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Title: Test NCP-MCI-6.10 Score Report | NCP-MCI-6.10 Download Pdf
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Nutanix NCP-MCI-6.10 Exam Syllabus Topics:
TopicDetails
Topic 1
  • Manage VMs within a Nutanix Multicloud Environment: This section of the exam measures the skills of Cloud Administrators and Virtualization Engineers and covers managing virtual machines (VMs) within a Nutanix multicloud environment. It includes creating and updating VMs by determining hardware requirements, boot modes, sizing, and configuration based on application needs. Candidates must understand how to deploy VMs using templates, snapshots, and image configurations, ensuring the correct formats for importing and exporting VMs. Migration processes require knowledge of prerequisites, storage, network settings, and software compatibility. Additionally, configuring VM categories and attributes is essential for proper organization and management within the environment, ensuring alignment with labels, storage policies, and security settings.
Topic 2
  • Conduct Custom Monitoring within a Nutanix Multicloud Environment: This section of the exam measures the skills of Cloud Analysts and Systems Engineers and covers custom monitoring for optimized performance management. Candidates must analyze performance charts, set retention policies, create custom service level agreements (SLAs), and manage storage based on policies. Creating reports involves identifying the required type, selecting generation frequency, determining retention properties, and customizing report formats for different monitoring needs. Effective monitoring ensures better resource utilization, system efficiency, and proactive issue resolution within the multi-cloud environment.
Topic 3
  • Troubleshoot a Nutanix Multicloud Environment: This section of the exam measures the skills of Technical Support Engineers and IT Operations Specialists and covers diagnosing and resolving common issues within a Nutanix multi-cloud environment. Troubleshooting protection policies and recovery plans requires identifying network mapping failures, vNIC issues, script execution problems, and connectivity failures. Metro replication troubleshooting involves addressing naming conventions, network limitations, and replication states. Security issues in AOS and Prism Central must be resolved by managing CVM communications, security warnings, and log analysis. LCM operations require diagnosing failures in inventory updates and version upgrades. Performance troubleshooting involves analyzing logs, reading performance charts, and adjusting VM configurations to meet performance needs.
Topic 4
  • Manage Clusters within a Nutanix Multicloud Environment: This section of the exam measures the skills of Infrastructure Engineers and Systems Administrators and covers the administration of Nutanix clusters. Storage management includes creating, reading, updating, and deleting storage containers and volume groups. Configuring AOS and Prism Central settings involves authentication, SSL certificate management, IAM role-based access control, and configuring network segmentation. Network administration procedures focus on creating VLAN-backed subnets, virtual switches, and load-balancing policies while monitoring NIC usage. Lifecycle management includes performing hardware and software updates and maintaining firmware. Hardware maintenance involves adding or removing nodes and physical disks while ensuring proper upgrades and replacements. Intelligent operations require configuring capacity policies, discovering application relationships, and simulating scenarios to optimize performance.
Topic 5
  • Configure Disaster Recovery and Data Protection within a Nutanix Multicloud Environment: This section of the exam measures the skills of Disaster Recovery Specialists and Cloud Engineers and covers configuring protection policies and domains for data security and recovery. Candidates need to identify the right entities for protection, schedule backups, define retention policies, and set up replication to remote sites. Recovery plans must be configured and executed with proper scripting, network mapping, and failover strategies. Metro replication requires understanding failover methodologies, comparing solutions on different hypervisors, and preventing split-brain scenarios. Effective disaster recovery planning ensures minimal downtime and data integrity across environments.

Nutanix Certified Professional - Multicloud Infrastructure (NCP-MCI v6.10) Sample Questions (Q138-Q143):NEW QUESTION # 138
In Prism Element, how many nodes can be placed into maintenance mode at one time on 12-node FT2 cluster?
Answer: B
Explanation:
In a 12-node FT2 cluster, onlyonenode can be placed into maintenance mode at a time. This ensures that the cluster maintains data redundancy and protection (FT2 indicates 2-failure tolerance).
From theNutanix Enterprise Cloud Administration (ECA)course materials:
"For FT2 clusters, a maximum of one node can be placed in maintenance mode at a time to ensure the cluster' s ability to tolerate failures and maintain quorum."

NEW QUESTION # 139
What guest customization options are available when creating a VM template?
Answer: C,D
Explanation:
When creating templates in Nutanix, Prism Central supports two official, built-in guest customization frameworks depending on the operating system family.
The Nutanix guest customization documentation states:
"For Windows VMs, Prism Central supports Sysprep-based customization. For Linux VMs, Prism Central supports Cloud-init customization." These two tools allow automation of hostname assignment, networking configuration, user accounts, and post- deployment initialization.
Additional extracts from internal documentation:
* "Sysprep is automatically invoked during clone operations from Windows templates to ensure that the cloned VM receives unique identifiers."
* "Cloud-init is used for Linux templates to allow dynamic provisioning, SSH key injection, and package installation during instantiation." Nutanix does not list "Custom Script" or "Guided Script" as valid VM template customization mechanisms.
Scripting can be applied after deployment but not as a built-in template customization framework.
Thus, the only valid template customization options are Sysprep and Cloud-init.

NEW QUESTION # 140
An administrator is trying to configure Metro Availability between Nutanix ESXi-based clusters. However, theCompatible Remote Sitesscreen does not list all required storage containers.
Which two reasons could be a cause for this issue? (Choose two.)
Answer: A,B

NEW QUESTION # 141
Within Intelligent Operations, Capacity Configurations have been set to Auto Detect for Reserve Capacity For Failure.
For an RF2 cluster with 10 nodes, what effect does this have on Capacity Runway?
Answer: C

NEW QUESTION # 142
An administrator received a request to create a new storage container for persistent desktops.
Which storage optimization setting must the administrator set for the best possible capacity savings?
Answer: D
Explanation:
The Nutanix ECA course covers storage optimization techniques for Nutanix storage containers, particularly for workloads like persistent desktops, which require efficient capacity utilization due to their repetitive data patterns. Persistent desktops typically store user-specific data and configurations, making them ideal candidates for storage optimization techniques like compression, deduplication, or erasure coding. The question asks for the setting that provides thebest possible capacity savings.
Extract from Nutanix Enterprise Cloud Administration (ECA) Course Documents:
* Module: Storage Management, Section: Storage Optimization"Erasure Coding provides the highest capacity savings for workloads with large amounts of data, such as persistent desktops. By distributing data and parity across nodes, Erasure Coding reduces storage overhead compared to replication factor (RF) while maintaining fault tolerance."
* Module: Storage Configuration, Section: Optimization for Virtual Desktops"For persistent desktop workloads, Erasure Coding is recommended to maximize capacity savings. It is more efficient than compression or deduplication alone, as it reduces the storage footprint by encoding data across nodes, making it ideal for environments with high data redundancy." Explanation of Options:
* A. Erasure CodingThis is the correct answer. Erasure Coding (EC-X) is a storage optimization technique in Nutanix AOS that distributes data and parity information across nodes, reducing the storage overhead compared to traditional replication factor (RF) settings. For persistent desktops, which often have large datasets with redundant patterns, Erasure Coding provides significant capacity savings by encoding data efficiently while maintaining fault tolerance. The ECA course highlights that Erasure Coding is particularly effective for workloads with cold or less frequently accessed data, which aligns with persistent desktop storage.
* Supporting Extract:"Erasure Coding can achieve up to 50% or more capacity savings compared to RF=2 for workloads like virtual desktops, making it the most effective optimization for capacity-constrained environments."
* B. Inline compression with a delay of 0 minutesThis is incorrect. Inline compression reduces data size in real-time as it is written to storage, but it provides less capacity savings compared to Erasure Coding for persistent desktops. Compression is effective for reducing the size of compressible data, but persistent desktops often benefit more from Erasure Coding due to their larger datasets and redundancy.
Additionally, a delay of 0 minutes means compression occurs immediately, which may increase write latency without maximizing savings. The ECA course notes:"Inline compression is useful for general workloads but is less effective than Erasure Coding for high-capacity workloads like persistent desktops."
* C. Inline Deduplication of Read CachesThis is incorrect. Deduplication removes duplicate data blocks, but "Inline Deduplication of Read Caches" is not a standard Nutanix feature for storage containers.
Nutanix supports inline and post-process deduplication, but these apply to data writes, not specifically to read caches. Even if deduplication were applied, it would provide less capacity savings than Erasure Coding for persistent desktops, as deduplication depends on data similarity, whereas Erasure Coding optimizes storage across all data types. The ECA course states:"Deduplication is effective for workloads with high data similarity, but Erasure Coding provides broader capacity savings for large- scale desktop deployments."
* D. Post Process DeduplicationThis is incorrect. Post-process deduplication analyzes and removes duplicate data after it is written, which can save capacity but is less efficient than Erasure Coding for persistent desktops. Deduplication requires significant data similarity to achieve savings, and its post- process nature delays optimization, potentially leading to temporary storage overuse. The ECA course clarifies:"Post-process deduplication is suitable for specific workloads, but Erasure Coding is preferred for persistent desktops due to its superior capacity efficiency and immediate applicability across nodes." Additional Context from ECA:
* Erasure Coding Details: Erasure Coding works by splitting data into fragments, adding parity information, and distributing these across nodes. For a storage container with persistent desktops, enabling Erasure Coding (e.g., with a stripe width of 4+2) can significantly reduce the storage footprint compared to RF=2 or RF=3. The ECA course notes:"Erasure Coding is ideal for containers with large datasets, such as VDI environments, where capacity savings are critical."
* Persistent Desktops: These desktops store user data and configurations, leading to large, redundant datasets. Erasure Coding's ability to optimize storage across nodes makes it the best choice for capacity savings, as confirmed by the ECA materials.
Supporting Reference from Web Results:
The Nutanix Bible (https://www.nutanix.com/go/the-nutanix-bible) supports the ECA documentation:" Erasure Coding (EC-X) provides the highest capacity efficiency for workloads like persistent desktops, reducing storage overhead by distributing data and parity across nodes, outperforming compression and deduplication in capacity-constrained environments."

NEW QUESTION # 143
......
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