OutSystems Associate-Reactive-Developer Exam Prep
Associate Reactive Developer (OutSystems 11) (Page 10 )

• A) Entities do not require an identifier. False. In OutSystems, an Entity must have an identifier (a primary key) to uniquely identify records.
• B) Entities are only stored in memory. False. Entities are persisted in the database; they are not limited to in-memory storage.
• C) Entities have attributes. True. Entities define attributes (fields) that describe the data.
• D) Entities can be created, updated, and deleted. True. CRUD operations apply to Entities.

• prompt: the input or instruction given to the model
• completion: the desired response

json 
{"prompt":"Summarize this customer complaint.","completion":"The customer reports a delayed shipment."}

• B: A .txt file containing CSV-style lines is not automatically a valid fine-tuning dataset. The required structure and format must match the selected Bedrock model.
• C: Provisioned Throughput provides dedicated inference capacity; it does not fine-tune a model.
• D: Journals and textbooks might support domain adaptation or pretraining, but they do not provide the prompt-to-answer examples typically required for supervised fine-tuning.

• administrators — Full access to switch configuration and REST API functions; excessive for this requirement.
• sysadmin — Intended for highly privileged system administration, not basic monitoring.
• helpdesk — More limited and focused on troubleshooting/support functions; it does not match the stated default role and level-1 requirement as directly.

• 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.

• 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.

• Works across SaaS and internal applications: TOTP is widely supported by authentication systems and can be integrated into many applications.
• Device manufacturer agnostic: A hardware token or authenticator application can generate the code without depending on a specific computer or phone manufacturer.
• Offline capability: The code is generated locally using a shared secret and the current time; an internet connection or cellular service is not required.

• Username and password: May work offline but provides weaker authentication and does not meet the intended improvement in security.
• Biometrics: Can depend on device hardware, operating-system support, and enrollment mechanisms.
• SMS verification: Requires cellular connectivity and is vulnerable to threats such as SIM swapping.

• Admin access to the deployment pipeline (B) – lets the developers use the pipeline and deploy content.
• Contributor access to the Development and Test workspaces (E) – required to deploy items into those workspaces.
• Viewer access to the Production workspace (D) – lets them view Production content without allowing deployment or modification.

• Contributor access to Production (F), because that could allow changes or deployment there.
• Viewer access to Development/Test (C), because Viewer is insufficient for deployment.
• Build permission to Production semantic models (A), because building reports on a semantic model is not required merely to view Production items.

• Forecasting lets sales leaders predict revenue for upcoming fiscal periods, compare forecasts with targets, and review performance by salesperson or team.
• Opportunity Stages help determine the likelihood that opportunities will close. Each stage can have a probability, which contributes to forecast calculations.

• Sales Quotes: Used to present pricing or product proposals to customers; they do not provide revenue forecasting.
• Opportunity List View: Helps users filter and view opportunities, but it is not the forecasting tool.

• A: Using an external OAuth 2.0 identity provider could provide unified identity, but it does not specifically address Salesforce capacity or high-volume login limits.
• B: Making the Experience Cloud community a SAML identity provider and using JIT provisioning is a possible federation pattern, but it may not be appropriate for this scale without Salesforce validation.
• C: A default account is unrelated to solving identity unification and high login throughput. Person Accounts can be supported in appropriate B2C Commerce integrations.

• 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.

• 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.

• 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.

• R-squared: Typically used for regression, not classification.
• RMSE: Measures prediction error for continuous numerical values, so it is not the best fit here.
• Learning rate: A training hyperparameter that controls how quickly the model updates its weights; it is not an evaluation metric.

• Leadership and stakeholder commitment
• Business capability and skills
• Organizational culture
• Availability of resources
• Ability to manage and sustain change
• Impact of the proposed transformation

• How ready the organization is
• Which areas require urgent attention
• How difficult each issue may be to resolve
• Risks that could affect implementation

• A: Places the assessment in Phase B and refers vaguely to creating views; this is not the prescribed technique.
• B: An Implementation Factor Assessment and Deduction Matrix is not the primary TOGAF technique described for business transformation readiness.
• D: A Business Scenario helps identify requirements and stakeholder concerns, but it is not the main technique for assessing organizational readiness.

• An Azure pay-as-you-go subscription follows an operational expenditure (OpEx) model.
• With OpEx, the organization pays for services as they are used, typically based on consumption.
• There is no need to purchase and maintain physical servers upfront.
• This contrasts with capital expenditure (CapEx), where the company makes a significant upfront investment in infrastructure, such as on-premises Hyper-V hosts.

• 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.

• 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.

• 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.

• netstat: Shows local network connections and listening ports, but not which WAN path carries the traffic.
• nslookup: Resolves domain names to IP addresses.
• ping: Tests reachability and latency but does not show the route.

• Check whether the data is accurate, complete, and properly prepared.
• Confirm that the pattern is not caused by an outlier, data-quality problem, or modeling issue.
• If the data is valid, treat the result as a potentially valuable new business insight.

• A: A data scientist may help, but expert validation and data-quality checking come first.
• C: Filtering out inconvenient data risks hiding a valid insight.
• D: Einstein’s result should not be accepted without verification simply because it produced the finding.

• Compensating control: The server is end-of-life, so it may no longer receive security patches or support. Placing it on a restricted VLAN provides an alternative layer of protection by reducing who can access it and limiting its exposure.
• Technical control: VLAN segmentation and access control lists (ACLs) are technology-based mechanisms that enforce network access restrictions automatically.

• Managerial: Policies, procedures, and governance—not network configuration.
• Physical: Locks, guards, or barriers.
• Corrective: Restores systems after an incident.
• Detective: Identifies suspicious activity rather than restricting access.
• Deterrent: Discourages behavior but does not enforce access rules.

• tag=Priv searches the tag field for values beginning with Priv. The wildcard can match the remaining characters, so it matches Privileged.
• tag=Priv would search for the exact tag Priv, not Privileged.
• tag=priv* uses lowercase priv; tag matching is treated as case-sensitive here, so it may not match the tag Privileged.
• tag=privileged uses the wrong capitalization for the exact tag.

• Amazon S3 — Object storage, not a database.
• Amazon DynamoDB — Fully managed NoSQL key-value and document database.
• Amazon Redshift — Managed data warehouse designed for analytics, not primarily transactional MySQL workloads.

• Inherent risk: Risk that exists before controls are implemented.
• Avoided risk: Risk eliminated by choosing not to perform the risky activity.
• Operational risk: Risk arising from failures in processes, people, systems, or daily operations.

• SQL injection (SQLi): Attacks databases by inserting malicious SQL commands.
• Cross-site scripting (XSS): Injects scripts into web pages viewed by other users.
• Sideloading: Installing an application from outside the official app store. It may install unauthorized apps, but it does not generally unlock the operating system or enable restricted system features.

• 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.

• 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.

• Identity provider (IdP): Authenticates users and asserts their identity.
• Service provider (SP): The application being accessed—in this case, Salesforce/the employee portal.
• Identity store: A directory that stores user identities, such as Active Directory.
• Authentication store: A system used to validate credentials.

• Input feature distributions differ from training data ? Analyze dataset drift metrics

• Model accuracy drops without code changes ? Analyze dataset drift metrics

• Endpoint latency increases under load ? Investigate scaling and infrastructure metrics

• Online payment fraud
• Account takeover
• Fake account creation
• Suspicious transactions

• 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.

• 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.

• 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.

• You provision the virtual machine.
• You manage the guest operating system, applications, and configuration.
• Azure manages the physical servers, datacenter, and underlying virtualization infrastructure.

• 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.

• 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.

• The user starts in the corporate portal.
• The portal launches the Salesforce resource.
• The IdP sends the SAML response to Salesforce.

• Connected App + OAuth is for OAuth authorization and API/app access, not this SAML-based seamless login scenario.
• SP-initiated SSO would begin when the user first requests the Salesforce resource and Salesforce redirects them to the IdP. That is not the described starting point.

• 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.

• A. Number ? Decimal — Correct. Salesforce Number fields are represented in Apex as Decimal.
• D. Date/Time ? Datetime — This is correct conceptually, but “Dateline” is not an Apex type. If the option literally says “Dateline,” it is incorrect.
• E. Checkbox ? Boolean — Correct. A checkbox contains true or false.

• Number ? Integer — A Number field maps to Decimal, even when its scale is zero.
• Text Area ? List<String> — A text area maps to a single String, not a list.

• A — conformant: Incorrect because one explicit requirement is violated.
• B — consistent: “Consistent” is not sufficient where the implementation contradicts a mandatory specification. The RPC mechanism is covered by the architecture, and the implementation differs from it.
• C — consistent: Incorrect reasoning: the RPC mechanism does have a defined architectural requirement, so conformance must be assessed.
• D — non-conformant: Correct because the implementation fails to follow the specified RPC/threading requirement.

• A. Configure prompt modifications to enforce tone, disclaimers, and refusal behavior at the system level.

• D. Configure Power Platform DLP policies to restrict unauthorized data connectors.

• B: Manual topic-by-topic disclaimer edits are specifically discouraged.
• C: Channel settings do not replace agent-level Responsible AI controls.
• E: Publishing before enabling safety filters violates the stated deployment sequence. Responsible AI filters should be enabled before publication, not afterward.

• A. Microsoft 365 group with Assigned membership
• C. Microsoft 365 group with Dynamic User membership

Why?

• Assigned membership: You explicitly add User1, User2, and User3.
• Dynamic User membership: Membership is automatically determined by a rule based on user attributes.

Why the other options are incorrect

• B and D: Security groups do not support the Microsoft 365 group expiration policy.
• E: Dynamic Device groups are intended for devices, not these users, and are also security groups.

• 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.

• staff use the new system;
• transactions and reports are checked;
• problems are corrected;
• feedback is collected.

• Phased changeover: different parts or functions are introduced in stages, often according to a planned sequence.
• Pilot changeover: one representative department, branch or group acts as a test site before wider implementation.
• Parallel changeover: old and new systems operate at the same time.
• Direct changeover: the old system is stopped and the new one starts immediately.

• Confirm the required columns and data types
• Identify the target/label column
• Handle missing or duplicate records if present
• Transform data into a suitable format
• Split it into training and validation/test datasets

1. Prepare the training data
2. Select an algorithm or configure AutoML
3. Train the model
4. Evaluate its performance
5. Tune hyperparameters if needed
6. Deploy 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.

• 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.

• Open or insecure ports
• Enabled legacy or insecure protocols
• Known vulnerabilities and misconfigurations
• Weak services and outdated software

• curl tests web requests and HTTP-based services.
• Wireshark captures and analyzes network traffic; it does not normally scan servers for weaknesses.
• netcat can test connectivity to individual ports and sometimes grab service banners, but it is not a comprehensive vulnerability scanner.