Palo Alto Networks SD-WAN-Engineer Exam Prep
Palo Alto Networks SD-WAN Engineer (Page 5 )

1. Convert text and images into numerical embeddings.
2. Store or compare those embeddings.
3. Retrieve the most semantically similar items.

• Embedding model: Best for similarity search and retrieval.
• Generation model: Best for producing new text or other content from multimodal input.

• Data loss prevention (DLP): Helps detect or prevent unauthorized data transfers, but does not directly protect data on a stolen, powered-off laptop.
• Operating system hardening: Reduces vulnerabilities and attack surface, but does not adequately protect stored data if the device is stolen.
• Boot security: Helps prevent unauthorized operating systems or boot media from loading. It supports device security but is not the primary solution for protecting the data itself.

• Honeypots: Decoy systems or services made to attract attackers. Legitimate users should not interact with them, so activity there is a strong indicator of malicious behavior.
• DNS sinkholes: Redirect requests for known malicious domains to a controlled internal system. This can reveal infected hosts attempting to contact command-and-control infrastructure.

• Tokenization: Replaces sensitive data with non-sensitive tokens.
• CI/CD: Automates software development, testing, and deployment.
• Threat modeling: Identifies and analyzes potential threats before or during system design.
• Data obfuscation: Makes data harder to understand or interpret.

• NIDS: Monitors network traffic for suspicious activity and network-based attacks targeting the application or its supporting services.
• HIPS: Protects an individual host by monitoring processes, files, and system activity. It can help secure the web server, but it is not focused specifically on the application’s network attack surface.
• SIEM: Aggregates and correlates logs; it does not directly prevent attacks.
• Honeypot: A decoy system, not the primary protection for a production web application.
• Certificate revocation list: Deals with certificate trust, not application exploitation.

• Blue team: Defends systems, monitors activity, and responds to attacks.
• Purple team: Coordinates red- and blue-team activities to improve defenses.
• White team: Oversees or manages the exercise, including rules and scope.

• The S3 bucket as an origin for static content
• The Application Load Balancer (ALB) as an origin for dynamic content
• An Amazon Route 53 alias record pointing the application domain to CloudFront

Why this works

• Static data: CloudFront caches objects from S3 at edge locations, reducing latency for users worldwide.
• Dynamic data: CloudFront forwards requests that require application processing to the ALB. It can also maintain persistent connections and use the AWS global edge network to improve delivery performance.
• One domain: CloudFront behaviors can route different path patterns to different origins—for example, /static/* to S3 and other paths to the ALB.

Why the other options are incorrect

• Global Accelerator is designed primarily for accelerating traffic to applications with endpoints such as ALBs, not for caching S3 content.
• Using separate domains or splitting static and dynamic traffic adds unnecessary complexity.
• CloudFront already provides the required global edge distribution and caching, so combining it with Global Accelerator is unnecessary here.

• 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.

• Secret scope: A named container that groups related secrets and defines access permissions. Example: finance-prod.
• Secret key: The name of an individual secret stored inside that scope. Example: db-password.

text 
Scope: finance-prod 
  Key: db-username 
  Key: db-password

python 
dbutils.secrets.get( 
    scope="finance-prod", 
    key="db-password" 
)

• 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.

• Career enhancement — A mentor can provide guidance, advice, networking support and help the mentee identify career opportunities.
• Support with new challenges — A mentor can help the mentee think through unfamiliar situations and develop confidence and practical solutions.
• Personal development — Mentoring can improve skills such as communication, leadership, decision-making and self-awareness.

• Solving all problems — The mentor supports and guides the mentee but should not take responsibility for solving every problem.
• Discipline would be dispensed if they make a mistake — Mentoring does not remove normal accountability or workplace consequences. Mistakes should instead become learning opportunities.

• Microsoft 365 groups can contain users, but generally can’t contain other groups as members.
• Security groups can contain users and, where supported, other security groups.
• Distribution groups have different nesting restrictions and aren’t equivalent to security groups.
• Dynamic groups can’t be manually populated with members; their membership is calculated from rules.
• A group’s membership type (Assigned or Dynamic) and group type determine whether it can be added to another group.

• Keep earlier prompt versions.
• Identify the last version that produced acceptable output.
• Restore it as a baseline.
• Make small, controlled changes—ideally one significant change at a time.
• Test the output after each change.

• A: Discards useful information about what worked.
• B: Large simultaneous changes make it difficult to identify the cause of problems.
• D: Accepts output that does not meet the requirements.

• You can configure different pre-shared keys for different device groups.
• All cameras could use one key.
• All scanners could use another key.
• Each key can be associated with an appropriate role or access policy.

• How quickly the vendor must respond to an incident or request
• Target resolution times
• Availability or uptime requirements
• Performance metrics and penalties for not meeting them

• SOW (Statement of Work): Describes the project’s scope, tasks, deliverables, and timeline.
• MOA (Memorandum of Agreement): Documents a formal agreement to cooperate or perform specific activities.
• MOU (Memorandum of Understanding): Records a mutual understanding or intent, often less binding than a contract.

• Honeypots: Deliberately vulnerable or attractive systems designed to lure attackers. Legitimate users should not access them, so activity on a honeypot is a strong indicator of compromise.
• DNS sinkholes: Redirect requests for known malicious domains to a controlled internal system instead of allowing the connection. This can identify infected hosts attempting to contact command-and-control infrastructure.

• Tokenization: Replaces sensitive data with non-sensitive tokens; it protects data but does not primarily detect attackers.
• CI/CD: Automates software development and deployment processes.
• Threat modeling: Identifies potential threats and weaknesses before or during system design.
• Data obfuscation: Makes data harder to understand, but it is not an attacker-detection method.

• Threat perspective: Focuses on possible attacks, but may seem technical or hypothetical.
• Compliance perspective: Can motivate action, but compliance alone does not demonstrate the broader business value of governance.
• Policy perspective: Policies are important, but they are a means of implementing governance, not its primary business justification.

• Subject: The entity that initiates an action—here, Derrick/user account.
• Object: The resource being accessed— the file.
• Action: Reading the file.

1. Identify the fact table

• Records something that happened, such as a sale, test, appointment, or measurement
• Contains foreign keys to other tables
• Contains measures or numeric results
• Has many rows

2. Identify a dimension table

• Describe people, products, dates, locations, or departments
• Contain descriptive columns
• Are referenced by the fact table
• Have fewer rows than the fact table

3. Identify the surrogate key

• System-generated
• Unique within the dimension
• Often named PatientKey, CustomerKey, or similar
• Usually an integer
• Not meaningful outside the model

• 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.

sql 
CREATE PROCEDURE dbo.usp_CreateOrder 
AS 
BEGIN 
    SET NOCOUNT ON; 
    SET XACT_ABORT ON; 


    BEGIN TRY 
        BEGIN TRANSACTION; 


        INSERT INTO dbo.Orders (/ columns /) 
        VALUES (/ values /); 


        SET @OrderID = SCOPE_IDENTITY(); 


        COMMIT TRANSACTION; 
    END TRY 
    BEGIN CATCH 
        IF @@TRANCOUNT > 0 
            ROLLBACK TRANSACTION; 


        THROW; 
    END CATCH; 
END;

• BEGIN TRY contains the transactional work.
• SCOPE_IDENTITY() retrieves the identity generated by the INSERT; it belongs after the insert, not as the error-handling logic.
• COMMIT runs only if all statements succeed.
• BEGIN CATCH handles failures.
• IF @@TRANCOUNT > 0 prevents attempting a rollback when no transaction is active.
• ROLLBACK undoes partial changes.
• THROW re-raises the original error with consistent details for the application.
• SET XACT_ABORT ON ensures many run-time errors automatically terminate and roll back the transaction.

• Fileless malware: Nothing in the command indicates malware executing only in memory.
• Living-off-the-land binaries: Mimikatz is a credential-access tool, not a normal system utility used for LOLBin abuse.
• Social engineering: The command shows technical credential abuse, not manipulation of an accountant.

• Financial performance
• Customer perspective
• Internal business processes
• Learning and growth

• Increasing the number of indicators can make the scorecard cluttered and less useful. Measures should be limited to those that are strategically important.
• The scorecard is mainly a tool for implementing and monitoring strategy, not for formulating strategy.
• It should contain both leading indicators and lagging indicators. Leading indicators predict future performance, while lagging indicators measure results already achieved.

json 
"Resource": "arn:aws:s3:::bucket-name/*"

• A: Revoking or changing an instance profile does not reliably invalidate temporary credentials that have already been issued and may still be valid.
• B: Changing the EC2 security group does not necessarily stop the attacker from using the stolen credentials from elsewhere.
• C: Amazon Macie helps discover sensitive data; Object Lock prevents modification/deletion, not reads or downloads.

• Access controls — ensuring only authorized users can access it.
• Encryption — protecting the data if it is intercepted or exposed.

• 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.

• Encryption to preserve confidentiality
• Integrity protection to detect alteration
• Authentication of the server through certificates

• SHA-256: A hashing algorithm; it does not encrypt data for transmission.
• SSL 3.0: Obsolete and insecure. It should not be used.
• AES-256: A strong encryption algorithm, but by itself it does not provide the complete secure communication protocol needed for data in transit.

• GPU: A failure may cause no video output, but the PC usually still powers on.
• RAM: Can prevent booting or produce error beeps, but fans and power indicators generally work.
• CPU: Can prevent startup or booting, but it usually does not cause a completely lifeless system.

• Issuer: Identifies the party issuing a SAML message—usually the identity provider in the assertion. It is not the Salesforce-specific identifier the architect should provide for differentiating Salesforce.
• Identity Provider Login URL: The endpoint where users are sent to authenticate.
• SAML identity location: Determines where the user identity is found in the SAML assertion, such as the subject or an attribute.

• 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”.

• Data lakes: scalable, low-cost storage for structured, semi-structured, and unstructured data.
• Data warehouses: reliable SQL analytics, governance, and performance features.

• Data lake: Primarily provides flexible, scalable storage but may lack warehouse-style reliability and governance.
• Data warehouse: Strong for structured analytics but less flexible for raw and unstructured data.
• All of these: The individual lake and warehouse do not, by themselves, unify the siloed architecture.

1. Create or verify cost groups

1. Set up the item model group

1. Create the costing version

1. Enter or calculate item costs

1. Activate the standard costs

• A: Allow SAN certificates — SANs are used to identify valid hostnames in a certificate. They do not bypass trust validation.
• C: Open the secure LDAP port — A blocked port would normally cause a timeout or connection-refused error, not certificate errors.
• D: Increase the TLS version on the RA — The issue concerns certificate trust, not the organization’s registration authority.

• 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.

• Planning — identify the need, objectives, resources and feasibility.
• Analysis — determine user requirements and examine the existing system.
• Design — specify how the new system will work.
• Implementation — build, test, install and introduce the system.
• Maintenance/evaluation — monitor and improve the system after implementation.

• ARP poisoning: Redirects or intercepts local network traffic; monitoring would typically show suspicious ARP changes or man-in-the-middle behavior.
• Jamming: Interferes with wireless or radio signals. It would affect connectivity, not usually show a server-specific overload.
• Kerberoasting: Attempts to obtain and crack Kerberos service-account hashes; it does not normally cause a system outage.

• Updating the CRL: Revokes compromised certificates, but does not fix the CA flaw that allowed them to be created.
• Changing passwords: May be necessary if accounts were compromised, but it does not address the certificate-generation vulnerability.
• Implementing SOAR: Improves security automation and response; it does not remediate the underlying PKI weakness.

• 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.

• A: Reduce management overhead — This is generally an advantage of public cloud, not hybrid cloud. Hybrid environments can increase management complexity.
• B: Cross-platform virtualization — Not the defining advantage of hybrid cloud.
• D: Leverage IaaS and PaaS — Public clouds commonly provide both IaaS and PaaS, so this is not unique to hybrid cloud.

• Detect risky sign-ins from unfamiliar or unidentified IP addresses
• Evaluate user or sign-in risk
• Automatically require a password change because of a risky sign-in

• User risk policy: Can require a user to securely change their password when the account may be compromised.
• Sign-in risk policy: Can require MFA or block access based on the risk of a particular sign-in.

• Reviewing security policies and standards checks whether controls are documented, not whether they work.
• Reviewing security logs may show that monitoring is occurring, but does not directly establish that preventive controls are effective.
• Analyzing technical security practices is broad and may assess implementation, but it is less objective than an actual controlled attack.

• Design/compliance effectiveness: policies, standards, and procedures
• Operational effectiveness: logs, records, and evidence that controls operate
• Technical security effectiveness: penetration testing or vulnerability testing

• Custom domain: miami.weyland.com requires a paid App Service tier; Free and Shared are unsuitable.
• Two instances: Standard supports scaling to multiple instances.
• SSL: Standard includes SSL support.
• 12 GB storage: Basic provides only about 10 GB, so it does not meet the requirement. Standard provides substantially more storage.
• Cost minimization: Standard is the lowest tier among the choices that satisfies all requirements.

• Azure Resource Manager (ARM) templates
• Or, in newer Azure terminology, Bicep files

• 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.

• Monitoring: Detects activity but does not remove the underlying risk.
• Patching: Useful for systems that must remain operational, but these desktops are unused.
• Isolating: Can be a temporary containment measure, but permanently removing unnecessary systems is more appropriate.

• The Subscribe to Reports user permission.
• At least Viewer access to the report’s folder.
• Access to the report itself.

• Subscribe to Reports: Run Reports is not the relevant Salesforce permission.
• Chatter Subscribe to Reports is not a Salesforce permission.
• Set Running User relates to configuring the user whose permissions determine report results—not subscribing to a report.

sql 
SELECT COUNT(*) FROM table;

• A: It does not normally need to scan all data files for this operation.
• B: Results are not simply reused from a query cache every time. Caching is separate from Delta’s metadata optimization.
• D: The relevant metadata is maintained through the Delta transaction log, not directly treated as a Parquet-file metadata operation in this context.

sql 
CREATE TABLE my_table 
USING CSV 
OPTIONS (path '/path/to/csv');

sql 
CREATE TABLE my_table 
USING CSV 
LOCATION '/path/to/csv';

• USING CSV specifies the file format.
• path or LOCATION specifies where the files are stored.
• USING DELTA would be used only when the source data is in Delta format.
• FROM is used in a SELECT statement, not normally as the format declaration in CREATE TABLE.

• Restrict a port to a defined number of MAC addresses
• Use statically assigned or “sticky” MAC addresses
• Shut down or restrict the port when violations occur

• Load balancer: Distributes application traffic; it does not protect switch MAC tables.
• IPS: May detect suspicious network activity, but is not the primary control for limiting switch MAC entries.
• NGFW: Filters traffic at the network boundary; it does not directly prevent MAC table flooding on access switches.

• DB1 (500 TB): Azure Data Box Heavy

• Virtual machines: Azure Migrate