Nutanix NCM-MCI-5.20 Exam Actual Questions
Nutanix Certified Master - Multicloud Infrastructure (NCM-MCI) 5.20 (Page 2 )

• On-prem you generalize and capture the VM as a VHD.
• Upload the VHD to Azure with Add-AzVhd.
• Register the VHD as an image in Azure with Add-AzImage (or New-AzImage) so it appears as a selectable image.
• Create new VMs from that image (e.g., with New-AzVM -Image ...).

• Correct answer: A) Hashing

• Why: Hashing produces a fixed-size digest of the software. If the final build is altered in any way, the hash will change, enabling you to detect tampering by comparing the stored digest with a freshly computed one.

• Why not the others:

• Answer: C — Spot Instances

• Why: The workload is a test environment that can be interrupted and does not need to run continuously. Spot Instances let you bid on unused EC2 capacity at a deep discount, making them the most cost-effective option for interruptible workloads.

• Why not the others:

• Quick tips:

• Correct answer: A. Inbound data transfer from the internet

• Why: AWS does not charge for data transferred into AWS from the internet. Inbound data transfer is free, regardless of the amount (in this case, 2 TB). The other options involve data leaving AWS or moving between AWS regions/AZs, which incur costs:

• Question 142: Security governance is MOST associated with which IT infrastructure component? Network / Application / Platform / Process
• Answer: D. Process

• Security governance is about how decisions are made, accountability, and oversight to ensure security objectives align with business goals. These are implemented through governance processes (policy development, risk management, assurance, monitoring, escalation, etc.).
• The other options (Network, Application, Platform) are concrete IT components; governance affects them, but it’s exercised primarily through the processes that govern how those components are managed and controlled.

• In governance-related questions, focus on the decision-making, accountability, and control processes rather than the underlying technology components.

• The requirement is a fully managed file server that natively supports Microsoft workloads and file systems and uses the SMB protocol. FSx for Windows File Server is built specifically for Windows workloads, provides native SMB file shares, and supports Windows permissions/Active Directory integration.
• Why the others don’t fit:

• Review iteration length: Changing duration does not resolve unclear requirements.
• Limit work in progress: Useful when excessive multitasking is the problem, but it does not directly clarify requirements.
• Review individual performance: The issue is a process and backlog-quality problem, not necessarily an individual performance problem.

• User1 can sign in because the account is cloud-only. It does not depend on the on-premises domain.
• User3 can sign in because the account uses Password Hash Synchronization (PHS). Azure AD has a synchronized password hash and can validate the sign-in even when connectivity to on-premises Active Directory is unavailable.
• User2 cannot sign in because the account relies on Pass-through Authentication (PTA). PTA sends the authentication request to an on-premises PTA agent, which must contact a domain controller. With the internet connection from on-premises lost, that validation cannot occur.

• A) You can only apply a single template BOM to a service object.

• C) You can modify or delete lines in a BOM template regardless of whether the template has been associated to a service object, or not.

• B) You can apply many template BOMs to a service object — false; typically only one template per service object.
• D) You can modify/delete lines only if not associated — false; you can modify templates even after association (per C).

• A push endpoint behind a load balancer handles massive fan-in from many devices while distributing load across servers.
• A container cluster (e.g., Kubernetes) provides scalable, flexible processing for ingestion and orchestration of services.
• Cloud Pub/Sub enables durable, scalable streaming of the raw vehicle data to downstream analytics, making real-time/near-real-time analysis feasible for centralized querying by analysts.

• Vehicles push data to the endpoint (HTTP) behind a load balancer.
• Ingestion services run in a container cluster and publish data to Cloud Pub/Sub.
• Pub/Sub streams data to analytics processing (e.g., Dataflow) and storage (e.g., BigQuery) for central querying by analysts.

• They don’t provide scalable, real-time streaming ingestion and centralized querying at the required scale.

• What the scenario tests: How monitoring paths on a Universal Forwarder (UF) behave when you deploy an app via the Deployment Server.
• How monitoring is configured: Log paths to monitor are defined in inputs.conf (within apps/local on the UF). Splunk on the UF merges inputs from all apps and local config.
• Key point: Deploying a new app that adds a monitor for a log file does not typically remove existing monitors. The UF will continue monitoring any previously configured paths and will add the new ones from the deployed app.

• Correct answer: C) /var/log/maillog and /var/log/messages.

• In the AWS shared responsibility model, AWS manages the security of the “infrastructure,” including the physical hardware and underlying virtualization.
• The customer is responsible for everything else in the cloud stack: the guest OS on EC2, the NoSQL database software running on it, data, patching the OS, and configuring access controls like security groups.
• So, for a self-managed NoSQL database on EC2, AWS would handle the physical hardware, while you would patch the guest OS and manage DB availability, backups, and security.

• Correct answer: D and E (Permanent table and Materialized view)

• Why: Time Travel and Fail-safe apply to permanent objects and materialized views. If a permanent object or a materialized view is dropped, you can recover it within the Time Travel retention period; after that, Snowflake’s Fail-safe provides a further, limited recovery window.

• Why the others are incorrect:

• The missing piece is to configure an event source mapping between the DynamoDB stream and the Lambda function. Enabling DynamoDB Streams alone doesn’t trigger the function—you must wire the stream to Lambda so events invoke the function.
• Note that changing StreamViewType (A) only affects what data is delivered (e.g., NEW_IMAGE) and does not trigger invocations. Options C and D are not required for invocation: you don’t need SNS, and increasing the timeout won’t enable the trigger.

• Catalog Items are the basic units users can request from the Service Catalog.
• Order Guides are bundles that group related catalog items so a user can place multiple items in one order.
• Record Producers are catalog items that, when submitted, create a new record in a specified table (for example, creating a new Incident or a custom record).

• Answer: No (the solution proposing an Application Security Group does not meet the goal)

• Why: An Application Security Group is used to simplify NSG rules for VMs, not to enable or configure service endpoints. The requirement is to allow the VM and its containers to reach Azure Storage and Azure SQL via the service endpoint, which is achieved by properly configuring the service endpoints and related networking (NSG and DNS), not by creating an ASG.

• What to do instead to meet the goal:

• Quick takeaway: Don’t rely on an ASG for this scenario. Focus on enabling service endpoints and appropriate NSG/DNS configuration to allow the VM and its containers to reach Storage and SQL.

Why B works

• AWS KMS keys are Regional resources. A normal customer managed key in Region A cannot be used directly in Region B.
• A customer managed multi-Region KMS key (MRK) has related key replicas in both Regions. The replicas share key material and key ID, although each has a Regional ARN.
• With client-side encryption, the application encrypts the data before storing it in S3. Cross-Region replication then copies already-encrypted objects, so S3 does not need to decrypt and re-encrypt them with a different Regional key.

Why the other choices are weaker

• A and C: SSE-S3 uses Amazon-managed S3 keys, not the required customer managed KMS key.
• D: SSE-KMS can work only if the solution creates and configures the appropriate KMS key or multi-Region key replica in each Region. As written, it says to create a customer managed KMS key in each Region, which implies separate keys—not the same KMS key. Replication also requires additional KMS permissions and destination encryption configuration.

• Sustainability is not a CAF perspective (it's not one of the CAF perspectives).
• Performance efficiency and Reliability are pillars of the AWS Well-Architected Framework, not CAF.

• Correct answer: A

• Why:

• Takeaway: For data exfiltration detection with ETD, opt for targeted data read audit logs on the designated resources to balance visibility and cost.

• Goal: serving a static website globally with minimal latency.
• Why C works: CloudFront is a Content Delivery Network (CDN) that caches content at many edge locations around the world. When users request the site, CloudFront serves cached copies from the nearest edge location, greatly reducing latency. It also reduces load on your EC2 origin by handling many requests at the edge.
• Why the other options aren’t as good:

• A) configure matching hold and delay timers

• B) configure matching key-strings

• C) configure matching priority values

• D) configure unique virtual IP addresses

powershell 
Get-AzureVM -ServiceName <service-name> -Name <vm-name> | 
  Set-AzureStaticVNetIP -IPAddress <private-ip> | 
  Update-AzureVM

• New-AzureRMVMConfig configures VM settings but does not itself assign the static IP.
• Set-AzureSubnet is not the appropriate cmdlet for assigning a VM’s private IP.
• The Azure portal option mentioned in the question was not the intended method for this older deployment model.
• Changing settings in Windows Network and Sharing Center is incorrect because Azure assigns the IP through the VM’s virtual network interface; manually configuring it inside the guest can cause conflicts.

• The Accrue liability on product receipt flag controls whether a liability is accrued and posted at the time of receiving the item.
• If this checkbox is unchecked, receipts won’t create postings to the Product receipt journal. Enabling it ensures the system posts inventory value and the vendor liability when the item is received.

• Go to the Item model group setup form.
• Enable (check) Accrue liability on product receipt.
• Save.

• The other option, Include physical value, affects how physical value is handled but is not the direct cause of postings to the product receipt journal. If issues persist after enabling accrual, you may need to verify related posting definitions or journal setup.

• Answer: D: Making business cases for improvement action

• Continual Improvement focuses on identifying and planning improvements and ensuring they’re funded and prioritized. Creating a business case for an improvement action is part of justifying and obtaining support/resources to implement improvements.
• A (Identifying the cause of incidents) aligns with Problem Management.
• B (Authorizing changes) aligns with Change Enablement.
• C (Logging/managing incidents that result in improvement opportunities) aligns with Incident Management, not Continual Improvement.

• IPv6 address types you’ll typically see:

• Unique Local Addresses (ULAs)

• If an address begins with fdXX:… or fc00:…, place it under “Unique Local Address” (ULA).
• If it begins with 2000::/3, place it under “Global Unicast.”
• If it begins with fe80::, place it under “Link-local.”
• If it begins with ff00::, place it under “Multicast.”

• Network Security Groups (NSGs) control network traffic to and from Azure resources.
• By applying NSGs to the web tier and the database tier (subnets or NICs), you can:

• NSGs provide the necessary granularity (source/destination, port, protocol) to enforce the desired traffic patterns between tiers.
• For easier management you can use separate subnets for each tier or, optionally, use Application Security Groups to simplify rule management.

• The correct AAA mapping (per Cisco objectives) is:

• Why the given options aren’t fully correct:

• Quick takeaway: when you configure AAA, you should conceptually map them as:

• Example commands (to reinforce concepts):

• RPO (Recovery Point Objective) — maximum acceptable data loss, measured in time. It specifies how far back in time you can tolerate data loss. Example: RPO of 2 hours means backups must occur at least every 2 hours.

• ARO (Annualized Rate of Occurrence) — expected frequency of a threat occurring per year. It estimates how often a risk is likely to happen on average (used in risk calculations).

• MTTR (Mean Time To Recover) — average time to recover/restore service after an incident. It includes detection, repair, and restoration time, and helps gauge downtime and alignment with RTO.

• Answer: Internal load balancers (ILB) — option C.

• An ILB has a frontend IP address that must be a private IP within the subnet’s address space. You pick this IP when you create the ILB, and it can be Static or Dynamic.
• Other options don’t require a per-subnet IP:

• Answer: Record Producer (option D)

• Why: In ServiceNow HR Service Delivery, to make an HR Service usable from the Employee Service Center (self-service portal), there must be a way for employees to submit the request. A Record Producer provides the employee-facing form that creates the underlying HR Case when submitted. Without a linked Record Producer, the HR Service wouldn’t offer a submit form in the Employee Center.

• What the other fields are generally for (not required for exposure):

• Quick check: Look at the HR Service definition and ensure a Record Producer is associated so employees can submit requests from the Employee Center.

1. Create a new AMI or copy the existing AMI while specifying EBS encryption and an appropriate AWS KMS key.
2. This creates an encrypted AMI backed by encrypted EBS snapshots.
3. Copy the encrypted AMI to the destination Region, using a KMS key available there.
4. Launch the application stack from the encrypted AMI.

• B: AWS KMS does not encrypt an existing unencrypted AMI in place. You must create an encrypted copy.
• C: AWS Certificate Manager manages TLS certificates, not EBS or AMI encryption.
• D: Enabling encryption by default affects newly created EBS volumes and snapshots; it does not encrypt an existing unencrypted AMI during copying.

• A) macOS with PowerShell Core 6.0 installed — not enough by itself (Az module must be installed as well). So not guaranteed.
• B) Windows 10 with the Azure PowerShell module installed — yes. PowerShell on Windows with Az loaded can run the script.
• C) Linux with the Azure PowerShell module installed — yes. PowerShell Core on Linux with Az can run the script.
• D) Linux with Azure CLI tools installed — no. The script is PowerShell-based (Az), not Azure CLI.
• E) Chrome OS with Azure Cloud Shell — yes. Cloud Shell provides an environment with Az available and can run PowerShell in the browser.

• To get min/max per column, you need column profiling. That’s provided by enabling the column profile.
• To actually see those min/max values, you should show the column profile in the details pane, and you also need the details pane itself enabled so you can view it.

• Enable column profile (B)
• Show column profile in details pane (C)
• Enable details pane (E)

• Show column value distribution (D) shows distribution shape but isn’t required to get min/max.
• Show column quality details (D) deals with data quality metrics, not min/max.

• AWS IoT Greengrass supports local ML inference using models trained in Amazon SageMaker.
• The model and inference code run on the factory’s local server, so processing continues even when internet connectivity is unavailable.
• A Greengrass component can:

• This provides low latency and avoids sending images to AWS for every inference.

• A: Uses AWS-hosted services and therefore depends on internet connectivity. It would fail during an outage.
• C: Snowball Edge is unnecessary for this use case and adds deployment complexity. A local Greengrass server is the intended edge-inference solution.
• D: Amazon Monitron is designed for monitoring industrial equipment health, not analyzing camera images with a custom SageMaker model.

• In Spark, an executor is a JVM that can have multiple cores. Each task can consume some CPUs (spark.task.cpus).
• The executor’s resources are effectively partitioned into slots, where each slot can run one task. The number of slots per executor is roughly spark.executor.cores / spark.task.cpus.
• Therefore, multiple tasks can run in parallel within the same executor (via these slots). So the statement “Tasks run in parallel via slots” is correct.

• A: A slot is not another name for an executor; a slot is a unit inside an executor.
• B: There’s no requirement that there must be fewer executors than tasks; tasks can be scheduled over time across the available slots.
• C: An executor can run more than one core; it’s not limited to a single core.
• D: There isn’t a rule that there must be more slots than tasks; tasks can wait if slots aren’t available, and you can have equal or even fewer slots than concurrent tasks.

• Review the risk register.
• Use the previously defined risk response plan, such as assigning a backup resource, reprioritizing work, or using another qualified engineer.
• Implement the response promptly because the task is on the critical path.

• B: Revising the schedule without first applying the planned response may be premature.
• C: Excluding a required task could compromise the project’s objectives and requirements.
• D: Updating the risk and lessons learned records is appropriate, but it should happen after managing the immediate issue, not as the next primary action.

• Multi-pass wipe: Overwrites the drive’s existing data multiple times, making recovery much more difficult while preserving the drive’s functionality.
• Single-pass wipe: May be sufficient in some modern sanitization standards, but is presented here as less secure than multiple overwrites.
• Degaussing: Uses a strong magnetic field to disrupt data. It can render the drive unusable or unreliable, reducing its resale value.
• Pinning: Is not an appropriate data-sanitization method.

• Reusing features across different models and teams
• Consistent feature definitions
• Managing feature versions and metadata
• Using features for both training and inference

• SageMaker Data Wrangler: Prepares and transforms data; it is not primarily a shared feature repository.
• SageMaker Clarify: Helps detect bias and explain model predictions.
• SageMaker Model Cards: Documents models, including intended use, risks, and evaluation results.

• Answer: A. Use Amazon SageMaker Serverless Inference to deploy the model.

• Why: SageMaker Serverless Inference hosts the model and serves real-time predictions without you provisioning or managing servers. It scales automatically and handles deployment details.

• Why the others aren’t suitable:

• Quick example flow: web app ? SageMaker Serverless Inference endpoint ? model ? response.

• Why: The data is unlabeled, so you can’t train a model with known input-output pairs. Unsupervised learning discovers structure in the data by grouping similar customers into clusters or tiers without labels.
• What it does: Clustering and segmentation (e.g., k-means, hierarchical clustering, DBSCAN, Gaussian mixtures) to form meaningful groups.
• Why the other options aren’t as suitable:

• '15' is a string. With + and a string, JavaScript does string concatenation: '15' + 10 -> '1510'.
• The result '1510' is then used in a multiplication: '1510' 2. The operator triggers numeric conversion, so '1510' becomes the number 1510.
• 1510 * 2 = 3020.

• If the code were let x = (15 + 10) * 2, the result would be 50 since 15 + 10 is numeric addition.

• Create Power Query parameters for the Azure SQL server/database—or at least the database name.
• Use the parameter in the PBIX connection.
• Publish the same PBIX separately to the relevant development, test, and production workspaces.
• Set each dataset’s parameter value in the Power BI service so it points to the corresponding Azure SQL database.

• Development dataset ? DevelopmentDB
• Test dataset ? TestDB
• Production dataset ? ProductionDB

• The same PBIX is used for every lifecycle stage.
• Each stage consumes data from its matching database.
• Deployment pipelines are not required.
• Azure SQL is a cloud source, so gateway administration is generally avoided.
• Only the parameter value differs between published datasets, reducing maintenance.

• Storage accounts: storage1, storage2, and storage3
• Log Analytics workspace: Analytics3

• Azure Backup reports can send the AzureBackupReports diagnostic log to eligible storage accounts. The storage account’s subscription and region do not have to match the Recovery Services vault, so all three listed storage accounts are valid.
• The Log Analytics workspace must be in the same region as the Recovery Services vault for this configuration. Vault1 and Analytics3 are both in West Europe, making Analytics3 the valid workspace.

• Transact-SQL (T-SQL) is used to query relational data in Azure SQL Database, not telemetry data from monitoring services.
• To analyze monitoring data from Azure SQL Database Intelligent Insights and Azure Application Insights, you should use the Kusto Query Language (KQL) in Azure Monitor Logs/Log Analytics (and in Application Insights Analytics).
• Using KQL lets you query telemetry tables such as requests, dependencies, pageViews, and customEvents (from App Insights) and any integrated monitoring data you’ve ingested into Log Analytics.

• Ensure Intelligent Insights and Application Insights data is available in a Log Analytics workspace or accessible via Application Insights Analytics.
• Go to Azure Monitor > Logs (or Application Insights > Analytics) and write KQL queries, e.g.:

• A (training data, hyperparameters, stakeholder feedback) focuses on training provenance; these details are important but are typically part of pre-deployment/training records, not the primary post-deployment documentation.
• B (encountered issues, monitoring process, risks) relates to governance and monitoring rather than the core documentation you’d publish about the deployed model itself.
• C (licensing information, the team, business goals) covers governance context but not the technical traceability and performance-based record needed for ongoing maintenance.

• Ensure that only users who manage the production environment sign in to the Azure portal from a hybrid Entra-joined device and authenticate with MFA.

• Use Microsoft Entra ID Protection (Identity Protection) to enforce MFA enrollment:

• Update the existing Capolicy1 (a Conditional Access policy):

• Identity Protection MFA registration policy ensures users are enrolled in MFA (Box 1 choice).
• CA policy Capolicy1 with aGrant control of “Require MFA” enforces MFA during sign-in (Box 2 choice).
• Both work together with the hybrid-joined device requirement to satisfy the authentication/authorization rules.

• Apply the MFA registration policy to the production-management users.
• Apply the MFA grant to Capolicy1 for those same users/groups.

• Multi-factor authentication
• A secure password change for users whose credentials may be compromised

• Create and manage catalogs of approved IT services
• Govern and publish infrastructure-as-code (IaC) templates, commonly AWS CloudFormation templates
• Control which users can deploy specific products and configurations
• Apply versioning, permissions, and deployment constraints

• AWS Resource Explorer: Searches and discovers AWS resources; it does not govern IaC templates.
• AWS Organizations: Manages multiple AWS accounts, policies, and consolidated billing.
• AWS Systems Manager: Helps operate and manage deployed resources, such as patching and automation, but is not primarily a catalog for governed IaC products.