Cisco 300-430 Exam Prep
Implementing Cisco Enterprise Wireless Networks (300-430 ENWLSI) (Page 11 )

• Amazon EC2 instances — ???????? ?? ?? ??????? CPU, memory ??? instance size ???????? ???????
• AWS Lambda functions — memory configuration ?????????? ???????
• Amazon EBS volumes — volume type ?? size optimize ???? ???????
• ??????? ECS workloads — resource configuration ? cost optimization-?? ???????

• Memory ? compute usage ?????????? ???? custom code ????? ???? development ? maintenance ??????
• Cost allocation tags ???? ????? ??? ?????? ???? ??????? ???; inefficient resource ??????? ?? recommendation ???? ???
• CloudTrail resource ???? ?? API activity ??????, resource utilization ????

• 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.

xml 
<apex:page> 
    <apex:stylesheet value="{!URLFOR($Resource.MyStyles, 'styles/main.css')}" /> 
</apex:page>

• <apex:includeScript> is for JavaScript.
• <apex:includeStyle> is not a valid Visualforce component.
• <apex:require> is not the Visualforce tag used to load CSS.

• 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.

• A — VARIANT "null" values are not the same as SQL NULL values: True

• B — Frequent, single-row DMLs: False

• C — Validate data before loading into the target table: True

• D — Use staging tables to manage MERGE statements: True

• The Intune device limit restriction does not apply in the normal way; DEM enrollment supports up to 1,000 devices.
• However, the Microsoft Entra maximum number of devices per user setting can still impose a limit when the enrollment creates an Entra device object.
• Therefore, a DEM account is not automatically unlimited. The effective limit depends on the Entra device setting and the enrollment/join type.

• File1.png — Yes: User1 can apply Label1 with the Microsoft Purview Information Protection client. The client supports labeling image files such as .png in this scenario.

• Folder2 — No: Folder2 is the root folder. The client does not allow labeling the root folder itself. Although the client can label ordinary folders, selecting one applies the label to existing files and subfolders—not automatically to future files.

• File1.docx — Yes: .docx is a supported Microsoft Word file type, so User1 can apply Label1 to it.

• CSIRT: A team that responds to and manages security incidents.
• CVSS: A scoring system for rating the severity of vulnerabilities.
• SOAR: A technology platform for automating and coordinating security operations and incident response.

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

• Shared capacity

• Fabric capacity — F SKUs

• Fabric trial capacity

• Existing Power BI Premium — P SKUs

1. x = -100
2. -100 < x < 100
3. 100 = x < 1000
4. x = 1000

• -500 ? class 1
• 0 ? class 2
• 100 ? class 3
• 1000 ? class 4

• C — Create a form extension and implement validation

• D — Use Chain of Command (CoC) with a form extension class

• 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.

• Label applied does not automatically exclude a file from Copilot.
• Encryption/usage rights determine whether Copilot can access the file’s content.
• If the user has no permission under Label2, File3 should be unavailable to Copilot for that user.
• File3’s label might be inherited by derived content only if File3 was actually processed and contributed by an authorized user; it should not be treated as contributing merely because it exists in the source set.

• Company documents
• Databases
• Knowledge bases
• Current web or business data

• A: Describes diversity and inclusive design, not grounding.
• B: Describes explainability or model interpretability.
• D: Describes documenting a model’s capabilities and limitations.

• 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.

• Early units show relatively large time savings.
• Later units still take less time, but the reduction becomes progressively smaller.
• The curve therefore becomes flatter as production approaches 256 units.

• B: The reduction is not constant; learning normally diminishes over time.
• C: Time does not reduce at an increasing rate.
• D: A steady state may eventually be reached, but the question concerns the first 255 units while learning is still occurring.

• Injection
• Broken access control
• Authentication failures
• Security misconfiguration
• Cross-site scripting

• STIX: A standardized language and format for exchanging threat intelligence.
• OVAL: Used to describe and assess system vulnerabilities and configuration issues.
• Threat intelligence feed: Provides current indicators and intelligence about threats, but not necessarily a structured overview of common application exploitation methods.
• CVE: A catalog of individually identified, publicly disclosed vulnerabilities.

• transform() — modifies every element in an array
• filter() — keeps elements matching a condition
• exists() — checks whether any element matches
• aggregate() — reduces array elements to one result

sql 
SELECT transform(scores, x -> x * 2) 
FROM student_scores;

• A is incorrect because higher-order functions are mainly useful for nested or complex data.
• B is incorrect because they do not convert logic into Python.
• D is incorrect because their purpose is not to fix slow built-in functions, but to process arrays or maps with custom logic.

• 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.

• The requirement is an assessment of the Azure environment’s design, which requires a support plan offering proactive architectural guidance.
• Premier support would provide this capability, but it is a high-cost option.
• Since the requirement says to minimize expenses, Premier is not the best recommendation.
• A lower-cost plan with the required advisory/design-review capability—historically Professional Direct in Azure’s support-plan model—would be more appropriate.

• B — The most significant risks are held by SQ.

• C — SQ should recognise the cars as inventory.

• F — SQ recognises revenue when LM sells a car to a third party.

• A: LM does not hold the most significant risks.
• D: LM does not recognise the cars as inventory.
• E: SQ should not recognise revenue when cars are merely delivered to LM.

• Customers may boycott V’s products.
• Supermarket customers may stop buying from V.
• Investors may view V as having higher legal, ethical and reputational risk.
• V could face fines, lawsuits, contract losses and higher costs.
• Expected future profits may fall.

• Microsoft Foundry is an enterprise platform for developers, data scientists, and IT teams.
• It supports the full AI application lifecycle: selecting models, connecting enterprise data, developing, evaluating, deploying, monitoring, and scaling solutions.
• It can include visual tools and low-code experiences, but it is not primarily designed to enable business users to build complete generative AI solutions independently.

• B: You still need to select and configure an appropriate model.
• C: Business users may participate through visual tools, but they are not the primary target audience.
• D: Foundry includes low-code tools, but it is not fundamentally a low-code-only platform.

• 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.

• B — Both inner and outer classes can be declared as with sharing.

• C — Inner classes do not inherit sharing settings from the container class.

apex 
public with sharing class OuterClass { 
    public with sharing class InnerClass { 
        // Explicitly uses sharing rules 
    } 
}

• 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.

• Feedback form: Captures opinions, not necessarily actual behavior; users may not respond.
• Questionnaire: Relies on memory and subjective judgments about usefulness.
• Interviews: Can provide valuable qualitative insights, but a sample of users may not represent overall usage accurately.

• Input validation: Prevents malicious or malformed input within an application; it does not authenticate a software package.
• Secure cookies: Protect web-session cookies; they do not protect downloadable software.
• Fuzzing: Tests software by supplying unexpected input to find vulnerabilities; it does not verify software integrity.

• A — Tables
• B — Named file formats
• C — Schemas
• E — Databases

Why these are correct

• Tables: Can be cloned using CREATE TABLE ... CLONE. The clone initially uses zero-copy cloning, so storage is shared until changes are made.
• Named file formats: Can be cloned as database objects, preserving the file-format definition.
• Schemas: A schema and its eligible objects can be cloned.
• Databases: A database and its eligible schemas and objects can be cloned.

Why the others are incorrect

• Shares: A share is an account-level data-sharing object, not a normal cloneable database object.
• Users: Users are security principals and cannot be cloned with CLONE.

• Azure DevOps Analytics views are accessed through the Power BI Azure DevOps (Boards only) connector.
• This connector authenticates directly to Azure DevOps Services and lets you select an Analytics view.
• Analytics views allow filtering and shaping data in the cloud before Power BI loads it.
• Azure DevOps Server (Boards only) is for an on-premises Azure DevOps Server instance, not Azure DevOps cloud.
• A generic OData Feed connection can access OData endpoints, but it is not the purpose-built connector for Azure DevOps Analytics views.
• “OData queries” describes the underlying technology or query approach, not the most appropriate Azure DevOps connector choice here.

• A — Use getRecordTypeInfosByDeveloperName()

apex 
  Id rtId = Schema.SObjectType.Account 
      .getRecordTypeInfosByDeveloperName() 
      .get('Business_Account') 
      .getRecordTypeId();

• C — Query the RecordType object

apex 
  RecordType rt = [ 
      SELECT Id 
      FROM RecordType 
      WHERE SObjectType = 'Account' 
      AND Name = 'Business Account' 
      LIMIT 1 
  ];

• B: An outbound SOAP call is unnecessary and inefficient.
• D: Hardcoding an ID is not dynamic, and IDs can differ between orgs.

• A. PsFile — Correct: Displays files opened remotely on a system. This reveals shared resources and user activity.
• B. UserInfo — Correct: Gathers information about user accounts, supporting account and privilege enumeration.
• C. PsPasswd — Answer key lists it: This is questionable. PsPasswd is primarily used to change passwords remotely, not enumerate information. The key may classify it broadly as a Windows account-management tool, but it is not a strong enumeration example.
• D. WinSSLMiM — Incorrect: Used for SSL man-in-the-middle activity, not enumeration.

Why this is correct

• Each user authenticates with their own Google account.
• Google manages the user’s SSH key association.
• IAM controls who can access instances.
• Access can be audited by user identity, so security can determine who accessed a VM.
• Granting the role to a Google group avoids managing permissions individually.

Why the others don’t apply

• A: A shared private key is difficult to distribute securely and cannot reliably identify which employee used it.
• B: Manually collecting and deploying keys on every instance is operationally inefficient and complicates auditing.
• D: A project-wide shared key has the same identity and key-management problems as option A. It also does not provide per-user accountability.

• Assign endpoints to a group based on the result of one policy.
• Use that group as the scope of another policy.
• This effectively passes the endpoints from one policy’s processing flow to another.

• Ramen is a Linux worm associated with Red Hat Linux 6.2 and 7.0 systems.
• It spreads by scanning randomly generated IP addresses using tools such as synscan.
• It exploits vulnerable network services, including web-related services, and may leave malicious files or altered web content.
• The tar.gz file is also a clue because it is a common Linux archive/package format.

• Code Red: Primarily targeted Microsoft IIS servers running Windows.
• LoveLetter: Spread mainly through email attachments.
• Nimda: A Windows-based worm that spread through email, web servers, and network shares.

• Preparing and managing datasets
• Building and training machine-learning models
• Testing and evaluating models
• Deploying models as endpoints for predictions

• Treatment one – easier to prepare: Convenience for the accounting team is not the main objective of financial reporting.
• Treatment two – fair representation: This is the correct choice because financial statements must faithfully represent the underlying transaction and its economic substance.
• Treatment three – maximises profit: Accounting policies must not be selected simply to manipulate or inflate reported profit.
• Treatment four – easier to understand: Understandability is important, but it cannot justify presenting information that is less faithfully represented.

• GPS coordinates
• Date and time the image was taken
• Camera or device information
• Image dimensions and software used

• Log data: Records generated by systems or applications, not normally embedded in image files.
• Encrypted data: Information intentionally encoded to prevent unauthorized access.
• Sensitive data: A broad classification, not the specific type of information being extracted.

• 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.

• Document feeder: A scratch, dirt, or debris on the feeder glass or rollers can create a line on every scanned image.
• Pickup rollers: Move paper through the printer; they would not normally create a scanner-only line.
• Corona wire: Affects toner charging and would cause defects on printed output.
• Drum assembly: Also affects printed pages, so faxes and computer print jobs would show the line too.

text 
ip route vrf Customer1 172.16.1.0 255.255.255.0 172.16.1.1 global 
ip route vrf Customer2 192.168.1.200 255.255.255.255 192.168.1.1 global 
ip route 192.168.1.0 255.255.255.0 Vlan10 
ip route 172.16.1.0 255.255.255.0 Vlan20

• The route in Customer1 VRF provides a path back to the Customer2 subnet, 172.16.1.0/24.
• The route in Customer2 VRF provides a path to the FTP server, 192.168.1.200.
• The keyword global tells the router to resolve the next hop using the global routing table, enabling controlled route leaking between the VRF and global table.
• The global routes identify the VLAN interfaces used to reach each customer network.

1. Wireless AP

1. Router

1. Firewall

1. Device placement

• True positive: The scan reports a vulnerability that really exists.
• False positive: The scan reports a vulnerability that does not exist.
• True negative: The scan correctly reports no vulnerability.
• False negative: The scan fails to detect a vulnerability that is actually present.

• Amazon S3 as the origin for static content
• Application Load Balancer (ALB) as the origin for dynamic content
• Amazon Route 53 configured to point the company’s domain name to CloudFront

• /static/* ? S3 origin; cache content at edge locations
• Dynamic paths such as /api/* ? ALB origin; forward requests to the EC2 application

• 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.

• Accept terms of use
• Enter a temporary code or credentials
• Provide basic registration information

• Enterprise authentication — Authenticates organizational users, often with centralized identity services; it is not specifically designed for temporary guest access.
• Ad hoc network — A temporary device-to-device network, not an authentication process.
• WPA3 — A wireless security standard. It protects Wi-Fi access but does not provide the web-based temporary access workflow described here.

• Record changes — a flow can start when a record is updated or otherwise changes.
• Schedules — a flow can run at a specified date/time or on a schedule.
• Record inserts — a flow can start when a new record is created.

• Subflows are reusable flow components called by another flow; they are not normally trigger types.
• Record views do not generally initiate a Flow Designer flow.

• Each Case must follow defined support steps.
• Each step must be completed within a specified time limit.

• Case Escalation Rules: Escalate Cases based mainly on age or criteria; they do not model a complete sequence of service steps.
• Process Builder with Scheduled Actions: Can automate time-based actions but is not the standard framework for Case service-level commitments.
• Omni-Channel Routing: Routes work to agents based on capacity and priority; it does not track Case lifecycle deadlines.