Salesforce Certified MuleSoft Developer I Exam Prep
Certified MuleSoft Developer I (Page 9 )

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

• An Adj-SID does not necessarily need manual configuration.
• It can often be dynamically allocated by the router, although manual configuration may also be possible.
• The adjacency information is advertised through the IGP, such as IS-IS or OSPF.

• It is identified by an Adj-SID.
• It represents a particular adjacency of a node.
• Its meaning is generally local to the advertising node; unlike a Node-SID, it is not a globally reusable instruction across the network.

• 10 TB with maximum I/O performance: Use EC2 instance store. It provides very high-throughput, low-latency local storage suitable for temporary video-processing data. The application must tolerate data loss because instance store is ephemeral.
• 300 TB of highly durable media: Use Amazon S3, which is designed for highly durable object storage and can scale to this size.
• 900 TB of inactive archival media: Use S3 Glacier, which provides lower-cost storage for data that is rarely accessed.

• A: Amazon EBS offers high performance but is not the best fit for the question’s “maximum possible I/O” requirement compared with local instance store.
• B: Amazon EFS is durable and shared, but is generally more expensive and less suitable for very large archival storage.
• C: Uses EC2 instance store for performance, but incorrectly uses EFS for the 300-TB durable tier and S3 rather than Glacier for archival data.

• The servers run different operating systems: Windows, Linux, and Unix.
• Containers generally share the host operating system’s kernel, so they cannot normally run workloads requiring unrelated kernels, such as Windows and Linux, on the same Linux host.
• A hypervisor can create separate virtual machines, allowing each VM to run its own guest OS.
• A Type 2 hypervisor runs on top of a host operating system and can support multiple guest operating systems.

• Employees can use approved devices from remote locations or worldwide offices.
• Users do not need to carry or insert extra hardware.
• It helps prevent account takeovers from unknown devices.

• Geotagging: Restricts access based on location, which could interfere with remote work and travel.
• Smart cards: Require additional physical equipment and card readers.
• Time-based logins: Limit access according to time but do not strongly bind access to an authorized user device.

• Password spraying: Tries a few common passwords against many accounts; no indication of repeated login attempts.
• Remote-access Trojan (RAT): Could install malware, but it does not explain how the attacker obtained the administrator’s credentials.
• Dictionary attack: Tries words or common passwords against an account; again, the scenario specifically highlights Telnet’s lack of encryption.

• A — Correct: Identify the data required by Salesforce, its dependencies, and how it should be validated. Verification scripts help confirm record counts, relationships, field mappings, and data integrity after migration.
• D — Correct: Use a full sandbox and perform trial migrations using realistic—or appropriately masked—legacy data. This exposes transformation, volume, dependency, and integration issues before production cutover.
• B — Less appropriate: Phased user migration and parallel operation primarily address user adoption and rollout risk, not the technical risks of data migration.
• C — Less appropriate: Although sandbox testing and integration testing are valuable, the option emphasizes test-data generation rather than validating the migration with representative legacy data. “A full sandbox for all systems” may also be impractical.

• 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.

• A is correct: It establishes the revised dates and identifies the effect on the critical path.
• B is premature: Stakeholders should be informed after the impact has been assessed and the updated schedule is understood.
• C is not automatically appropriate: Fast-tracking may introduce additional risk and should be considered only after analyzing schedule options.
• D is premature: Adding resources may not resolve a dependency and could increase costs without addressing the actual constraint.

• 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.

• Restarting the device: may fix software problems, but not a directional connection issue.
• Swollen battery: is a safety concern, but would not typically cause recognition only in one orientation.
• Failing cable: possible in general, but less likely because it works on other similar devices.
• Dirty or damaged port: best matches the symptoms. Inspect and carefully clean the port, or have it serviced if damaged.

• Due diligence: Investigating and evaluating a third party before entering into or continuing a business relationship.
• Attestation: An independent party provides assurance about an organization’s claims or controls. A SOC 2 examination is an example of an attestation engagement, but the analyst requesting and reviewing the report is performing due diligence.
• Internal audit: Reviews the organization’s own internal controls.
• Penetration testing: Actively tests systems for exploitable vulnerabilities.

• Espionage: Stealing information for intelligence or competitive purposes.
• Data exfiltration: Unauthorized removal or transfer of data.
• Nation-state attack: A sophisticated attack sponsored by a government.
• Shadow IT: Unapproved technology or access methods used by employees.

• CHAP: Uses a challenge-response exchange, so the password is not directly transmitted.
• IPsec: Provides authentication, integrity, and encryption for IP communications.
• EAP: An authentication framework that supports stronger methods, such as certificates or token-based authentication.

• The message came from the claimed sender (authentication)
• The message was not altered in transit (integrity)
• The sender cannot easily deny having signed and sent it (non-repudiation)

• Compliance standards: May be a reason in some organizations, but it is not the primary security benefit.
• Increase delivery rates: Digital signatures do not generally improve email delivery.
• Block phishing attacks: Signatures can help recipients verify legitimate messages, but they do not block phishing by themselves.

• A: It allows for branching and merging...

• C: It allows multiple engineers to work against the same code and configuration files and manage differences and conflicts.

• B: Build automation and infrastructure provisioning are handled by CI/CD and automation tools, not by version control alone.
• D: User Stories and backlogs are managed by project-management tools.
• E: Version control stores and tracks code, but it does not itself ensure that developers write effective unit tests.

• 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.

• Azure Cosmos DB is a globally distributed NoSQL database service. It stores and retrieves application data, but it does not provide the complete environment for building, testing, and deploying predictive analytics models.
• Azure Machine Learning is the appropriate service for this requirement. It supports creating experiments, training and testing models, and deploying them for predictions.
• Azure Machine Learning Studio provides the browser-based interface for these tasks.

• Compute: Not used; no virtual warehouse is required.
• Data Storage: Not scanned again.
• Metadata: May help Snowflake manage and validate cached results, but it is not the Snowflake architectural layer identified as serving the request.
• Cloud Services: Handles query coordination, metadata services, authentication, and result-cache access.

• The type of change: standard, normal, or emergency
• The risk, impact, and complexity
• The change model being used

• A standard change may be pre-authorized through its change model.
• A normal change may require assessment and approval by an appropriate change authority.
• An emergency change may be authorized by an emergency change authority, often using an expedited process.

• Change authorities are not only needed for emergency changes.
• They are not assigned only when a change is deployed.
• They are not only required for normal changes.

1. insert con; ? 1
2. Database.setSavepoint(); ? 2
3. update con; ? 3
4. Database.rollback(sp_admin); ? 4

• Azure Machine Learning is the overall Azure service.
• Machine Learning designer is the visual, drag-and-drop interface within Azure Machine Learning.
• Microsoft may refer to the broader product as Azure Machine Learning studio, while “Designer” remains the specific visual workflow tool.

• Azure Logic Apps: Workflow and integration automation.
• Azure Batch: Large-scale parallel or batch compute.
• Azure Cosmos DB: Globally distributed NoSQL database.

• Unfamiliar locations or IP addresses
• Anonymous or malicious IP addresses
• Leaked credentials
• Unusual sign-in behavior

• Owner, Contributor, and Network Contributor provide sufficient management permissions.
• Reader can view Traffic Analytics data but cannot enable or configure it.

• 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: \(\$10\)

• Maximum response and resolution times
• Expected uptime or availability
• Performance requirements
• Escalation procedures
• Consequences for failing to meet requirements

• SOW: Defines a project’s scope, tasks, deliverables, and schedule.
• MOA: Documents specific responsibilities agreed upon by two parties.
• MOU: Records a general understanding or intent to cooperate.

• LastName: Required.
• FirstName: Optional.
• AccountId: Optional; a Contact may be associated with an Account later or remain private, depending on organization settings.
• Name: A compound display field made from first and last name; it isn’t entered as a separate field.

• User preferences change, so the model must learn from recent data.
• Keeping the existing data helps preserve knowledge of older patterns and provides a broader training distribution.
• Training only on new data can cause catastrophic forgetting and may overfit if the new dataset is small.
• The new data should not automatically be used as the test set, because it is needed for training and the model must still be evaluated on separate, representative data.

• Identifying the communication strategy: Usually part of a business continuity or incident response plan.
• Evaluating the risk management plan: Part of risk assessment and risk management activities.
• Establishing backup and recovery procedures: Usually part of disaster recovery planning.
• Developing the incident response plan: Part of incident response planning.

• Tokens: Individual units of text processed by a model, such as words, subwords, or characters.
• Models: Systems that learn patterns and generate predictions or outputs.
• Binaries: Data represented using the binary number system, not semantic representations.

• 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.

• 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 requirement is to obtain an assessment of the Azure environment’s design.
• The proposed solution is the Premier support plan.
• Premier can provide this type of guidance, but it is a higher-tier, more expensive option.
• The question specifically says to keep costs to a minimum. A lower tier—typically Professional Direct in the support-plan model used by this question—provides architectural/design guidance.

• SQL injection
• Cross-site scripting (XSS)
• Malicious file uploads
• Common web-application exploits

• Layer 4 firewall: Filters primarily by IP addresses, ports, and transport protocols; it lacks detailed web-application inspection.
• NGFW: Provides advanced network filtering and may include application awareness, but a WAF is more specialized for protecting web applications.
• UTM: Combines several security functions in one device, but it is not specifically focused on web-application attacks.

• Default network device credentials: More associated with external attackers or poor device configuration.
• Spear phishing emails: Commonly used to compromise users, but less characteristic of an insider who already has access.
• Typosquatting and impersonation: Primarily social-engineering techniques aimed at deceiving users.
• Unidentified removable devices: Provide a direct way to transfer data outside the organization and may bypass network monitoring.

• The JSON files contain one billion items, so this is a big-data workload.
• PySpark uses Apache Spark’s distributed, parallel processing, allowing the data to be processed across multiple compute nodes.
• It can read and transform data directly from OneLake, helping minimize unnecessary data movement or duplication.
• A Fabric notebook can also support exploration and visualization, as well as Spark-based analytics and anomaly-detection workflows.

• Pandas is primarily in-memory and generally suited to smaller datasets. One billion records would be impractical on a typical single machine.
• A Power BI report with core visuals is appropriate for visualization and sharing, but it is not the best tool for large-scale transformation, parallel processing, or anomaly detection. It would normally consume prepared data rather than perform the entire workload.

• Namespace: The namespace associated with the code where the checkpoint was set.
• Time: When the checkpoint was captured or executed.

• Exception: Exceptions are viewed through debug logs or execution results, not as the primary Checkpoints tab information.
• Debug Statement: System.debug() output belongs in the Logs tab. A checkpoint captures program state, such as variables and their values, at a specific point in execution.

• 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.

• Amazon SageMaker — charges apply for compute, storage, and other resources used.
• AWS Config — generally charges for configuration recording and rule evaluations.
• Amazon CloudWatch — has a limited free tier, but many metrics, logs, alarms, and API usage can incur charges.

• C: Develop the rule in the Rules Editor, define the events, match, and condition sections, then use the test rule feature. This directly validates the YARA-L rule without enabling it in production.
• A: UDM Search can help investigate data and refine filters, but it does not fully test YARA-L logic—especially complex event joins, match windows, and conditions.

• Accept: Acknowledging the risk without taking additional action.
• Transfer: Shifting responsibility or financial impact to another party, such as through insurance or outsourcing.
• Mitigate: Reducing the likelihood or impact of the risk through controls.
• Avoid: Eliminating the activity or condition that creates the risk.

• IRR assumes that interim cash flows can be reinvested at the project’s own IRR. This may be unrealistic, especially when the IRR is very high.
• MIRR assumes reinvestment at a specified rate, usually the company’s cost of capital or another realistic reinvestment rate.

• B: MIRR does not specifically favour projects with long payback periods.
• C: MIRR and IRR can rank competing projects differently.
• D: MIRR is not always higher than IRR; it may be higher or lower depending on the cash flows and reinvestment rate.

• The vulnerability scan identifies a vulnerability.
• The administrator verifies that the vulnerability is not present.
• Therefore, the scan produced a false positive.

• True positive: A vulnerability is reported and genuinely exists.
• False negative: A vulnerability exists, but the scan fails to detect it.
• True negative: No vulnerability exists, and the scan correctly reports no issue.

• HTTPS: Secure web traffic, not general command-line server administration.
• SNMPv3: Secure network monitoring and management, not interactive server login.
• RDP: Provides graphical remote desktop access. It can be secure, but it is not the direct replacement for Telnet in this scenario.
• SMTP: Used to send email.

• Accept: Acknowledging the risk and choosing not to take additional action.
• Transfer: Shifting the risk or financial consequences to another party, such as an insurer.
• Mitigate: Reducing the likelihood or impact through controls, such as patching or access restrictions.
• Avoid: Eliminating the activity that creates the risk.

• 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

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• Employees can work from any location, including remote sites and offices worldwide.
• Login can be relatively seamless after the device is registered.
• It does not require distributing additional physical authentication equipment.

• Geotagging: Identifies location, but location alone is not a strong authentication method and may prevent legitimate remote access.
• Smart cards: Provide strong authentication but require card readers and physical cards, increasing equipment and management requirements.
• Time-based logins: Typically involve one-time codes that users must enter, making the experience less seamless and potentially requiring a token or authenticator app.

• B: Developer Edition has limited user, storage, and data-volume capacity, making realistic community testing difficult.
• C: A Developer Edition org cannot contain sandboxes, so it cannot provide separate environments for development, integration, and UAT.
• E: A standalone Developer Edition org is not part of the production org’s deployment path, so change sets cannot be used to deploy from it directly to that production org. The team would need Metadata API, Salesforce CLI, or another deployment method.

1. Yes — Microsoft Foundry provides a secure, governed environment for building and managing generative AI applications and agents. It brings together models, data, tools, evaluation, deployment, and monitoring.

1. Yes — Foundry is designed for enterprise workloads and supports scaling AI applications as usage grows. Scalability comes from the underlying Azure services and managed infrastructure.

1. Yes — Foundry can be used in solutions involving image recognition and computer vision. Applications can use vision-capable models and Azure AI vision capabilities for tasks such as image analysis, object detection, and OCR.