Scaled Agile SAFe-Agilist Exam Prep
SAFe Agilist (Page 2 )

• Base table — the table containing common inherited fields
• Parent table — the table directly extended by the child
• Other tables in the hierarchy

CIMA P3 topics

• IT governance and systems strategy
• Systems development and implementation
• Change and project governance
• Strategic and business risk

• A — Plan for new systems: The committee should help identify and prioritise systems requirements and ensure planned systems support organisational needs.
• D — Consider competitive issues: New information systems may affect Y’s competitive position, service quality and efficiency. These strategic implications should be considered.
• E — Ensure the system meets company goals: This is a key governance responsibility. The committee should ensure the project remains aligned with Y’s objectives and delivers business value.

• B — Develop new systems: Detailed system development should be performed by IT specialists and project teams, not the steering committee.
• C — Manage the project: The project manager should handle day-to-day project management. The steering committee should provide oversight, challenge and key decisions, rather than manage daily activities.

• A. Remove rows where Sales[Status] is Canceled

• E. Remove Sales[Canceled Date]

• B: Removing Sales_Date would remove information users need—the date portion.
• C: Changing Delivery_Time to Integer could alter its meaning or precision and is not necessarily safe.
• D: Splitting the date/time column creates additional columns rather than simply removing unnecessary data.

• Azure Machine Learning Studio is designed to build, test, train, and deploy machine-learning models, including predictive analytics.
• Azure Cosmos DB is a globally distributed NoSQL database. It can store data used by an AI solution, but it is not the primary service for developing and deploying predictive models.
• Therefore, the appropriate recommendation is Azure Machine Learning Studio, as shown in Question 15.

• Disable high concurrency: Changes workspace-wide behavior and is not the targeted way to isolate these workloads.
• Modify the number of executors: Adjusts capacity and performance, but does not provide workload isolation.
• Set the default environment: Controls libraries and runtime configuration, not compute isolation.

• IaaS: You deploy and manage virtual machines, including the operating system and installed software. Azure manages the physical datacenter, hosts, and networking infrastructure.
• PaaS: Azure manages the infrastructure and operating system, while you deploy and manage your application code. Examples include Azure App Service and Azure Functions.

• Share files with the wrong people
• Use public links unnecessarily
• Fail to classify sensitive data
• Upload data to unauthorized services
• Misunderstand company sharing policies

• A — Step-up authentication: Helps protect administrator accounts, but does not directly address improper file sharing by users.
• C — Password complexity: Helps reduce password attacks, not accidental data disclosure.
• D — Mobile device management: Secures managed mobile devices, but does not directly control file-sharing behavior across the organization.

• Verifies the sender’s identity using their private key.
• Confirms the transaction was not altered after signing.
• Provides evidence that the signer approved or originated the transaction.

• Digital certificates: Bind an identity to a public key, but do not themselves prove that a specific transaction was signed.
• Encrypted passwords: Protect confidentiality or authentication, but generally do not provide transaction-level nonrepudiation.
• One-time passwords: Authenticate a user for a session or transaction, but usually do not provide durable proof of who authorized the electronic record.

• Each team’s Bedrock workflow uses a separate IAM service role.
• The role’s Amazon S3 permissions can be limited to only that team’s customer folder or objects.
• This enforces least privilege and prevents one team’s Bedrock application from accessing another team’s data.
• Access is enforced by AWS permissions, not by asking users to provide a customer name in each request.

• A single role with broad S3 access does not provide team-level isolation.
• Asking teams to specify a customer name is not an access-control mechanism.
• Redacting data does not prevent unauthorized access.
• A bucket policy alone is insufficient unless it explicitly enforces the required team-role restrictions.

• A user connects with their Google account.
• Google associates the user’s SSH key with that identity.
• IAM roles determine whether they can log in.
• Access can be tied to a specific employee for auditing.
• Removing the IAM role removes their login access.

• compute.osLogin: regular OS login access
• compute.osAdminLogin: OS login with administrative privileges, typically including sudo

text 
enable-oslogin=TRUE

• Accept: Acknowledging the risk without taking additional action.
• Transfer: Moving the risk’s financial impact to a third party, such as an insurer.
• Mitigate: Reducing the likelihood or impact through controls, such as patching or employee training.
• Avoid: Eliminating the activity that creates the risk.

• Frequency/likelihood = how often or how likely the risk is to occur.
• Severity/impact = how damaging or costly the consequences would be.

• A minor equipment fault occurring frequently may have high frequency but low severity.
• A major cyberattack occurring rarely may have low frequency but high severity.
• A risk that happens often and causes substantial losses has high frequency and high severity.

• Active remediation actions role in Microsoft Defender for Endpoint

• Security Reader role in Azure AD/Entra ID

• Security Administrator is broader than necessary because it grants extensive security-management permissions, violating least privilege.
• Compliance Data Administrator is intended for compliance data management, not Defender for Endpoint remediation approvals.

• Architects design overall Splunk infrastructure and data strategy.
• Administrators manage configuration, access, and system operations.
• Knowledge Managers create and maintain knowledge objects such as data models, field extractions, and event types. They may support pivots, but they are not the primary users of them.

• File hashes
• Strings and metadata
• Binary or code structure
• Known malicious patterns
• Embedded indicators or signatures

• Sandbox: Executes the file in an isolated environment; useful for observing behavior, but usually slower.
• Network traffic analysis: Examines communications generated by a system or application, not the file itself.
• Package monitoring: Tracks software packages or installations and is not the primary method for examining malware signatures.

• Training data for potential bias before model training
• Trained models for bias in predictions
• Model features to help explain how they influence predictions

• A: RAG workflows are typically built using services such as Amazon Bedrock, knowledge bases, and data sources.
• B: Monitoring model quality in production is primarily associated with SageMaker Model Monitor.
• C: Documenting model details is handled by capabilities such as SageMaker Model Cards.

• terraform apply
• terraform destroy

• Malware or malicious software
• Command-and-control tools
• Internet surveillance and intrusion software

• ITAR: A U.S. regulation controlling defense-related articles and services; it is not the international arrangement described.
• Palermo Convention: Focuses on transnational organized crime and related protocols, not export controls for cyber weapons.
• GDPR: European data-protection and privacy legislation.

• IKE (Internet Key Exchange) negotiates the IPsec security association, including:

• ESP (Encapsulating Security Payload) protects the data after negotiation by providing encryption and optionally authentication.
• AH provides authentication and integrity but does not encrypt traffic.
• TLS is used for protocols such as HTTPS, not for negotiating IPsec parameters.

• Espionage: Stealing confidential information, often for a competitor or government.
• Data exfiltration: Unauthorized transfer of data outside the organization. This could occur, but the question focuses on using unapproved access methods.
• Nation-state attack: An attack sponsored or conducted by a government.
• Shadow IT: Employees using technology or access methods outside the organization’s approved security controls.

• B: Prompt caching reduces cost and latency for repeated content, but cached content still occupies the context window. It does not solve context accumulation.
• C: Switching to a smaller model changes model capacity but does not address the growing context or remove irrelevant data.
• D: Keeping everything indefinitely increases token usage, risks context-window limits, and can distract the model with outdated information.

1. Create a temporary Onboarding OU.
2. Move the new account into it.
3. Move the restrictive SCPs from the organization root to the Production OU.
4. Allow the account to update AWS Config.
5. Move the account into Production after onboarding.

• An SCP attached at the organization root applies to every account and OU beneath it.
• An SCP attached to the Production OU applies only to accounts in that OU.
• Therefore, moving the restrictive SCP from the root to Production temporarily exempts the onboarding account without weakening the policies for existing production accounts.
• Once onboarding is complete, moving the account into Production subjects it to the normal restrictions.

• B — Incorporate contextual output encoding/escaping: Encode untrusted data based on its context—HTML, attribute, JavaScript, or URL—so the browser treats it as data rather than executable code.
• D — Run untrusted HTML input through an HTML sanitization engine: Sanitization removes or neutralizes dangerous elements and attributes, such as script-related content, while preserving safe HTML where needed.

• A: Enabling client-side scripts does not prevent XSS. Script restrictions may reduce risk in some environments, but “enable” is not a general XSS control.
• C: Cookie inspection is unrelated to preventing injected scripts.
• E: The SameSite cookie attribute primarily helps mitigate CSRF, not XSS. It should not generally be described as an XSS prevention measure.

• Information sources: Collect security-related data, such as network packets, system logs, audit records, or application events.
• Analysis: Examines the collected data to identify suspicious activity, attacks, or policy violations.
• Response: Takes or recommends action, such as generating alerts, logging the event, or supporting a protective response.

• Set credit quotas for an account or individual virtual warehouses.
• Define monitoring intervals.
• Trigger actions when usage reaches thresholds, such as sending notifications or suspending a warehouse.
• Help control unexpected warehouse spending.

• Account Usage: Provides historical usage and billing data; it does not enforce credit limits.
• Warehouse Limit Parameter: Not the Snowflake object used for account-wide credit controls.
• Credit Consumption Tracker: Not a standard Snowflake object.

• Accept: Acknowledges the risk without taking additional action.
• Transfer: Shifts the risk or financial impact to another party, such as an insurer.
• Mitigate: Reduces the likelihood or impact through controls like patching, MFA, or segmentation.
• Avoid: Eliminates the activity that creates the risk.

• The load balancer provides the listener’s frontend IP address.
• The active SQL Server node must also respond to that same listener IP.
• Enabling Floating IP allows the listener IP to be preserved and handled correctly by the active replica.
• Without it, SQL connections may be sent to a node that cannot correctly claim the listener address.

• A health probe for the SQL Server port
• A load-balancing rule using the listener port
• Floating IP enabled on that rule

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• ?? NFS ?? SMB ?? ??
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• B: ????? NFS ? Snowball Edge? ?? ?? ? AWS? ?? ? S3
• D: ????? NFS ? ????/Direct Connect ? File Gateway ? S3

• A hypervisor allows multiple virtual machines to run on one physical server.
• Each VM can have its own operating system, so the customer can consolidate Windows, Linux, and Unix servers.
• A Type 2 hypervisor runs on a host operating system and can be deployed on local hardware, helping address data privacy and avoiding ongoing public-cloud charges.

• Containers share the host operating system’s kernel.
• They are well suited to consolidating applications, but they generally cannot independently run a mix of unrelated kernels such as Windows, Linux, and Unix on one host.

• On VirtualNetworkA: enable Allow gateway transit.
• On VirtualNetworkB: enable Use remote gateways.

• User-generated content: precisa ser coletado, filtrado, anonimizado e rotulado.
• Moderation logs: podem conter dados inconsistentes, informações pessoais e decisões que precisam ser revisadas.
• Content moderation guidelines: são regras ou orientações, não dados diretamente utilizáveis para medir o comportamento do modelo.

• Controlar o fluxo de dados entre S3 e SageMaker;
• Aplicar regras de segurança por meio da VPC;
• Reduzir a exposição dos dados;
• Permitir acesso privado ao bucket do S3.

• Amazon Inspector: avalia vulnerabilidades, mas não gerencia o fluxo de dados.
• Amazon Macie: ajuda a descobrir e proteger dados sensíveis no S3, mas não cria a conexão com o SageMaker.
• S3 Glacier Deep Archive: é uma classe de armazenamento para arquivamento, não uma solução de conectividade.

• AWS Network Firewall can inspect and block traffic across a VPC when traffic is routed through the firewall. A Drop action rule can deny traffic from the suspicious source IP.
• GuardDuty findings are sent to Security Hub.
• A Lambda function can be invoked when Security Hub receives a new GuardDuty finding, extract the source IP, and update the Network Firewall policy with a blocking rule.

• GuardDuty threat lists: Used to identify or increase the severity of findings; they do not directly block VPC traffic.
• AWS WAF: Protects supported web applications, such as CloudFront or Application Load Balancers. It does not provide general VPC-wide traffic blocking.
• GuardDuty suppression rules: Suppress or hide findings. They do not block the suspicious traffic.

• Install unauthorized or unapproved applications
• Access system areas normally restricted
• Add features unavailable in the default software
• Modify the device’s operating system

• SQL injection (SQLi): Attacks databases by inserting malicious SQL commands.
• Cross-site scripting (XSS): Injects malicious scripts into web pages viewed by users.
• Sideloading: Installs an application from outside the official app store, but it does not necessarily remove the phone’s operating-system restrictions.

• Response and resolution times
• Availability or uptime
• Performance targets
• Support obligations
• Penalties for failing to meet commitments

• SOW (Statement of Work): Describes the work, deliverables, scope, and tasks.
• MOA (Memorandum of Agreement): Documents a formal agreement about roles or responsibilities.
• MOU (Memorandum of Understanding): Records a general mutual understanding, often without detailed service metrics.

1. The specific table — for example, incident
2. The parent table — for example, task
3. The wildcard table — *, which applies broadly

• 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.

• Honeypots: Decoy systems or services designed to attract attackers. Legitimate users should not access them, so activity there is a strong indicator of compromise.
• DNS sinkholes: Redirect malicious or suspicious DNS requests to a controlled destination. This can identify infected systems attempting to contact command-and-control infrastructure.

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

• Red team: Offensive security; attempts exploitation and simulates attackers.
• Blue team: Defensive security; monitors, detects, and responds to attacks.
• Purple team: Combines red- and blue-team activities to improve defenses, but is not the best direct answer here.
• White team: Usually oversees or coordinates an exercise, including rules of engagement and scope.

• Instant messaging/chat: Can be abused to send malicious links or attachments, but is not the answer most directly associated with high-risk file sharing.
• E-mail: A common malware delivery method, but the question emphasizes an application type known for direct file exchange.
• End-to-end applications: This describes communication protection or architecture, not a specific malware distribution risk.

• Training or coaching
• Mentoring
• Additional support or resources
• Targeted performance improvement plans

• A: Recognition may be appropriate, but awards do not address identified gaps.
• C: Rotating schedules does not necessarily improve the specific competencies that are missing.
• D: Assessment results should be handled sensitively, but keeping them entirely private prevents useful feedback and development discussions.

• Remote and global work: Access is based on the approved device, not a specific office or geographic location.
• Seamless login: Users may not need to repeatedly enter credentials on a recognized device.
• Limited equipment: It uses devices employees already have rather than requiring separate hardware.

• Geotagging: Restricts access based on location and may prevent legitimate remote work.
• Smart cards: Require issuing and managing additional physical equipment.
• Time-based logins: Limit access by time and do not provide a seamless authentication experience.

• Portfolio definition cycle — establishes and maintains the portfolio strategy, objectives, and management framework.
• Portfolio delivery cycle — coordinates and monitors the delivery of change initiatives, ensuring the portfolio remains aligned with strategic objectives and delivers value.

• Practice — a structured area of portfolio management activity, such as risk management or resource management.
• Technique — a method used to perform an activity; it is not the term for portfolio delivery itself.
• Principle — a guiding rule for effective portfolio management.

• Two-part tariff pricing: $10 per unit
• Dual pricing: $20 per unit

Two-part tariff pricing

Dual pricing

• Division X, the seller, is credited with the market price: \(\$20\)
• Division Y, the buyer, is charged the marginal cost: \(\$10\)

apex 
for (Account updatedAccount : Trigger.new) { 
    AccountTriggerHelper.notinyxternalSystem(updatedAccount.Id); 
}

• Too many callouts: The callout occurs asynchronously in the future method, and each future transaction can perform its permitted callouts.
• Too many SOQL queries: The SOQL query is inside the future execution, not repeatedly in the trigger transaction.
• Callout from triggers not supported: Direct callouts from triggers are prohibited, but the trigger delegates the callout to asynchronous Apex, which is the correct pattern.

• Existing measures
• Relationships
• Calculated columns
• Tables and fields
• Existing transformations in the model

• SharePoint folder: Reconnects to the source files. You would likely need to recreate the model and measures.
• Power BI dataflows: Primarily provide reusable data preparation and storage, but they do not automatically provide the existing semantic model and measures.
• Excel workbook: Connects directly to the source file and would also require rebuilding the model and measures.

1. Initiate — establish the project, scope, team, and governance.
2. Plan — develop the detailed plan, schedule, resources, and implementation approach.
3. Execute — configure, integrate, migrate, test, and prepare the solution.
4. Deploy — move the solution into production and support go-live.
5. Close — complete handover, confirm outcomes, and formally close the project.

1. Create Workspace2 with Lakehouse2 — F
2. Migrate the Employee table to Lakehouse2 — E
3. Assign the data engineer the Contributor role for Workspace1 — D

Why

• Sharing Lakehouse1 would not provide the required isolation.
• Viewer access would not allow writing to Customer.
• Giving Contributor access to Workspace2 would expose the sensitive table.

• Red team: Simulates attackers and tests exploitability.
• Blue team: Defends, monitors, detects, and responds to attacks.
• Purple team: Combines red- and blue-team activities to improve cooperation and defenses.
• White team: Manages and oversees the rules, scope, and authorization of the exercise.

• User1 (user1@contoso.com) — This is an external guest in the Fabrikam tenant. Assuming the guest uses email one-time passcode authentication, Azure AD emails a passcode to user1@contoso.com.
• User2 (user2@outlook.com) — An Outlook.com address can authenticate with a Microsoft account, so Azure AD uses that account’s authentication rather than sending an email OTP. The fact that User2 has never accessed Fabrikam resources does not by itself trigger OTP.
• User3 (user3@fabrikam.com) — This is an internal Fabrikam user, so the user signs in with the organization’s normal credentials and does not receive a guest OTP.