
Option C is incorrect because a distributed installation is significantly more complex than the "all-in-one" appliance approach and requires manual configuration of externalized services. Option B is slightly inaccurate because while RabbitMQ itself is required, a dedicated "RabbitMQ load balancer" is often handled by the primary application load balancer (like an F5 or NetScaler) rather than being a specific required installation component. Option D is incorrect as upgrades in a distributed environment involve a coordinated, multi-step process across all nodes, which typically requires a scheduled maintenance window rather than "minimal" downtime.
NEW QUESTION # 19
Which statement is correct about when an HPE Partner runs a CloudPhysics assessment of a customer's third- party storage solution?
Answer: C
Explanation:
A foundational principle of the HPE CloudPhysics partner program is transparency and collaboration.
When an HPE Partner invites a customer to run a CloudPhysics assessment (using the "Invite Customer" workflow in the Partner Portal), it establishes a shared view of the customer's data center environment.
According to the HPE CloudPhysics Partner and Customer User Guides, both the partner and the customer have access to the same set of analytics "cards" within the platform. This shared visibility is intentional; it allows the partner to act as a "trusted advisor" by walking the customer through the same data visualizations and insights that the partner is using to build their proposal. Whether looking at the "Storage Inventory," "VM Rightsizing," or "Global Health Check" cards, both parties see the same data points, ensuring there is no "black box" logic in the assessment process.
While partners have additional administrative tools in their specific Partner Portal (like the ability to manage multiple customer invitations or use the Card Builder for advanced custom queries), the actual environment assessment and the standard reports are based on the core cards available to both accounts. Option A is incorrect because CloudPhysics provides a robust library of pre-built "Assessment" cards specifically designed for storage and compute sizing, eliminating the need for custom coding. Option C is incorrect as the typical assessment engagement is 30 days (though data remains in the SaaS data lake), and the 90+90 day cycle is not a standard hard-coded limit. Option D is incorrect because HPE provides these assessments at no cost to both the partner and the end customer to facilitate the transition to HPE solutions.
NEW QUESTION # 20
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