NCP-MCI-6.10 Sample Questions Answers

VMs using GPU pass-through cannot be live-migrated because they are directly tied to a physical GPU on a specific host.

Option B (VMs use GPU pass-through) is correct:

Pass-through devices (such as GPUs) are directly assigned to VMs, makingmigration impossibleunless the VM is powered off first.

Option A (VMs use a Volume Group) is incorrect:

Volume Groupssupport live migrationunless they are configured incorrectly.

Option C (VM-VM anti-affinity) is incorrect:

Anti-affinity rules prevent two specific VMs from running together, but do not prevent migration.

Option D (VMs use external NAS) is incorrect:

Using NAS does not block VM migration, as Nutanixsupports shared storage across hosts.

The Nutanix ECA course provides guidance on performance monitoring and troubleshooting for VMs, including metrics to analyze when determining whether additional vCPUs are needed. The scenario involves a VM experiencing performance issues, with the cluster performing well overall, suggesting the issue is VM-specific.

Extract from Nutanix Enterprise Cloud Administration (ECA) Course Documents:

Module: Performance Monitoring, Section: VM Performance Metrics"To determine if a VM requires additional vCPUs, analyze VM CPU Usage and VM CPU Ready Time. High CPU Usage indicates the VM is under heavy load, while high CPU Ready Time suggests the VM is waiting for CPU resources, both justifying additional vCPUs."

Module: Troubleshooting, Section: VM Performance Issues"When a VM experiences performance issues, VM CPU Usage and VM CPU Ready Time are critical metrics. CPU Usage shows demand, while CPU Ready Time indicates contention or scheduling delays, helping determine if more vCPUs are warranted."

Explanation of Options:

A. VM CPU UsageThis is correct. VM CPU Usage measures the percentage of CPU resources the VM is consuming. High CPU Usage (e.g., consistently above 80–90%) indicates that the VM is under heavy load and may benefit from additional vCPUs to handle the workload. The ECA course emphasizes:"VM CPU Usage is the primary metric to assess whether a VM’s CPU allocation is sufficient for its workload."

B. VM CPU Ready TimeThis is correct. VM CPU Ready Time measures the time a VM is ready to run but waiting for CPU resources from the hypervisor due to contention or oversubscription. High CPU Ready Time (e.g., above 5–10%) suggests that the VM is not getting enough CPU cycles, and adding vCPUs could alleviate the issue. The ECA course notes:"High VM CPU Ready Time indicates CPU contention, often resolved by adding vCPUs or optimizing resource allocation."

C. Host Memory Swap Out RateThis is incorrect. Host Memory Swap Out Rate indicates memory pressure on the host, causing memory pages to be swapped to disk. While this can affect VM performance, it is unrelated to CPU performance and does not justify adding vCPUs. The ECA course states:"Host Memory Swap Out Rate is relevant for memory-related issues, not CPU allocation decisions."

D. Host CPU UsageThis is incorrect. Host CPU Usage measures the overall CPU utilization of the host, not the specific VM. Since the cluster is performing well overall, high Host CPU Usage is unlikely, and it does not directly indicate whether the VM needs more vCPUs. The ECA course clarifies:"Host CPU Usage is a cluster-wide metric and less relevant for diagnosing VM-specific CPU performance issues."

Additional Context from ECA:

Performance Monitoring Tools: In Prism Element or Prism Central, VM CPU Usage and CPU Ready Time can be monitored underVM > Monitoror through dashboards. These metrics provide insight into the VM’s CPU demand and contention.

Adding vCPUs: The ECA course advises caution when adding vCPUs, as over-allocation can increase CPU Ready Time due to scheduling overhead. However, if both CPU Usage and Ready Time are high, adding vCPUs is justified.

Supporting Reference from Web Results:

The Nutanix Bible (https://www.nutanix.com/go/the-nutanix-bible) supports: "For VM performance issues, analyze VM CPU Usage and CPU Ready Time to determine if additional vCPUs are needed, as these metrics directly indicate CPU demand and contention."

Nutanix Life Cycle Manager (LCM) relies on validated firmware and driver bundles for hardware components. For GPU-enabled hosts, LCM documentation states:

“GPU-enabled AHV hosts require GPU driver bundles to be uploaded manually via the Direct Uploads mechanism so that LCM can validate and upgrade the necessary GPU components during workflow execution.”

GPU drivers are vendor-specific and not always available in the standard catalog, so the administrator must upload them before LCM can orchestrate the upgrade.

Running in dark site mode does not provide missing GPU bundles. Creating agent VMs is unrelated to GPU driver operations. Updating NCC improves validations but does not provide GPU support files.

Therefore, Direct Uploads of GPU driver bundles is required.

To create a custom Intelligent Operations report and run it across multiple Prism Central instances, administrators must export the report configuration from one Prism Central instance and then import it into the others. This process leverages the .rpt file format, which encapsulates the report’s configuration details, including data sources, visualization preferences, and thresholds.

From theNutanix Enterprise Cloud Administration (ECA)course materials:

“Administrators can create custom Intelligent Operations reports in Prism Central and export the configuration as a .rpt file. This exported file can then be imported into other Prism Central instances, ensuring consistency across environments without requiring manual recreation of the report’s details.”

Additionally:

“The export/import feature for reports ensures that custom dashboards and reports can be easily migrated or replicated across multiple Prism Central instances, enabling a standardized approach to monitoring and analytics in a multicloud environment.”

This clearly indicates that the recommended and supported method for sharing or replicating custom reports across multiple Prism Central instances is by exporting and importing the report configurations in .rpt format. This approach avoids the need for manual recreation and ensures that the reports maintain their intended configuration and layout across different instances.

During cluster expansion, Nutanix uses the Controller VM discovery service, which relies on multicast-based node advertisement. The internal architecture documentation states:

“Node discovery during cluster expansion requires IPv4 multicast to be enabled and permitted on the switching infrastructure.”

This allows new nodes to announce themselves to the existing cluster through standard Nutanix discovery packets.

IPv6 multicast is not used for node discovery. Matching AOS or hypervisor versions is recommended for compatibility but not required for discovery itself. These are post-discovery compatibility concerns, not prerequisites.

Thus, IPv4 multicast is required for automatic node discovery.

Nutanix Prism Central uses Role-Based Access Control (RBAC) combined with Projects to segment access to workloads. Documentation describes Projects as:

“Projects provide a scalable method to group VMs and assign user or group permissions so that access is restricted to only the resources belonging to that project.”

When VMs are added to a project, Prism Central automatically handles:

scoping of administrative permissions

allowed actions (power, console, modify)

limiting visibility only to VMs inside that project

isolation between different teams or business units

Role mapping alone does not limit scope; it only assigns permissions. Without projects, users may see more VMs than intended. VPCs relate to Flow Virtual Networking and network segmentation, not Prism RBAC or VM-level access control. Security Policies isolate network traffic, not administrative visibility.

Thus, creating a project for each team lead and assigning VM access is the most efficient and intended Nutanix mechanism.

When diagnosing CPU performance issues, CPU Ready Time and CPU Usage are the key indicators of whether more vCPUs are needed.

Option A (VM CPU Ready Time) is correct:

High CPU Ready Time means the VM is waiting for CPU resources, indicatingCPU contention.

Option B (VM CPU Usage) is correct:

If CPU usage isconsistently high, adding more vCPUsmay improve performance.

Option C (Host CPU Usage) is incorrect:

Host-wide CPU usage does not indicate whether a specific VM needs more vCPUs.

Option D (Host Memory Swap Out Rate) is incorrect:

Memory swappingaffects RAM performance, not CPU allocation.

Question 155 [Manage Nutanix clusters]

Which Nutanix feature allows administrators to expand a cluster by adding new nodes without downtime?

A. AHV Protection Domains

B. Prism Central

C. Scale-out Architecture

D. Metro Availability

Answer: C

Offset-based IP mapping in Nutanix Recovery Plans allows automatic subnet changes during DR failover.

Option D (Utilize Recovery Plan Offset-based IP mapping) is correct:

This methodautomatically adjusts the IP rangewhile keeping the same last octet.

It eliminates the need formanual interventionafter failover.

Option A (Custom script) is incorrect:

Scripting is an option, butRecovery Plan IP mapping is simpler and native to Nutanix.

Option B (Use IPAM) is incorrect:

IP Address Management (IPAM) is useful, butoffset-based mapping provides more control.

Option C (Manually update IPs) is incorrect:

This would betime-consuming and error-prone.

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."

Nutanix Categories allow administrators to group related VMs, making Disaster Recovery (DR) planning easier.

Option B (Utilize Categories to organize VMs in Recovery Plans) is correct:

Categories help group VMsbased on application tiers(e.g.,database, middleware, web servers).

This ensuresorderly failoverwhile maintaining application dependencies.

Option A (Naming schema) is incorrect:

Naming conventions help, but theydo not provide functional organizationin recovery plans.

Option C (1:10 Recovery Plan to VMs) is incorrect:

The ratio depends onbusiness requirements, not a fixed number.

Option D (RESTful APIs) is incorrect:

Automation is useful, butit does not replace proper VM grouping via categories.

NutanixIntelligent Operations Reports(Option D) provideweekly summariesof cluster health, performance, and resource consumption.

These reports includerecommendations for optimization, alerts, and forecasted resource usage trends.

Option A (Admin Center LCM)managesfirmware and software upgradesbut does not generate weekly performance reports.

Option B (Prism Central Syslog)is used forlogging and event tracking, not performance summaries.

Option C (Infrastructure VMs List)provides astatic list of VMsbut does not generate periodic reports.

After a Prism Central upgrade, IAM authentication settings may require reconfiguration.

Option D (Log in with a local admin account) is correct:

If IAM authentication fails, thelocal admin account must be usedto check domain settings.

Option A (Ping the Domain Controller) is incorrect:

Network connectivity is important, but theissue is likely related to IAM settings, not network reachability.

Option B (Check firewall port 9441) is incorrect:

Port 9441 is used forSSO authentication, butport issues usually result in login delays, not complete failures.

Option C (Validate signing certificate) is incorrect:

While certificates can cause issues,local admin login should always work.

Dead VMs and Zombie VMs are different classifications of inactive VMs in Nutanix, and their deletion timelines depend on Playbook configuration.

Dead VMs→ Consideredinactive after 30 days, then must wait99 more daysbefore deletion.

Total time: 30 + 99 = 129 days.

(Option C is correct).

Zombie VMs→ Consideredinactive after 30 days, then must wait99 more daysbefore deletion.

Total time: 30 + 99 = 129 days.

(Option B is correct).

Nutanix storage container configuration guidance specifies that “Advertised Capacity” is the setting used to define a maximum limit for the container. This value enforces a hard cap on space usage. Reserved Capacity, in contrast, defines a minimum guarantee of space for the container and does not limit growth.

Prism Element is the correct interface for creating storage containers with specific data reduction settings such as compression and deduplication, as the container-level storage policies are applied directly at the cluster’s storage layer.

The documentation further clarifies that RF1, inline compression, and deduplication settings are configured within Prism Element under container creation. Therefore, to enforce the 100 GiB limit, the administrator must create the container in Prism Element and set the Advertised Capacity to 100 GiB.

The Nutanix Enterprise Cloud Administration (ECA) course provides detailed guidance on managing images in a multicloud environment, particularly when administering multiple clusters across different geographic sites via a single Prism Central instance. The goal of optimizing image uploads to all locations involves ensuring efficient image availability, minimizing latency, and balancing storage and network resource usage. The ECA course emphasizes the use ofImage Placement Policiesto control how images are distributed and stored across clusters registered with Prism Central.

Extract from Nutanix Enterprise Cloud Administration (ECA) Course Documents:

Module: Image Management, Section: Image Placement Policies"Prism Central allows administrators to manage images centrally for multiple clusters. Image Placement Policies define how images are distributed to clusters. A policy with Soft Enforcement ensures that images are uploaded to a preferred cluster and replicated to other clusters as needed, optimizing for network efficiency and availability while allowing flexibility if a target cluster is unavailable."

Module: Prism Central Management, Section: Multi-Cluster Image Management"For environments with clusters at different geographic sites, an Image Placement Policy with Soft Enforcement is recommended to optimize image uploads. This policy allows Prism Central to select a primary cluster for image storage and replicate the image to other clusters based on demand, reducing unnecessary uploads while ensuring images are available where needed."

Explanation of Options:

A. Image Placement Policy with Soft EnforcementThis is the correct answer. The ECA course highlights that anImage Placement Policy with Soft Enforcementis designed to optimize image distribution in multi-cluster environments, especially across geographic sites. With Soft Enforcement, Prism Central uploads the image to a designated cluster (e.g., the closest or most available) and replicates it to other clusters as needed, based on workload requirements or VM deployment demands. This approach minimizes redundant uploads, reduces network congestion, and ensures images are available efficiently across sites. The "soft" aspect allows flexibility—if a target cluster is offline or has insufficient storage, Prism Central can select an alternative cluster, ensuring operational continuity.

Supporting Extract:"Soft Enforcement allows Prism Central to prioritize a primary cluster for image storage but permits fallback to other clusters if the primary is unavailable, optimizing upload efficiency and image availability across multiple sites."

B. Custom Image Upload RoleThis is incorrect. The ECA course does not define a "Custom Image Upload Role" as a feature in Prism Central for optimizing image uploads. While Prism Central supports role-based access control (RBAC) for managing permissions, including image management, these roles govern who can upload or manage images, not how images are distributed or optimized across clusters. The ECA materials state:"RBAC in Prism Central allows administrators to assign permissions for image management, but it does not influence the placement or optimization of image uploads."This option is irrelevant to the question’s focus on optimizing image distribution.

C. Bandwidth Throttling PolicyThis is incorrect. While bandwidth throttling can regulate network usage during data transfers (e.g., during replication or migration), it does not directly optimize image uploads for availability or efficiency across multiple clusters. The ECA course mentions bandwidth throttling in the context of data protection and replication:"Bandwidth Throttling Policies can be applied to replication schedules to manage network usage, but they are not used for image placement or upload optimization in Prism Central."Throttling could even slow down image distribution, counteracting the goal of optimization, especially in a multi-site scenario.

D. Image Placement Policy with Hard EnforcementThis is incorrect. AnImage Placement Policy with Hard Enforcementstrictly mandates that images be uploaded to specific clusters as defined in the policy. If the designated cluster is unavailable (e.g., due to network issues, storage constraints, or downtime), the upload fails, which can disrupt operations in a multi-site environment. The ECA course notes:"Hard Enforcement ensures images are only stored on specified clusters, but this can lead to upload failures if the target cluster is offline or lacks capacity, making it less suitable for geographically distributed environments."This rigidity makes Hard Enforcement less optimal compared to Soft Enforcement, which provides flexibility and ensures image availability.

Additional Context from ECA:

Image Management Workflow: The ECA course explains that Prism Central’s Image Service centralizes image management for all registered clusters. When an image is uploaded, the Image Placement Policy determines where it is stored and how it is replicated. For geographically dispersed clusters, Soft Enforcement balances efficiency and availability by prioritizing a primary cluster (e.g., based on proximity or storage capacity) while allowing replication to other clusters as needed for VM provisioning or workload deployment.

Extract:"In multi-site deployments, Soft Enforcement optimizes image uploads by reducing redundant data transfers and ensuring images are accessible across clusters without requiring manual intervention."

Practical Consideration: In a multi-site scenario, network latency and storage availability vary across clusters. Soft Enforcement allows Prism Central to adapt dynamically, ensuring images are uploaded to a viable cluster and replicated efficiently, which aligns with the goal of optimization.

Supporting Reference from Web Results:

The Nutanix Bible (https://www.nutanix.com/go/the-nutanix-bible) reinforces the ECA documentation: "Image Placement Policies in Prism Central streamline image management across clusters. Soft Enforcement is ideal for multi-site environments, as it allows flexible image placement and replication, ensuring efficient uploads and availability."This confirms that Soft Enforcement is the recommended approach for optimizing image uploads in a multi-cluster, multi-site setup.

The Intelligent Operations and Analysis Dashboard in Prism Central supports generating ad-hoc reports. These reports are temporary artifacts and are not designed for long-term storage. Internal documentation states, “Generated reports are retained for 24 hours and then automatically purged by the system to prevent report accumulation and data bloat.” This automatic cleanup is part of the reporting subsystem and applies regardless of user role or storage location. The reports are not stored in Prism Element, nor are they archived automatically. Therefore, after the 24-hour retention window, the system removes them, explaining why the user could not find the previously generated report.

TheBully VMs List (Option C)in Prism Central’sIntelligent OperationsidentifiesVMs consuming excessive CPU, memory, or storage, which negatively affects other VMs.

Option A (Inactive VMs List)is used foridentifying unused VMsbut does not detect performance issues.

Option B (Overprovisioned VMs List)helps identifyVMs with excessive allocated resources, but it does not focus on live performance impact.

Option D (Constrained VMs List)highlightsVMs suffering from resource contention, not those causing it.

Nutanix AHV networking supports multiple bond types that determine how traffic is distributed across physical NICs. The detailed guidance in the AHV networking section states:

“Active-Active bonding provides load distribution of outbound traffic across all interfaces in the bond, allowing aggregate throughput beyond a single physical adapter.”

Active-backup keeps only one NIC active at a time and provides no throughput gain. Active-Active with MAC pinning distributes VMs across NICs but does not aggregate the total throughput for a single VM and is typically used with switch-independent designs.

Because the requirement is to “take advantage of bandwidth beyond a single adapter,” only the standard Active-Active bond type satisfies this, as it truly aggregates available bandwidth.

Therefore, the correct bond type is Active-Active.

Nutanix documentation explains that Reserved Capacity for a storage container allocates a guaranteed amount of physical space exclusively for that container. The internal description is:

“Reserved Capacity is space carved out from the storage pool for guaranteed use by a container. When a container’s reserved allocation approaches exhaustion, alerts are raised even if the overall cluster has ample free space.”

This means that although the physical cluster capacity may be sufficient, the container itself may hit its reserved limit, triggering an out-of-space forecast. Advertised Capacity determines an upper usage limit but does not produce this behavior. Replication Factor affects total usage but cannot explain container-only exhaustion when the cluster is fine. Compression levels influence data reduction but not capacity alerting mechanisms.

Thus, an oversized Reserved Capacity value is responsible for the alert.

Entity Charts in Nutanix Prism Central allow multiple metrics from a single entity (e.g., VM, storage container) to be displayed on a single graph.

Option B (Entity Chart) is correct:

This allows the administrator totrack multiple performance metrics(e.g., read/write bandwidth, IOPS) for aspecific VM.

Option A (Metric Chart) is incorrect:

Metric Charts track a single metric across multiple entities, which does not meet the requirement ofdisplaying multiple metrics for a single VM.

Option C (Hypervisor Performance Chart) is incorrect:

Hypervisor Performance Chartstrack host-level metrics, notVM-specific bandwidth metrics.

Option D (VM Summary Chart) is incorrect:

VM Summary Chartsonly provide an overviewand do not supportcustom multi-metric tracking.

In Nutanix Protection Domain-based replication, both thesourceanddestinationstorage containersmust have the same Replication Factor (RF)to ensure consistent data protection and replication. This is a key requirement for the data’s protection and integrity.

From theNutanix ECAdocumentation:

“Replication and recovery require that the source and destination containers have the same RF setting (either RF2 or RF3). If the RF does not match, replication and recovery points will not be generated in the DR site.”

The other options:

A (NGT): NGT is not required for crash-consistent protection.

C (Windows updates): Updates are not directly relevant to replication consistency.

D (container name): Names can differ; what matters is the container’s RF setting.

The test_esx_entering_mm_pinned_vms check in an AOS upgrade validates whether there are any pinned VMs on ESXi hosts, which could prevent host maintenance mode transitions.

From theNutanix Enterprise Cloud Administration (ECA)course materials:

“Affinity or anti-affinity rules that pin VMs to specific hosts prevent those VMs from migrating during host maintenance mode entry. This directly triggers a failure in the LCM precheck test_esx_entering_mm_pinned_vms check.”

Scale-out Prism Central deployments consist of multiple nodes running the Prism Central service. Nutanix documentation emphasizes that:

“When deploying multi-node Prism Central, an FQDN backed by DNS can provide request distribution across all Prism Central nodes, enabling load balancing and increased concurrency.”

A Virtual IP in contrast only directs traffic to a single active Prism Central node. Internal behavior notes:

“A VIP is not active-active; it designates one node as primary for all inbound requests.”

“Using an FQDN with DNS round-robin or an external load balancer allows the cluster to distribute workload across all PC nodes.”

The FQDN allows:

distributing API/UI traffic across multiple Prism Central nodes

improving performance under heavy load

enabling parallel query handling

avoiding bottlenecks on the primary node

SSL certificates apply to either VIP or FQDN. Segmentation and resiliency are unrelated to FQDN usage.

Thus, the correct answer is Load Balancing.

Understanding the Exhibit & the Alert

The alert states:

"The cluster is using password-based SSH access for the CVM."

"Password-based remote login is enabled on the cluster."

"It is recommended to use key-based SSH access instead of password-based SSH access for better security."

This means that the nutanix user can log in to Controller VMs (CVMs) using a password, which is a security risk.

Corrective Action: Enabling Cluster Lockdown

✅(C) Enable Cluster Lockdown. (Correct Answer)

Cluster Lockdown Mode restricts password-based SSH access and forces key-based authentication.

This prevents users from logging into CVMs using passwords, enhancing cluster security.

To enable Cluster Lockdown:

Go to Prism Central or Prism Element.

Navigate to Settings → Security → Cluster Lockdown.

Enable Cluster Lockdown Mode.

Evaluating the Other Answer Choices

❌(A) Rename the nutanix user. (Incorrect)

The nutanix user is a built-in system account required for cluster operations.

Renaming the user will not prevent SSH access via password.

❌(B) Block port 22 on the CVM firewall. (Incorrect)

Blocking port 22 (SSH) will completely disable SSH access, including key-based authentication.

This may break cluster management and troubleshooting operations.

❌(D) Delete the nutanix user. (Incorrect)

The nutanix user is a critical system account required for cluster functionality.

Deleting the account will cause serious issues with cluster management.

Multicloud Infrastructure References & Best Practices

Nutanix Security Best Practices:

Always use key-based SSH authentication instead of password-based logins.

Enable Cluster Lockdown Mode to enforce security policies.

Regularly audit user access to ensure security compliance.

Cluster Lockdown Benefits:

Prevents unauthorized SSH access via passwords.

Enforces public key authentication, reducing brute-force attack risks.

Strengthens CVM security against potential exploits.

Data-in-Transit Encryption for Prism Central and CVMs requires specific internal communication ports to be open. Nutanix internal component documentation states:

“Port 2020 is used by the Nutanix encryption service for encrypted CVM-to-CVM communication during Data-in-Transit Encryption operations.”

This port is essential for establishing secure tunnels between control-plane services. Ports 2009 and 2010 are used by other CVM services (e.g., Stargate, Curator coordination) but not for transport encryption. Port 9440 is for Prism UI/API traffic, and while it must be accessible for management, it does not enable encrypted back-end service traffic.

Thus, the administrator must ensure that port 2020 is permitted to enable Data-in-Transit Encryption functionality.

The NCC alert indicates connectivity failure to the remote site. Resolving this involves confirming network connectivity and re-establishing the remote site configuration if necessary.

From theNutanix Enterprise Cloud Administration (ECA)course materials:

“The primary ports used for replication between clusters are 2009 (for Prism Element API) and 2020 (for data replication). Ensuring these ports are open and reachable is critical for remote site connectivity.”

Also:

“If the remote site has been re-imaged or reconfigured, it may have a new cluster incarnation ID. In such cases, the remote site configuration must be recreated to align with the current cluster information.”

Steps like checking ping with MTU 9000 (D) are not directly related to remote site connectivity for replication, and NAT configurations (B) are generally not recommended unless explicitly required.

The Nutanix AHV virtualization guide explains that vGPU-enabled VMs can be live migrated only when the destination host contains compatible GPU hardware and has available vGPU capacity matching the profile assigned to the VM. The documentation states that the VM must have "adequate and equivalent GPU resources on the target host" for migration to proceed. Host affinity is a limiting factor and not a requirement. Agent VMs are not designed to be migrated. Changing the vGPU profile is not necessary as long as the target host supports the currently assigned profile. Therefore, ensuring the destination host has sufficient compatible resources is the required condition.

Duringfailover in Nutanix Disaster Recovery, VMs retain theirstatic IPsbut maylose DNS settingsif the network configuration at the DR site is different from the primary site.

Option B (Create custom in-guest scripts) is correct:

Custom scriptsallowWindows or Linux VMs to restore DNS settings automaticallyafter failover.

These scripts can be executed usingpost-failover automationin Nutanix DR policies.

Option A (Self-Service Restore) is incorrect:

Self-Service Restore is used forend-user recovery of deleted files, not for network settings.

Option C (nncli tool) is incorrect:

Thenncli toolis used fornetwork troubleshooting, but it does not automatically restore DNS settings.

Option D (Configure a Protection Domain) is incorrect:

Protection Domains definereplication policies, but they do not fix DNS settings after failover.

Reserved Capacity settings define how much storage is exclusively allocated for a specific container.

Option B (Reserved Capacity is too high) is correct:

If too much space is reserved for a container, it can report "out of space" while the cluster still has free capacity.

Options A, C, and D are incorrect:

Advertised Capacity, Compression, and RF settings do not directly cause storage exhaustion unless misconfigured with Reserved Capacity.

The most efficient way to move a VM’s storage to a container that has different storage optimization policies (like compression) is to perform aVM migrationto the target container. This operation ensures that all the VM’s vDisks are moved to the destination container and allows leveraging the configured optimizations on the Production container.

From theNutanix Enterprise Cloud Administration (ECA)course materials:

“VM migration to another storage container in Nutanix Prism Central is supported and can be performed with minimal disruption. When moving a VM to a new container, it inherits the storage optimization policies of that container, including compression, deduplication, and encryption.”

Furthermore:

“Migrations can be initiated at the VM level in Prism Central or Prism Element. This is the most streamlined method to ensure all vDisks for a VM are moved together, preserving data integrity and performance characteristics.”

Recreating the VM or vDisks would be cumbersome and require manual data copying, introducing potential risks and downtime.

Snapshots that are part of an active recovery operation cannot be deleted until the process is completed or manually canceled.

Option A (Active recovery in progress) is correct:

Nutanix does not allow deletion of snapshots ifthey are being used in an ongoing recovery process.

The administrator shouldverify whether the snapshot is currently part of a Protection Domain or Disaster Recovery (DR) plan.

Option B (Ransomware encryption) is incorrect:

Nutanix snapshots are immutable by defaultandcannot be encrypted by external threats.

Option C (Approval policy denial) is incorrect:

Snapshot deletionsdo not require manual approval, unless controlled by an external workflow system.

Option D (Snapshot corruption) is incorrect:

Nutanixuses checksums to prevent corruption, so snapshots cannot besilently damaged.

Within Nutanix Recovery Plans, IP address transformations are handled through an automated mechanism known asIP Address Mapping. The documentation describes two methods: fixed mappings and offset-based mappings.

Offset-based mapping allows administrators to maintain consistent host identity attributes such as the last octet while shifting only the subnet portion during DR failover. The internal guidance states, “Offset-based mapping enables automatic recalculation of target IP addresses using offsets applied to source subnets, allowing preservation of host-specific octets across networks.”

Custom scripts are possible but not recommended because Nutanix already provides a built-in, automated IP transformation system. Editing IPs inside VMs after failover is operationally expensive and defeats the purpose of an orchestrated DR workflow. IPAM is useful for dynamic IP assignment but does not preserve the last octet mapping requirement.

Thus, Offset-based IP mapping is the correct mechanism for this requirement.

A cluster runway below 365 days does not necessarily indicate an issue if Intelligent Operations determines that workloads are sustainable.

Option B (Because new workloads are sustainable) is correct:

Nutanixanalyzes resource trendsand marks clusters as healthyif new workloads are within projected capacity.

Option A (Storage Runway is still good) is incorrect:

Storage isone component, butCPU and memoryalso affect runway calculations.

Option C (Recommended resources) is incorrect:

Recommendations help optimize capacity, butdo not define cluster health.

Option D (Target is 1 month) is incorrect:

The scenario’s target window does not impact the actual runway calculation.