Google PROFESSIONAL CLOUD NETWORK ENGINEER Exam Prep
Professional Cloud Network Engineer (Page 3 )

• A. VPC flow logs: Capture metadata about network traffic entering and leaving VM instances. They provide visibility into traffic patterns, sources/destinations, ports, and protocols—essential for monitoring and incident response.

• B. Firewall logs: Log the actions (allow/deny) taken by firewall rules. They show which traffic was blocked or permitted, helping verify security policies and investigate anomalies.

• Cloud Audit logs: Admin activity, not per-network traffic.
• Stackdriver Trace: Application/request tracing, not raw network traffic metadata.
• Compute Engine instance system logs: OS-level logs, not network traffic telemetry.

1. Ensure BOMs can include subcomponents ? Configure an entity relationship

1. Report changes made by engineers ? Enable auditing

• Configure entity relationship
• Configure auditing

• A: Person Accounts cannot be merged directly with standard Contact records.
• C: There is no Account Setup option that automatically merges Person Account duplicates.
• D: Matching rules and duplicate rules can help identify or prevent duplicates, but they do not automatically merge Person Accounts. Also, relationship considerations do not change the basic merge capability.

• Amazon DynamoDB — Managed NoSQL database, not PostgreSQL.
• Amazon Athena — Serverless service for querying data in S3; intended for analytics, not OLTP.
• Amazon EMR — Managed cluster platform for big-data frameworks such as Hadoop and Spark.

• Help the team identify the causes of delays.
• Encourage continuous improvement through retrospectives.
• Support the team in changing its process, tools, or collaboration methods.
• Help remove impediments that the team cannot resolve independently.

• A: An impediment log may help, but simply maintaining it does not ensure the impediments are resolved.
• B: Directing the team to solutions conflicts with agile self-management.
• C: Adding impediments to the product backlog could delay their resolution and treats them like product features.

• A) configure matching hold and delay timers

• B) configure matching key-strings

• C) configure matching priority values

• D) configure unique virtual IP addresses

• AWS Audit Manager continuously collects evidence from AWS services and helps assess whether workloads comply with regulatory frameworks and internal policies. It can produce audit-ready reports.
• AWS Config records resource configurations and evaluates them against compliance rules. For example, it can check whether encryption, logging, or access settings meet company requirements.

• Amazon Inspector identifies software vulnerabilities and unintended network exposure, not general policy or regulatory compliance.
• Amazon CloudWatch monitors metrics, logs, and operational events, but is not primarily a compliance assessment service.
• AWS CloudTrail records API activity for auditing and investigation. It supports compliance, but does not itself provide the structured compliance assessment capabilities of Audit Manager and Config.

• B — Increase provisioned concurrency for Lambda

• D — Refactor the Lambda functions

• E — Use Amazon RDS Proxy

• Answer: False. Agents and managers CAN create knowledge articles from Community questions.

• Why: In ServiceNow, a Community question can be converted into a Knowledge article using the Create Knowledge (or Convert to Knowledge) action. This allows what customers asked to become a reusable article for others.

• How it works (high level):

• Permissions: This ability depends on having the right roles/permissions (e.g., agents or knowledge managers). If you don’t see the option, check your role assignments or the knowledge-management configuration.

• Quick take: If a question in Community is valuable for others, a trained agent can turn it into a Knowledge article, making it available for self-service.

• runParallel is defined as async, so it returns a Promise.
• To use the result, you attach a then handler (or use await inside another async function).

• A: “Async runParallel() .then(data);” is invalid. “async” is a keyword for function declarations, not something you put in front of a call, and you’d need a function as the then-argument.
• B: “runParallel().done(function(data){return data;});” .done is not standard in native Promises (it exists in some libraries). Without a compatible library, this won’t work.
• C: “runParallel().then(data);” is invalid because then expects a function as its argument; data is not a function.
• D: “runParallel().then(function(data){ return data; });” is valid (or equivalently, runParallel().then(data => data);).

• The robust, standard option is D.
• B could work only with a library that provides .done; otherwise it’s not reliable.

• 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.

• BIOS language support: Useful for usability, but not whether the PC can operate electrically.
• Supply chain security: Concerns procurement and hardware trust, not deployment across countries.
• Power efficiency: Important for energy usage, but it does not ensure compatibility with local power systems.

• Filtering or reshaping columns
• Joining with an analysis-specific dataset
• Creating calculated fields
• Applying business logic for a particular project

• Data blending: Combining different data sources, not specifically the final processing step.
• Data enhancement: A broad term for enriching data.
• Data testing: Checking data quality or pipeline correctness.
• Last-mile ETL: The precise term for additional transformations performed after the main pipeline, often directly before analytics or reporting.

• 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

• 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.

• A. Modify CommunitiesSelfRegController

• C. Configure Communities registration to use a custom Visualforce page

• B. Modify the self-registration trigger — There is no standard “self-registration trigger” intended for this configuration. The registration logic is handled by the Visualforce controller.
• D. Configure a custom Apex controller — The standard approach is to modify the provided CommunitiesSelfRegController, rather than simply selecting a separate controller configuration.

• Premium file shares: contoso104 only
• Blob access tiers: contoso101, contoso102, and contoso103

• Premium Azure Files shares require a storage account with the FileStorage account kind. This is a specialized account type and is not used for blob storage.
• Blob access tiers such as Hot, Cool, and—where supported—Archive apply to blob-capable accounts, such as General-purpose v2 or BlobStorage accounts shown in the exhibit.
• contoso104 is therefore excluded from the blob-tier selection because it is the premium Files account.

• Assign users or their team an appropriate security role.
• Ensure the role has the required table privileges, such as read, create, write, and append.
• Share the app with that security role in the app designer.

• Dynamics administration center: Used for environment and service administration, not routine app access configuration.
• Manage Roles: Not the specific Dataverse area used to define app and data permissions.
• Security Roles: Define what users can access and which operations they can perform.

• ADF: Automatic Document Feeder; a printer/scanner hardware component.
• USB: A short-range wired connection, not a protocol for accessing a remote shared folder.
• PCL: Printer Control Language; it describes how print jobs are formatted, not how files or printers are shared over a network.

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.

• The requirement explicitly says the organization wants to use SAML to secure Salesforce API access.
• The SAML Bearer Assertion Flow exchanges a SAML assertion for a Salesforce OAuth access token.
• It is intended for server-to-server or other noninteractive integrations where the application has already been authenticated by an identity provider.
• The connected app can be configured so administrators authorize or preauthorize applications that consume the APIs.

• B — JWT Bearer Flow: Uses a signed JWT, not a SAML assertion. It would be appropriate if the requirement specified JWT-based authentication.
• C — SAML Assertion Flow: This is not the standard Salesforce OAuth flow name; the relevant name is OAuth 2.0 SAML Bearer Assertion Flow.
• D — User-Agent Flow: Designed for interactive browser-based authorization, not a SAML-based server-to-server integration.

• 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.

• Correct answer: B (No, it does not).

• A purchase agreement in Dynamics 365 SCM is a vendor-side price arrangement. It sets prices/discounts for what your company buys from suppliers, not for what you sell to customers.
• The objective in Question 2 is to give clients a quantity-based discount on items they purchase from you. To accomplish this, you should configure a sales price / trade agreement (on the customer/sales side), not a purchase agreement.
• In a sales price trade agreement, you can define quantity breaks such as:

• Create a Sales price trade agreement for the item and relevant customer (or customer group).
• Add quantity breaks: 51–100 with 10% discount, 101+ with 15% discount.
• Ensure the agreement is active for the desired date range.

• Self-signed certificate: Causes a certificate warning, not incorrect IP resolution.
• Nameserver record: A DNS record problem would typically affect multiple users, not just one.
• IP helper: Relays DHCP or other broadcast traffic between networks; it does not control website name resolution.

• L2TP uses UDP port 1701 for the L2TP control channel.
• The destination port is 1701; the source port is a dynamically chosen ephemeral port on the client (not 1701).
• Therefore the statement that both source and destination ports are 1710 is incorrect (and 1710 is not the standard L2TP port).

• The destination port should be 1701, not 1710.
• The source port should be an ephemeral port chosen by the client, not 1701.

• B — AWS DataSync: Transfers data between storage systems, such as S3, file systems, and on-premises storage. It is not a marketplace or catalog for third-party datasets.
• C — Kinesis Data Streams and CodeCommit: CodeCommit is a source-code repository, not a third-party data provider. Kinesis is for streaming data ingestion.
• D — Kinesis Data Streams and ECR: ECR stores container images, not datasets. Kinesis does not provide access to ECR data as an external dataset source.

1. Selling price per unit: $750
2. Required annual return:

1. Required profit per unit:

1. Target cost per unit:

• 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.

• Hardware and infrastructure
• System software
• Networks and communications
• Technology platforms and services

• Business Architecture: Defines business strategy, organization, functions, and processes.
• Data Architecture: Defines the structure and management of enterprise data.
• Application Architecture: Describes application systems and how they interact to support business and data processing.

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

• What the scenario asks: You have a Power BI semantic model that pulls from multiple sources (Azure SQL Database and SharePoint Online), must support a single dataset for three reports, keep data current (daily refresh by 7 AM PT), and apply RLS to limit sales data by region. You need to choose a storage mode for the tables.

• Correct choice: Dual storage mode.

• Why Dual fits:

• Key concepts:

• Modelo de embeddings de texto: trabalha principalmente com texto, não sendo adequado para imagens.
• Modelo generativo multimodal: pode interpretar ou gerar conteúdo de vários tipos, mas não é a opção específica para busca por similaridade.
• Modelo de geração de imagens: cria imagens a partir de entradas, não realiza busca multimodal.

• Correct answer: A
• What this is saying: You need to write a Transact-SQL query that uses REGEXP_SUBSTR to extract the ID from MessageText, and you should apply STRING_ESCAPE(MessageText, 'json') before calling REGEXP_SUBSTR.

• MessageText may contain JSON characters (quotes, backslashes, etc.). Escaping the JSON content first ensures the string you pass to the regex is safe and won’t confuse the regex engine.
• The pattern you apply with REGEXP_SUBSTR would then extract the first substring that matches your ID pattern from the (escaped) text.

• Example (conceptual):

• The question implies REGEXP_SUBSTR is available in this environment; some SQL Server and Fabric contexts don’t expose it natively in all versions. If REGEXP_SUBSTR isn’t available, you’d need an alternative approach (e.g., using built-in regex-like capabilities or CLR/UDFs).
• If you need the ID specifically from the first paragraph, you might first isolate the first paragraph and then apply REGEXP_SUBSTR, or compose a single pattern that anchors to the first paragraph.

• Date: 2018-12-31
• Time: 08:59

• B: The original value contains the text at, so it cannot be converted directly to a date.
• A: The last characters contain the time, not the date.
• D: Extracting the first 11 characters can leave an unwanted space and does not properly separate the time component.

• Interactive development and exploration
• Small datasets
• Lightweight transformations or testing
• Avoiding the overhead and cost of multiple workers

• Automated reports: Jobs may benefit from job clusters or SQL warehouses.
• Working with SQL in Databricks SQL: Databricks SQL warehouses are the relevant compute option.
• Automatically scaling for larger data: A multi-node cluster with autoscaling is more suitable.
• Large amounts of data: Distributed worker nodes are generally needed.

• Why Ishikawa:

• Why not the others:

• Modelo de embeddings multimodal: transforma texto e imagens em vetores no mesmo espaço semântico. Isso permite comparar uma consulta textual com imagens, ou uma imagem com textos relacionados.
• Modelo generativo multimodal: interpreta diferentes modalidades e gera conteúdo, mas não é a escolha específica para indexação e busca vetorial.
• Modelo de geração de imagens: cria imagens, portanto é inadequado.
• Modelo de embeddings de texto: não atende consultas com imagens.

• A: My Domain is required for many SSO configurations, but if SSO works, it is unlikely to be the cause of losing the target record.
• B: HTTP-POST is a valid SAML binding and does not inherently prevent redirection.
• D: An incorrect Federation ID generally causes authentication or user-matching failure—not successful login to the home page.

• Improve QA testing efficiency: A prototype may help discover defects early, but that is not its greatest benefit.
• Decrease time allocated for user testing and review: Prototyping usually requires additional user involvement and review, not less.
• Minimize scope changes: Prototypes can actually reveal new requirements or cause scope changes. However, discovering those changes early is beneficial.

• 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.

• Customers access the portal without needing a full Dynamics 365 license.
• They submit case information through portal forms.
• The submitted data is stored in Dataverse tables, such as the Case table.
• Security is controlled using web roles and table permissions, so customers can access only appropriate records.

• Dynamics 365 Connector — connects apps to Dynamics 365 data but is not the portal’s underlying data platform.
• Microsoft SharePoint — useful for documents and collaboration, not the standard case-management data source for portals.
• Microsoft Azure Storage — stores files or other data, but is not the native portal business-data platform.

• Alice is co-resident on the same physical host and exploits shared hardware (the processor cache) to infer secrets. This is the classic definition of a side-channel attack—information leakage through implementation details (like timing or cache behavior) rather than by breaking a protocol or injecting code.

• Observing cache timing or access patterns to deduce cryptographic keys or plaintext data from the victim VM.

• Man-in-the-cloud attack: targets cloud trust/auth, not local hardware sharing.
• SQL injection: exploits input to run SQL commands, not a VM/caching vector.
• Service hijacking: takes control of a service, not about covert data leakage via shared hardware.

• Notice phrases like “shared hardware resources,” “co-resident,” or “cache”—these indicate a side-channel vector.

• Assign a Teams license to a user — Licenses are assigned through the Microsoft 365 admin center, Microsoft Entra ID, or PowerShell.
• Deploy the Teams client — The Teams admin center manages Teams policies and apps, but it is not the primary tool for deploying the desktop client.
• Prevent users from creating teams — Team creation depends on controlling the creation of Microsoft 365 groups, generally configured through Microsoft Entra ID and PowerShell rather than directly in the Teams admin center.

• nomes de pessoas;
• organizações;
• locais;
• datas;
• números de processos;
• leis ou contratos.

• NER = identifica informações específicas e classificáveis.
• Sumarização = reduz um documento e apresenta seus pontos principais.

• 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.

• Options:

• Answer: The correct choice is A (800-61r3).

• NIST SP 800-61 Rev. 3 is the dedicated guide for incident handling/response and reflects the latest guidance on the incident response lifecycle (preparation, detection/analysis, containment, eradication, recovery, post-incident activity).
• 800-61r2 is an older revision of the same incident response guide.
• 800-53 covers security and privacy controls, not a specific incident response standard.
• 800-171 focuses on protecting CUI in non-federal systems and networks, not incident response guidance.

• 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.

• 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.

• Developed and maintained independently
• Deployed without changing the entire application
• Scaled separately based on demand
• More resilient when another service has problems

• A: Functional testing is useful, but it is not the main practice described.
• B: Automation helps deployment, but the scenario focuses on architectural decomposition.
• C: Multiple locations improve availability, not application modularity.