Huawei H14-231_V1.0 Exam Prep
HCIP-HarmonyOS Application Developer V1.0 (Page 47 )

• Answer: No.

• Why:

• If you need such an assessment while controlling costs, you’d generally pursue a paid MCS engagement or another option outside of the basic Premier entitlement.

• A: Daily involvement is unnecessary and may not solve the availability problem.
• C: Clarifying all requirements at the start conflicts with agile’s iterative refinement.
• D: Simply reviewing based on availability leaves the problem unresolved and allows rework to continue.

• Primary and core nodes: Use On-Demand Instances because the workload is business-critical. These nodes manage the cluster and store/process HDFS data.
• Task nodes: Use Spot Instances in an instance fleet. Task nodes are suitable for interruption because they do not hold essential cluster data and can be replaced or diversified across instance types.
• Terminate the entire cluster after processing: The job runs only about six hours each morning, and EMRFS stores data in Amazon S3. Keeping the cluster running for the rest of the day would waste money.

• A: Using Spot for primary and core nodes risks interruption of the critical cluster.
• C: All On-Demand is reliable but unnecessarily expensive; terminating the cluster helps, but Spot task nodes provide greater savings.
• D: Leaving primary and core nodes running after the task finishes continues to incur costs. Savings Plans also are less appropriate for this intermittent workload.

• Issuer: Identifies the party issuing a SAML message, commonly the IdP in the SAML assertion. It is not the Salesforce setting used to distinguish Salesforce from other service providers.
• Identity Provider Login URL: Specifies where Salesforce sends users for authentication; it does not identify Salesforce.
• SAML Identity Location: Specifies where the user identity is found in the SAML assertion, such as the subject or an attribute.

kusto 
Event | where EventType == "error"

• == is the KQL equality operator.
• -eq is a PowerShell operator, not KQL.
• is is not the correct equality operator in this context.

text 
Event | where EventType –eq "error"

• Event | search "error" — valid, broad search.
• search in (Event) "error" — valid, broad search.
• Event | where EventType == "error" — valid, targeted filter.

• Which Security policy matches
• Which NAT rule/translation is selected
• Which PBF rule applies
• Which route is used

text 
test security-policy-match ... 
test nat-policy-match ... 
test pbf-policy-match ... 
test routing fib-lookup ...

• B — Prompts and suggestions retained for 28 days
• C — User engagement data kept for two years

• The key distinction is between content data—your prompts, code context, and generated suggestions—and engagement data, such as usage activity.
• Do not confuse retention with training: enterprise Copilot data is generally not used to train GitHub’s models without appropriate authorization.
• For a current exam, verify the policy version cited by the exam provider. The key’s C is likely correct, but B should be treated cautiously and may no longer reflect the current policy.

• Cutover: The old system is replaced immediately. It may be fast, but any failure can cause significant disruption.
• Phased: The system is introduced in stages, which reduces implementation risk but may prolong the transition.
• Pilot: The system is first deployed to a limited group or location. This is useful for testing but does not necessarily minimize downtime for the entire organization.

• Remote and global access: Employees can authenticate from anywhere, not just a specific location.
• Seamless login: The device can authenticate in the background, reducing repeated password or MFA prompts.
• Minimal equipment: It uses devices employees already have, rather than requiring separate hardware.

• Geotagging: Identifies location but is not a complete authentication method and can be spoofed.
• Smart cards: Can provide strong authentication, but require cards and often readers, adding equipment and user steps.
• Time-based logins: Restrict access by time but do not verify the user or device adequately.

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

• Amazon Cognito is designed for customer-facing apps to handle user sign-up, sign-in, and access control, and it can federate identities from social providers (Facebook, Google, etc.) or enterprise IdPs via SAML/OpenID Connect.
• You can configure a Cognito User Pool and connect social identity providers, then use tokens (JWT) to authorize backend API calls.

• AWS Directory Service is for connecting your AWS apps to an existing directory (like Active Directory) for enterprise users, not social login for customer apps.
• AWS IAM is for managing access to AWS resources, not end-user authentication for your website.
• AWS IAM Identity Center (AWS SSO) provides SSO for AWS accounts and enterprise apps, not typical social logins for consumer-facing websites.

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.

Why

cmd 
PowerShell.exe -ExecutionPolicy Bypass -File C:\Scripts\ConfigureVM.ps1

Why the other options are less suitable

• GPO logon script: Runs only when a user logs on and may not run during initial VM provisioning.
• GPO startup script: Can work, but requires the VM to be joined to the domain and the policy to be applied. It is also normally evaluated at each startup.
• Place scripts in a VHD: Merely placing scripts on a disk does not cause them to execute.

1. Start with the Customer table.
2. Use Merge Queries and select the Address table.
3. Match Customer[Address ID] to Address[Address ID].
4. Use a Left Outer join so every customer is retained.
5. Expand only City, State/Region, and Country.

• Append adds rows vertically; it is for stacking similarly structured tables.
• Group By summarizes rows and does not retrieve address columns.
• Transpose swaps rows and columns and is unrelated to table relationships.

• VM CPU, memory, disk, and network usage
• Storage transactions and latency
• App Service response time
• Database DTU or CPU utilization

• Azure Traffic Analytics analyzes network traffic flows and security patterns; it is not the general infrastructure metrics tool.
• Azure Activity Log records subscription-level control-plane operations, such as resource creation, deletion, or configuration changes.
• Azure Advisor provides recommendations about cost, security, reliability, performance, and operational excellence, but it is not the primary tool for investigating live metrics.

• Why: ADS is designed to collect information about on-premises environments to plan migrations. It inventories details like hostname, IP address, MAC address, OS, hardware, and installed software, plus dependency mappings. This data helps you understand your current environment before moving to AWS.

• How it differs from the other options:

• Practical use: Install the ADS agent on on-prem hosts to collect data, then view the inventory in Migration Hub to inform migration planning and sequencing.

• Disable default accounts: Default or unused accounts may have predictable names or credentials and can be abused by attackers. They should be disabled, removed, or secured with strong credentials where necessary.
• Remove unnecessary services: Every running service can contain vulnerabilities or provide an entry point. Removing services the server does not need reduces exposure.

• Add the server to the asset inventory: Important for asset management, but it does not directly harden the system.
• Document default passwords: Default passwords should be changed or disabled—not recorded for continued use.
• Send logs to the SIEM: Supports monitoring and detection, rather than directly reducing the attack surface.
• Join the corporate domain: A deployment/configuration decision, not inherently a hardening measure.

• Microsoft Teams: Connects to Teams-related data, but it isn’t the primary connector for the Power Apps data tables.
• Personal Analytics: Provides personal productivity insights, not application data.
• SQL Server database: Only applies if the app explicitly uses SQL Server as its data source.
• Dataflows: Used for preparing and centralizing data, not as the normal direct connection to a Power Apps app.

• Answer: D. Select an IdP

• Why: To reduce the number of credentials across multiple SaaS apps, implement a single sign-on approach via an Identity Provider. The first step is choosing the IdP; once selected, you can enable SAML (A) or OAuth as supported by apps. Password vaulting (C) is not a true SSO solution, and B is not the foundational step.

1. The sender hashes the original message and sends the message plus its hash.
2. The receiver applies the same hashing algorithm to the received message.
3. The receiver compares the newly calculated hash with the sender’s hash.
4. Matching values indicate that the message was not altered in transit.

• A binary image is not the normal description of a hash result.
• Using a different algorithm produces a different type of digest, so the values cannot be directly compared.
• Hashing verifies integrity, but by itself does not prove who sent the message. Digital signatures or MACs address authentication and integrity together.

• Correct answer: D. AWS CloudShell

• Why: AWS CloudShell is a browser-based shell that runs in the AWS Console and uses the current authenticated session. It provides a pre-authenticated, ready-to-use command-line environment directly from the Management Console, with AWS CLI and common tools installed.

• Why the other options aren’t correct:

• Conserve public IPv4 addresses: IPv4 addresses are limited, so many internal devices share a smaller number of public addresses through NAT.
• Reduce direct exposure: Private addresses are not directly routable from the public Internet, which helps reduce unsolicited access to internal devices.

• Honeypots: Decoy systems or services designed to attract attackers. Legitimate users should not access them, so activity on a honeypot is a strong indicator of unauthorized activity. Security teams can also observe attacker behavior.

• DNS sinkhole: Redirects requests for known malicious domains to a controlled internal server or blocks them. If an infected workstation attempts to contact command-and-control infrastructure, the sinkhole records the request and helps identify the compromised device.

• Tokenization: Protects sensitive data by replacing it with tokens.
• CI/CD: Automates software development and deployment.
• Threat modeling: Identifies potential risks before or during system design.
• Data obfuscation: Makes data harder to understand, but does not detect intruders.

• Numerical flexibility: Adjusting the number of employees, such as using temporary, part-time or contract staff.
• Temporal flexibility: Varying when employees work, such as through flexitime, overtime or different working hours.
• Shift system flexibility: Changing work patterns or shift arrangements; it is not specifically about moving between tasks.

• A — Custom Button: A button can launch a flow, typically by passing the flow’s URL and record context.
• D — From a Process: A Process can invoke a flow using an Apex action configured for flow invocation. However, this is automation-triggered, not directly accessed by a user.
• B — Quick Action: In current Salesforce functionality, a Flow Quick Action can launch a screen flow directly from a record page. This makes B a valid modern method.
• C — Visual Workflow Launcher: This is not generally listed as a standard access method in current Salesforce terminology; Salesforce commonly uses the Flow component on Lightning pages instead.

• Use one Azure AD directory for the organization.
• Separate divisions with subscriptions and/or resource groups.
• Assign each division’s administrator appropriate Azure role-based access control (RBAC) permissions, scoped to their subscription or resource group.

• Drops packets when traffic exceeds a certain bitrate: This describes traffic policing, not shaping.
• Fragments large packets and queues them: Shaping does not fragment packets as its primary congestion-control action.
• Drops packets randomly from lower-priority queues: Packet dropping may occur if a shaping queue becomes full, but it is not the defining behavior.

• Shaping: buffers and delays excess traffic.
• Policing: drops or marks traffic that exceeds the configured rate.

• Idioma: “Responda em português.”
• Tamanho: “Responda em até três frases.”
• Formato: “Use uma lista com três recomendações.”
• Objetivo: “Recomende produtos com base nas necessidades do cliente.”

• Mudar o tamanho do LLM: pode alterar capacidade e custo, mas não garante idioma ou respostas curtas.
• Aumentar a temperatura: aumenta a criatividade e a aleatoriedade; não controla diretamente o tamanho ou idioma.
• Aumentar o Top K: permite considerar mais tokens prováveis, aumentando a variedade; também não é o mecanismo principal para controlar idioma ou comprimento.

• Authentication: Verifies a user’s identity, such as username and password.
• Authorization: Determines what the authenticated user is allowed to access.
• Accounting: Records connection and usage details, such as login time or session duration.

• CIA: Confidentiality, integrity, and availability are broad security objectives, not a specific RADIUS function.
• ACL: An access control list contains permit/deny rules on systems or network devices. RADIUS can support access decisions but is not itself an ACL.
• PEM: Privacy-Enhanced Mail is also associated with certificate and key encoding formats; it is unrelated to RADIUS’s primary purpose.

• vSmart controls the overlay control plane. It uses OMP to exchange routing information, distribute policies, and determine how WAN Edge devices reach one another.
• vManage is the centralized management and configuration platform.
• vBond is the orchestrator. It helps devices authenticate, discover controllers, and traverse NAT during onboarding.
• APIC-EM is not the SD-WAN control-plane component described here.

• Azure Resource Manager (ARM) templates define Azure resources in a declarative JSON file.
• You can deploy the same template repeatedly for each business unit, ensuring that identical resources are created consistently.
• Templates reduce manual administrative effort and support repeatable, automated deployments.
• Parameters can customize values such as names, regions, and sizes while keeping the overall resource configuration the same.

• B. Data loss prevention (DLP): Helps prevent sensitive data from being copied, emailed, or exfiltrated. It is not the primary control for protecting a stolen laptop’s stored data.
• C. Operating system hardening: Reduces vulnerabilities by disabling unnecessary services and applying secure settings, but it does not necessarily protect the files if the disk is accessed directly.
• D. Boot security: Helps ensure the device starts only through trusted software or approved processes. It supports platform integrity but does not itself encrypt stored files.

• Árvores de decisão: usam regras sequenciais, como “se característica X > valor, siga para este ramo”. São fáceis de visualizar e explicar. Atendem bem a problemas de classificação e regressão com alta interpretabilidade.

• Regressão linear: prevê um valor numérico contínuo, como preço, custo ou temperatura. Não é a escolha principal para classificar genes em categorias.

• Regressão logística: calcula a probabilidade de uma categoria. Pode atender à classificação, inclusive multiclasses, mas sua explicação costuma ser menos intuitiva que uma árvore para documentar decisões.

• Redes neurais: atendem a tarefas complexas, como imagens, texto e padrões não lineares. Porém, são menos interpretáveis, funcionando mais como uma “caixa-preta”.

• Recovery procedures actually work
• Recovery time and recovery point objectives can be met
• Staff understand their responsibilities
• Contact details, dependencies, and technical configurations are accurate
• Gaps or conflicts exist in the plan

• Not version-controlled: Creates a risk of using an outdated copy, but the plan might still be effective.
• Contact information needs updating: This is a specific weakness that can be corrected, often identified during testing.
• Not approved by senior management: Approval is important for authority and resource commitment, but an untested plan presents the most direct risk that recovery will fail when needed.

• The Balanced Scorecard translates an organization’s vision and strategy into a set of concrete objectives and metrics across four perspectives (financial, customer, internal processes, learning & growth). This framework explicitly links IT goals to business goals and provides a way to measure and monitor alignment over time.

• Enterprise architecture (EA): Great for governance, standards, and roadmaps to ensure IT assets support business needs, but it’s more about structure and alignment at design time rather than directly measuring ongoing alignment of goals.
• KPIs: Useful metrics, but they don’t by themselves provide a full framework to ensure IT goals are aligned with organizational strategy.
• Enterprise dashboard: A visualization tool for metrics; it helps report status but doesn’t inherently establish or assess alignment.

• IaaS: You manage the virtual machine’s operating system, configuration, applications, and data. Azure manages the physical infrastructure and virtualization platform.
• PaaS: You deploy applications without managing the underlying operating system or servers.
• SaaS: You consume a complete application managed by the provider, such as Microsoft 365.

• A — VARIANT "null" values are not the same as SQL NULL: Correct.

• B — Frequent, single-row DMLs: Incorrect.

• C — Validate data before loading into the target table: Correct.

• D — Use staging tables to manage MERGE statements: Correct.

• Key difference: DirectQuery leaves data in the on-prem SQL Server and queries it live. That means every visual request can trigger online processing on the source, which can be slower and adds load on the on-prem system. In contrast, Import loads data into the Power BI data model, so visuals render from the in-memory engine (faster).

• Why that helps with the requirements:

• Why not A or B: Both rely on live data via DirectQuery, which contradicts the goal to minimize online processing and visuals performance.

• Why not D: It uses Import, but refreshing hourly adds unnecessary processing and complexity when daily refresh already satisfies currency needs.

• SageMaker endpoint: Not required because the model is being used through Amazon Bedrock.
• SageMaker Model Registry: Used for managing SageMaker models, not for making a Bedrock custom model available.
• Grant access in Amazon Bedrock: IAM permissions may still be needed, but granting access alone does not provide the required inference capacity.

• A vulnerability scanner automates discovery of known vulnerabilities and misconfigurations across systems. It can contribute to a supply-chain assessment.
• A penetration test actively attempts exploitation and is usually limited to an agreed scope.
• SCAP standardizes vulnerability and configuration assessment data; it is not the analysis itself.
• Illumination tool is not a commonly defined CompTIA Security+ term.

• The problem describes the class updating field-level security on some profiles. To prevent updating fields that are not updateable for the current user, you should check each field’s updateability before making changes. Use DescribeFieldResult.isUpdateable() (e.g., via Field.describe() on each field) to guard updates.

• A and D (With Sharing): Running a class with Sharing affects record visibility, not whether a field can be updated by a user. It doesn’t prevent updates to fields the user shouldn’t modify.
• C (WITH SECURITY_ENFORCED in SOQL): This enforces FLS/FRC during queries, but it doesn’t control whether the Apex code updates fields or modifies permissions. It’s not addressing the update behavior directly.

• 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.

• The connecting host keeps the private key securely.
• The destination host stores the corresponding public key in its authorized keys.
• Authentication can occur without a person entering credentials each time.
• SSH also provides encrypted communication and host authentication.

• Biometric: Requires a human user and is difficult to automate.
• Smart card: Often requires user interaction or card access.
• Hard-coded password: Unsafe because passwords stored in scripts or applications can be exposed, reused, or difficult to manage securely.

• Entradas grandes, de até aproximadamente 1 GB.
• Processamentos demorados, que podem levar até cerca de 1 hora.
• O cliente envia a solicitação e consulta o resultado depois, sem precisar manter uma conexão aberta durante todo o processamento.

• Real-time inference: indicada para respostas imediatas, com entradas menores e processamento rápido.
• Serverless inference: adequada para cargas variáveis e solicitações menores; não é ideal para processamento longo e arquivos grandes.
• Batch transform: processa grandes volumes em lote, mas não atende à necessidade de respostas próximas do tempo real.

• Batch processing, such as scheduled data transformations
• Streaming processing, such as continuously ingesting events

• Manipulating data with multiple languages: Mainly a benefit of Databricks and Spark.
• Real-time notebook collaboration: A workspace/notebook feature.
• Alerts for query failures: A Databricks SQL or job-monitoring feature.
• Distributing complex operations: Primarily a Spark compute capability.

• The two correct options are:

• The two incorrect options:

• Sending calls to available agents quickly
• Balancing interactions across agents
• Preventing calls from being handled manually one at a time

• Workforce Management: Forecasts demand and schedules enough staff; it supports wait-time reduction but does not directly distribute calls.
• Skill-based Routing: Routes calls based on agent skills and may improve the customer experience, but the question is asking about the core feature that distributes calls efficiently.
• IVR: Lets callers navigate menus and self-service options; it does not primarily assign calls to agents.

• Low usage during the first three weeks
• Very high usage during the last week

• High availability: Keeps services running despite failures.
• High latency: Means slow response times; it is not a benefit.
• Load balancing: Distributes traffic across resources but does not specifically address scaling resources up and down.