Salesforce Certified AI Specialist Exam Prep
Certified AI Specialist (Page 16 )

• Endpoint Manager: manages hosts and sensor-related settings.
• Falcon Investigator: supports investigation and analysis, but does not necessarily grant RTR access.
• Remediation Manager: handles remediation-related actions rather than interactive host access.

• C — Custom buttons display at the top and bottom of a page: Correct. In Salesforce Classic, buttons can appear in the page’s button areas, including the top and bottom of record pages.
• D — Custom buttons are available for Person Accounts: Correct. Person Accounts use the Account object, so Account custom buttons can be available on Person Account layouts.
• E — Custom buttons can reference an external app: Correct. A URL custom button can launch or navigate to an external application or website.

• A: JavaScript custom buttons are a Salesforce Classic feature and are not supported in Lightning Experience. They do not enhance Lightning Experience.
• B: The User object does not generally support custom buttons in the same way standard business objects do.

• 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.

• Suspended an operator who refused to use unsafe equipment.
• Paid another operator a bonus for using it.
• Prioritised short-term productivity over employee safety.

• A — Management is not particularly concerned with managing risks.

• B — Employees will perceive that management does not care about health and safety risks.

• C — The factory’s safety record is likely to be poor.

• The application failing to start or becoming unhealthy
• An incorrect probe path, port, or protocol
• The application needing more startup time
• Dependency or configuration failures
• A liveness probe being too aggressive

bash 
kubectl describe pod <pod-name> 
kubectl logs <pod-name> --previous

• Scale to more replicas: may hide the issue but does not diagnose it.
• Decrease initialDelaySeconds: makes probes run earlier and could worsen startup failures.
• Drain and reboot the node: node metrics are normal, so rebooting is not justified as the first step.

• A. IDS attack signatures: Primarily detects suspicious network activity, not necessarily malware embedded in uploaded files.
• C. Load balancer: Improves availability and distributes traffic; it does not inspect documents for malware.
• D. WAF: Protects web applications from attacks such as SQL injection and command injection, but its primary role is not scanning uploaded PDFs for malware.

• 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.

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

• 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.

• Load balancer: Distributes application traffic; it does not protect switch MAC tables.
• IPS: May detect some attack traffic, but it is not the primary control for switch-port MAC learning.
• NGFW: Protects at network boundaries but does not directly limit MAC addresses learned on access ports.

• Transport and handling
• Storage and warehousing
• Refrigeration
• Shelf-stacking or replenishment
• Other costs directly attributable to product P

• 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.

• A — Increasing the minimum password length to 14 characters: Longer passwords have more possible combinations, making them harder to guess or crack through brute force.
• F — Requiring at least one special character: This increases password complexity and expands the possible character combinations.

• MD5 to SHA-512: Improves password-hash resistance, but does not stop users from choosing easy-to-guess passwords. Also, modern systems should use a password-specific hashing algorithm such as bcrypt, scrypt, or Argon2.
• Increasing maximum age to 120 days: Leaves weak passwords in use longer.
• Reducing minimum length to 10: Makes guessing easier.
• Reducing minimum age to zero: Allows immediate password changes but does not make the password itself harder to guess.

1. Install a Cassandra-compatible ODBC driver.
2. Configure a data source name (DSN), if required.
3. In Power BI Desktop, select Get Data > ODBC.
4. Choose the configured DSN and connect.

• Microsoft SQL Server database: Connects to SQL Server, not Cassandra.
• OLE DB: Requires a compatible OLE DB provider; this is not the standard choice for Cassandra in Power BI.
• OData: Requires Cassandra data to be exposed through an OData service, which is not the normal direct connection method.

• 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.

• Existing expected ROI: 15%
• New project ROI: 14%
• Cost of capital: 12%

• Project return = 14%
• Cost of capital = 12%
• It earns 2% more than the cost of capital, so it should increase shareholder value.

• Escape to host: A virtualization attack where code escapes a guest VM and accesses the host system. Nothing in the scenario mentions virtualization.
• Browser extension: Can redirect or manipulate web-browser traffic, but not normally database-server traffic.
• Valid accounts: Describes using stolen or compromised credentials, not redirecting network traffic.
• Process injection: Injecting malicious code into a legitimate database or networking process could allow an attacker to alter how that process handles outgoing traffic.

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

• Regression predicts continuous numeric outcomes, such as house price, temperature, or sales amount.
• Linear regression assumes the target can be estimated from a linear relationship between the input features and the target.
• In Azure Machine Learning, you use a labeled dataset containing:

• Classification predicts a category or class, such as “spam” or “not spam.”
• Clustering groups similar records without a known label; it is an unsupervised learning technique.

• Server provisioning
• Operating systems and runtime infrastructure
• Scaling
• Much of the maintenance and patching

• Thin clients reduce endpoint hardware requirements but do not specifically streamline code deployment.
• Private cloud provides dedicated cloud infrastructure but usually requires more management and expense.
• Virtual machines improve resource utilization, but administrators still manage the VMs, operating systems, and deployments.

• Power BI dataset — Reuses the existing tables, relationships, and measures. You mainly create new visualizations.
• SharePoint folder — Connects to the source files, but you would need to rebuild the model and measures.
• Power BI dataflows — Primarily provide reusable data preparation; they do not automatically provide the existing report’s measures and model.
• Excel workbook — Requires reconnecting to and modeling the source data again.

• Periodic vulnerability assessments: Identify technical weaknesses but do not establish governance or ensure risks are managed.
• Established information security metrics: Help measure performance and report status, but measurement alone does not make governance effective.
• Advanced security technologies: Support security operations, but governance is primarily about direction, accountability, decision-making, and alignment with business objectives.

1. Get Data > Folder

1. Expand the Attributes column

1. Remove the Content column

• Folder connector: lists files and their metadata, but also includes a Content binary column.
• Combine Files: processes and combines the actual CSV contents, which is explicitly disallowed here.

• A password cracker would normally be identified by behavior such as loading password hashes or attempting dictionary/brute-force attacks.
• The question describes a routine audit, not password recovery.
• Simply encountering a protected file during an audit is characteristic of a misconfigured or insufficiently privileged FIM.

• Each Azure VM must have at least one network interface (NIC).
• A single NIC can have:

• Therefore, each of the five VMs needs only one NIC:

• 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.

• Vulnerability scanner: Identifies technical weaknesses in systems, applications, or devices.
• Penetration test: Simulates attacks to determine whether vulnerabilities can be exploited.
• SCAP (Security Content Automation Protocol): Uses standardized formats and protocols for automated vulnerability, configuration, and compliance checks.
• Illumination tool: Maps and analyzes broader supply-chain exposure and third-party risk.

• MFA adds an additional authentication factor, such as a phone notification or verification code.
• It helps prevent unauthorized sign-ins, even if a password is compromised.
• It does not encrypt, store, or protect credentials used by deployment processes.

• 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.

• 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.

• Database data: Aggregates are used to retrieve structured data, commonly from entities and database sources.
• Screen scope: A Screen Aggregate belongs to the screen where it is defined and is not directly reusable as a screen-level aggregate elsewhere.
• Asynchronous and parallel execution: Multiple Screen Aggregates can run asynchronously and in parallel, helping the screen load data efficiently.

• A. IDS attack signatures: An IDS primarily detects suspicious network activity; it is not the best control for scanning uploaded documents for malware.
• C. Load balancer: Distributes traffic among servers and improves availability, but does not inspect files for malware.
• D. WAF: Protects web applications against attacks such as SQL injection and command injection. It may help secure the upload function, but malware scanning is the key requirement here.

• AWS AppSync is designed for serverless applications that need to retrieve and combine data from multiple sources.
• A pipeline resolver can invoke multiple functions or data-source resolvers, including resolvers connected to different DynamoDB tables.
• The application can receive the combined result through one GraphQL request, without requiring custom aggregation logic in the application.
• This is operationally efficient because AppSync manages the API layer and resolver execution.

• Athena Federated Query is intended primarily for analytics and ad hoc querying, not low-latency application data retrieval.
• Querying DynamoDB through Athena can consume DynamoDB read capacity and may affect table performance.
• It also introduces analytical-query overhead and is not the normal choice for a microservice web application.

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.

• Replaces the verbal message — this describes non-verbal communication being used instead of words.
• Substitutes for verbal communication — similar; it means communicating without speech.
• Confuses the verbal message — this occurs when non-verbal signals contradict or obscure the spoken message.

• state preserves the client’s original context, such as the specific idea URL the user requested.
• The portal sends that value in the OAuth authorization request.
• Salesforce returns it after authorization, allowing the portal to redirect the user to the original idea rather than the Ideas home page.

• 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.

• A — Use a custom controller: An Apex class can contain the page’s logic.
• C — Use a standard controller with extensions: The standard controller provides basic CRUD behavior, while an extension adds custom logic.
• E — Use a standard controller: Useful when the page works mainly with one Salesforce object and needs standard functionality.

• A page with no controller for static or controller-free content.
• A custom controller with extensions; extensions are not limited only to standard controllers.

• 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.

• Security controls
• Processes and procedures
• Compliance evidence
• Performance against contractual requirements

• Service-level agreement (SLA): Defines expected service performance, such as uptime and response times.
• Memorandum of agreement (MOA): Documents a general agreement between parties, but does not necessarily provide audit rights.
• Supply chain analysis: Identifies risks across suppliers and dependencies, but is not a contractual mechanism for reviewing vendor controls.

• 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.

• Microservices: An application-design approach that divides an application into smaller services. It does not inherently reduce the number of operating systems.
• Virtualization: Creates virtual machines, but each VM generally requires its own complete operating system. This improves isolation but does not minimize OS instances as effectively.
• Infrastructure as code: Uses code to automate infrastructure deployment and configuration. It improves consistency but does not determine how many operating systems are used.

• Un AG puede tener réplicas en Windows y Linux desde SQL Server 2017; por tanto, una réplica Windows y otra Linux es posible.
• Sin embargo, las réplicas de un AG deben utilizar normalmente la misma versión principal de SQL Server. Una instancia SQL Server 2017 no puede tener directamente una réplica secundaria SQL Server 2019 como configuración normal y permanente.
• En tu escenario, SQL Server 2017 en Windows y SQL Server 2019 en Linux no se pueden añadir directamente como réplicas equivalentes de AG1. Primero habría que realizar un proceso de actualización/migración compatible, por ejemplo mediante una actualización gradual o una tecnología de migración como log shipping o distributed availability groups, según el diseño.

• Tipo de clúster y mecanismo de quorum.
• Failover normalmente manual en configuraciones multiplataforma.
• Edición y características compatibles.
• Configuración de endpoints y permisos.
• Limitaciones específicas de SQL Server en Linux.

• Asynchronous inference is designed for applications that submit individual inference requests, place them in a queue, and retrieve results later. It is useful when requests may take a long time or when traffic is intermittent.
• Batch transform is designed specifically to run inference over an entire large dataset stored in Amazon S3 and produce an output dataset.

• Large dataset/offline processing ? Batch transform
• Large or slow individual requests processed later ? Asynchronous inference

• 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.

• D — Create sibling resource pools for the Production VMs and Test VMs.

• B — Configure a memory reservation on the Production resource pool.

• Shares only determine relative priority when resources are scarce; they do not guarantee memory.
• A parent resource pool alone does not provide a guarantee.
• A child pool for Test VMs does not reserve memory for Production.

• Reduce the training data: Usually makes overfitting worse.
• Add hyperparameters: Hyperparameters already control training; simply adding them does not solve the problem. Proper tuning could help, but that is not what the option states.
• Increase training time: More training can worsen overfitting if the model is already memorizing the training data.

• 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.

• Virus signatures: Primarily associated with antivirus or antimalware tools.
• Security agent deployment: Usually handled by endpoint-management or endpoint-security platforms.
• Vulnerability scanning: Performed by vulnerability-assessment tools, although a SIEM may ingest their results.

• Sets a high initial price for a new product.
• Targets customers willing to pay more, often called early adopters.
• Gradually reduces the price to attract more price-sensitive customers as the product becomes less novel and competition increases.

• Penetration pricing: starts with a low price to gain market share quickly.
• Premium pricing: maintains a high price to communicate superior quality or status; it does not necessarily involve later price reductions.
• Loss leader pricing: sells one product at a very low price, sometimes below cost, to attract customers who may buy other products.