Huawei H13-321 Exam Actual Questions
HCIP-AI-EI Developer V2.0 (Page 3 )

1. Ingestion Lambda receives requests from API Gateway and places messages in an SQS queue.
2. Processing Lambda is triggered by the queue and loads records into Aurora PostgreSQL.

• Decoupling: API request handling is separated from database loading.
• Buffering: SQS absorbs bursts when incoming traffic exceeds the database’s processing capacity.
• Controlled concurrency: Configure the SQS-triggered Lambda’s concurrency and batch size to avoid overwhelming Aurora or exhausting database connections.
• Automatic retries: Messages that fail processing can return to the queue and be retried. A dead-letter queue can capture persistent failures.
• Lower operational effort: The solution remains serverless and avoids managing EC2 servers or Kubernetes clusters.

• A: EC2 and Tomcat add server-management overhead.
• B: DynamoDB/DAX would require changing the database model and does not solve the Aurora ingestion design.
• C: SNS is useful for notifications and fanout, but SQS is better for durable buffering and backpressure in this producer-consumer workflow.

• TCP is connection-oriented. It establishes a connection before data transfer using a three-way handshake (SYN, SYN-ACK, ACK), enabling reliable delivery, ordering, and flow control.

• UDP is connectionless. It sends datagrams without a prior connection and provides no guarantee of delivery, order, or protection against duplicates; any reliability is up to the application.

• B incorrectly states UDP uses acknowledgment packets; UDP has no built-in ACKs.
• C wrongly claims UDP provides reliable transfer and that TCP is connectionless.
• D misstates framing bits; neither protocol uses the listed TCP/UDP handshake bits in frames.

• Answer: B — Improve employee training and awareness

• Why this is correct:

• Why the other options are less effective here:

• Quick practical note:

• 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.

• The correct setting to configure is the Enrollment Status Page (ESP) profile.
• Why: ESP tracks the enrollment progress and logs during Autopilot provisioning. You can enable log collection within the ESP policy so that, if ESP times out, the user can collect and share the logs with support.
• Optional enhancement: In the ESP policy (or the Autopilot diagnostics settings), you can enable:

• Automatic enrollment settings: control how devices auto-enroll, not log collection.
• Windows Autopilot deployment profile: controls deployment steps but not ESP log collection.
• Device configuration profile: applies settings but doesn’t provide ESP log collection mechanics.

• Correct answer: A. Email templates

• Snippets are reusable content blocks that you insert into email content, and they require an email template (or at least an email draft) to render.
• You can store region-specific footers as snippets and include them in a template, but there would be nothing to render the snippet into without a template.
• The other options aren’t prerequisites for using snippets:

• IaaS provides virtualized infrastructure, including VMs, disks, and networking. You manage the guest operating system and software installed on the VM.
• PaaS provides a managed platform for deploying applications without managing the underlying VMs or operating systems. Examples include Azure App Service and Azure Functions.

• Startup scripts run at computer startup, before any user logs on, making them ideal for machine-wide configuration on each new VM.
• They execute under the Local System account, which is appropriate for initial setup tasks.
• Linking a GPO to the OU ensures every new VM in that domain automatically receives the configuration—great for scalability.

• A) SetupComplete.cmd runs only once, right after Windows Setup, not on every boot, so it isn’t ideal for provisioning multiple VMs consistently.
• B) Logon scripts run per user, not per machine, so they aren’t reliable for initial VM configuration before a user signs in.
• D) Placing scripts in a VHD doesn’t automatically execute them.

• 6-phone boxes: 6x
• 8-phone boxes: 8x

• View/inspect configuration: Possible.
• Modify the installed application or its S-Controls: Typically restricted in a test-drive org.

• Voice devices ? VLAN 10
• Data devices ? VLAN 20
• SVI for VLAN 10 ? 192.168.10.1
• SVI for VLAN 20 ? 192.168.20.1

• A: Describes a physical trunk interface, not an SVI.
• B: An SVI can provide management access, but that is not its primary definition here.
• D: SVI does not compensate for insufficient physical ports; it is a logical interface.

• 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.

• 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.

• Windows 10 VMs
• Windows Server 2012 or later VMs
• Running VMs—they do not need to be shut down
• Debian 8.2+ VMs, assuming the specific version is supported
• Stopped or deallocated VMs

• S3 Lifecycle rules automate actions such as transitioning objects to different storage classes or deleting old objects.
• S3 bucket policies control access permissions; they do not preserve earlier object versions.
• S3 server-side encryption protects data confidentiality by encrypting objects at rest, but it does not prevent deletion or overwriting.

• Accidental deletion or overwriting ? S3 Versioning
• Unauthorized access ? bucket policies and IAM
• Data encryption ? server-side encryption

• 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.

• A private IP address on the virtual network
• An associated public IP address

• Correct answer: A. System characterization

• Why the other options are not correct:

• 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:

• 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.

• 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.

• Who performed the action
• What action occurred
• When it occurred
• Where it originated
• Whether it succeeded or failed

• Investigating suspicious activity: Important, but investigation depends on having adequate audit data first.
• Storage allocation: Necessary for retention, but storage does not help if the records lack meaningful details.
• Actions after audit failure: Part of operational planning, not the primary assessment of the application’s audit capability.

• Why Ishikawa:

• Why not the others:

• Correct answer: C: Amazon Comprehend.

• Why: The library wants to classify books based on their text content. This is an NLP (natural language processing) task. Amazon Comprehend is AWS’s managed NLP service that can perform content classification (including creating custom classifiers) and extract meaningful information from text. The other services are not focused on text classification:

• Quick note: In practice, you’d store the books in S3, extract text if needed (e.g., from PDFs with Textract), and then use Comprehend to classify the documents into topics or genres.

• Import mode loads the data into the Power BI model. Visuals query the in-memory model, which generally provides faster calculation and rendering than DirectQuery.
• Import mode also minimizes online processing because report interactions do not send queries back to the dataflow or SQL Server.
• A daily refresh can load data through the previous day, satisfying the freshness requirement without unnecessary hourly processing.

• DirectQuery keeps querying the data source or dataflow during report use, increasing online processing and potentially slowing visuals.
• Adding a gateway enables connectivity for on-premises sources, but it does not remove the performance disadvantages of DirectQuery.
• An hourly Power Automate refresh is unnecessary when the requirement is only data through the previous day and creates additional processing overhead.

• The stage has a default file format defined (e.g., when you create the stage with FILE_FORMAT = (...)), and Snowflake will use that default.

• You use a named file format attached to the stage, or you specify an inline format in the COPY command, e.g., COPY INTO my_table FROM @my_stage FILE_FORMAT = (TYPE = 'CSV');

• Use a stage default: omit FILE_FORMAT in COPY.
• Or rely on a named/inline format: specify FILE_FORMAT in COPY or set a format on the stage.

• Port 515: LPD/LPR line-printer service
• Port 631: IPP — Internet Printing Protocol
• Port 9100: JetDirect/RAW printing, commonly used by network printers

• Linux machine: Linux could run these services, but the three printer-specific ports strongly indicate a printer.
• Router: Routers may use Telnet and HTTP, but normally would not expose ports 515, 631, and 9100 together.
• Windows machine: Windows can share printers, but this particular service combination is more characteristic of a network printer’s embedded operating system.

• A assigned without var becomes a global variable (in non-strict mode). So after myFunction(), a = 5 is accessible.
• b is declared with var inside the function, so it’s local to that function (function-scoped). It’s not defined in the outer (global) scope.

• console.log(a) prints 5.
• console.log(b) throws a ReferenceError: b is not defined.

• 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.

python 
import azure.cognitiveservices.speech as speechsdk 


speech_config = speechsdk.SpeechConfig( 
    subscription="YOUR_KEY", 
    region="YOUR_REGION" 
)

Important Azure Speech SDK classes

• SpeechConfig

• AudioConfig

python 
  audio_config = speechsdk.audio.AudioConfig( 
      use_default_microphone=True 
  )

• SpeechRecognizer

python 
  recognizer = speechsdk.SpeechRecognizer( 
      speech_config=speech_config, 
      audio_config=audio_config 
  )

• SpeechSynthesizer

• AudioOutputConfig

 Bogotá, Colombia