Network Appliance NS0-184 Exam Prep
NetApp Certified Storage Installation Engineer, ONTAP (Page 2 )

• 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.

• 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 Azure DevOps (Boards only) connector is designed specifically for Azure DevOps Analytics views.
• It authenticates directly to Azure DevOps and lets you select an existing Analytics view.
• Filters defined in the Analytics view are applied by Azure DevOps before Power BI retrieves the data, reducing the amount of data transferred.

• Azure DevOps Server (Boards only) is for on-premises Azure DevOps Server.
• OData Feed can consume OData endpoints, but it is not the dedicated Azure DevOps Analytics-view connector.
• OData queries are not the intended dedicated connector for this requirement.

• Suspended an operator who correctly refused to use unsafe equipment.
• Rewarded another operator for using the equipment despite the broken safety guard.

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

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

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

• 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: \(\$10\)

• Build, measure, learn: Create something, assess real feedback or results, and adapt.
• Minimum viable product (MVP): Produce the smallest useful version to test assumptions and reduce uncertainty.
• Fail fast: Test ideas early so that unsuccessful approaches can be identified before significant time or cost is invested.

• 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.

• 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.

• IDS attack signatures: Primarily detects suspicious network activity; it is not the best control for scanning uploaded documents.
• Load balancer: Distributes traffic and can improve availability, but does not inspect files for malware.
• WAF: Helps block web attacks such as command injection and SQL injection, but it is not primarily a malware-scanning solution.

• A — Capacity: The system must handle all current records and anticipated future records. A system that cannot cope with volume will quickly become ineffective.
• C — Accuracy: Academic records are critical, so the new system must be at least as accurate as the existing system and comparable systems. Poor accuracy could cause serious administrative and reputational problems.
• D — Integration: Linking with the university’s financial systems supports consistency and avoids duplicate data entry, especially for registration, deregistration and fee-related transactions.

• B — Parallel running: This is a useful implementation and risk-control technique, but it is not an essential feature of the system itself. It may also be expensive and time-consuming.
• E — Internet access for all information: This creates significant confidentiality and security risks. External access might be needed for selected services, but unrestricted access to all information is not essential and would be inappropriate for student records.

• 24 cores: Available in the Business Critical provisioned-compute configurations.
• Approximately 124 GB memory: Matches the memory capacity of the relevant Business Critical hardware configuration.
• More than 50,000 IOPS: Business Critical uses local SSD storage and provides the high I/O performance required here.
• 500 GB storage: Well within the tier’s supported capacity.

• Premium: The DTU-based Premium tier does not provide the required combination of compute, memory, and I/O characteristics.
• Hyperscale: Hyperscale is primarily intended for very large databases and independent storage scaling. It is not the best match for these specific high-memory and high-IOPS requirements.

DAX 
Previous Year Sales = 
CALCULATE( 
    [Total Sales], 
    PARALLELPERIOD('DATE'[Month], -1, YEAR) 
)

• CALCULATE evaluates [Total Sales] after modifying the filter context.
• PARALLELPERIOD shifts the current date period. -1 moves it backward, and YEAR specifies a one-year shift.
• 'DATE'[Month] is the date column used for the time calculation. In a proper date table, this should be a real date column or an appropriate calendar column—not merely text such as "January".

• TLS passthrough: A TCP listener does not decrypt traffic. The client establishes TLS directly with the backend, so the backend can perform mutual TLS (mTLS) authentication.
• gRPC over TCP: gRPC commonly uses HTTP/2 over TLS, and an NLB can forward the underlying TCP connections without modifying them.
• Scalability: Registering the Pods as IP targets allows Kubernetes to add or remove Pods as the Horizontal Pod Autoscaler changes the workload. The AWS Load Balancer Controller updates the target registrations.
• Port 443: The NLB can forward TCP traffic on port 443 without terminating TLS.

• An ALB HTTPS listener terminates TLS at the load balancer, violating the requirement that traffic must not be decrypted before reaching the backend.
• Targeting the EKS node group's Auto Scaling group does not directly track dynamically scaling Pods.
• An NLB TLS listener also terminates TLS at the NLB, preventing end-to-end mTLS between the client and backend.

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.

• 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.

• desktopwidth:i:1280
• desktopheight:i:1024

• Connection information: Controls connection-related settings, not the desktop resolution.
• Scaling plan: Controls when session hosts start, stop, or scale based on demand.
• Session behaviour: Controls behavior such as disconnect or logoff handling.
• Display settings: Specifically controls RDP display properties, making it the appropriate choice.

• Virtual introductions: Team members share their role, experience, location, and working preferences.
• Online icebreakers: Short, informal activities such as “two truths and a lie.”
• Virtual coffee chats: Pair team members for informal, non-project conversations.
• Collaborative problem-solving: The team works together on an online puzzle or scenario.
• Retrospectives: The team discusses what went well, what did not, and how to improve.
• Working-agreement sessions: The team agrees on response times, meeting etiquette, communication channels, and handoffs.
• Recognition sessions: Members acknowledge one another’s contributions.
• Remote workshops: Teams jointly create plans, diagrams, or schedules using collaboration tools.

• Annual interest payments net of tax relief (A): future cash outflows for the issuer.
• Redemption value (B): the final cash outflow when the bond is redeemed.
• Market value now (C): the cash proceeds received now, acting as the initial cash flow in the IRR calculation.

• Measurement bias: Errors in how features or labels are measured, such as unreliable camera data or inconsistent labeling.
• Observer bias: A human evaluator’s subjective judgment influencing observations or labels.
• Confirmation bias: Favoring information that supports an existing belief.

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.

• CPU: Number of virtual CPUs and, where applicable, CPU reservations.
• Memory: Amount of memory and memory reservations.

• Network interface: Usually configured through the VM or workload networking configuration.
• PCI devices: Specialized hardware and not a standard VM Class resource in this context.
• Storage: Typically selected through storage policies or the VM’s storage configuration.

• Economy: Obtaining inputs at the lowest appropriate cost.
• Efficiency: Making the best use of resources, such as staff, money, and equipment.
• Effectiveness: Achieving the intended objectives or outcomes.

apex 
Set<Id> accountIds = new Set<Id>{ accountId1, accountId2 }; 


List<Account> accounts = [ 
    SELECT Id, Name 
    FROM Account 
    WHERE Id IN :accountIds 
];

• A: LIMIT accepts a number, not a collection of IDs.
• B: Set.containsAll() checks set contents in Apex; it does not filter SOQL results.
• C: Database.query() accepts a dynamic SOQL string, not a Set<Id> directly.

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.

• SAML (Security Assertion Markup Language): Commonly used for enterprise SSO between an identity provider and cloud applications. It sends signed authentication assertions to the service provider.
• RADIUS: Primarily used for centralized authentication to network devices, VPNs, and wireless networks.
• EAP: An authentication framework commonly used with network access technologies; it is not typically the SSO protocol for SaaS applications.
• OpenID: Related to identity authentication, but traditional enterprise SSO questions involving cloud applications generally expect SAML. OpenID Connect is a newer authentication layer built on OAuth 2.0.

• Penetration test: Tests for exploitable vulnerabilities; it does not provide a broad opinion on whether security controls operate effectively.
• Annual self-assessment: Not independent, so it provides less assurance.
• Allow each client the right to audit: Inefficient because every customer may conduct a separate audit, creating duplicated effort and disruption.

• Smartphones and tablets
• Laptops and workstations
• Other mobile or endpoint computing devices

• API tool matcher: runs a deterministic normalization command after the API tool returns.
• Write/Edit matcher: checks whether the target path begins with src/api/ and runs the linter.

json 
{ 
  "hooks": { 
    "PostToolUse": [ 
      { 
        "matcher": "api_tool", 
        "hooks": [ 
          { "type": "command", "command": "normalize-to-snake-case" } 
        ] 
      }, 
      { 
        "matcher": "Write|Edit", 
        "hooks": [ 
          { "type": "command", "command": "lint-if-under-src-api" } 
        ] 
      } 
    ] 
  } 
}

• 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.

• 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.

• Actions that call external APIs
• Subflows
• Connection and credential aliases
• Supporting integration logic

• Action — A reusable operation within a flow, such as “Create a record” or “Send email.”
• Connection — Defines how ServiceNow authenticates and communicates with an external system.
• Integration step — A general flow step, not the name for the packaged integration.

• 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.

• Customize Opportunity Contact Role
• Add the Opportunity Contact Role related list to the Opportunity page layout

• 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.

• Share of overall contribution: part of the organization’s total contribution is allocated to the supplying division.
• Dual pricing: the supplying division may record a higher transfer price while the receiving division records a lower price, with central accounts absorbing the difference.
• A centrally imposed price range: this may allow the transfer price to be set above variable cost, helping the supplying division recover fixed costs.

• A is valid:

apex 
  for (Account theAccount : AccountList) { 
      // process theAccount 
  }

• D is conceptually valid, using an index:

apex 
  for (Integer i = 0; i < AccountList.size(); i++) { 
      Account theAccount = AccountList[i]; 
  }

• B is invalid because for(AccountList) is not valid loop syntax.
• C is invalid because each item is an Account, not a List.

• 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.

• Standardize which services users can deploy
• Apply governance and access controls
• Manage approved product versions
• Give users self-service access to authorized resources

• AWS Control Tower: Sets up and governs a multi-account AWS environment.
• AWS Cloud Map: Provides service discovery for applications.
• AWS Clean Rooms: Enables privacy-preserving collaboration on data analysis.

• Streams — track change data for tables or views.
• External tables — reference data stored in an external cloud storage location.

• Role — account-level security object.
• Warehouse — account-level compute resource.
• User — account-level security object.
• Share — account-level object used to share data.

• 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.

Correct sequence

1. Merge Sales_Region with Sales_Manager using an inner join

1. Merge Region_Manager with Manager using an inner join

1. Merge Sales_Region and Region_Manager using a right join as a new query

• Disable default accounts: Default or unused accounts may have known usernames or predictable settings, making them targets. They should be disabled, removed, or securely configured.
• Remove unnecessary services: Every running service creates potential vulnerabilities. Removing services the server does not need reduces exploitable entry points.

• Add the server to the asset inventory: Important for asset management, but not a hardening step.
• Document default passwords: Default passwords should be changed or eliminated—not documented for continued use.
• Send server logs to the SIEM: Valuable for monitoring and detection, but generally performed as part of logging/monitoring configuration.
• Join the server to the corporate domain: May be necessary operationally, but does not itself harden the server.

1. Write a structured log entry to CloudWatch Logs containing:

1. Create a CloudWatch Logs metric filter that:

text 
ApiRequests 
Operation=GetOrders 
ResponseCode=500 
Version=2.4.0

• B is incorrect: CloudWatch Logs Insights queries analyze logs but do not directly publish metrics in this manner.
• C is incorrect: ALB access logs do not contain arbitrary Lambda response metadata as custom fields.
• D is incorrect: X-Ray traces and insights are not the appropriate mechanism for creating these custom, dimensioned application metrics.

• 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.

• Normal or expected input
• Boundary values
• Invalid input
• Potential error conditions

• A is incorrect: it creates test code, not detailed test documentation.
• C is incorrect: it does not primarily integrate external testing frameworks.
• D is incorrect: executing tests requires your development environment or test runner.

• Atomicity: a write fully succeeds or does not appear.
• Consistency: table state remains valid.
• Isolation: concurrent operations do not corrupt one another.
• Durability: committed changes persist.

• Flexible schemas: common data lakes often support flexible or schema-on-read data.
• Open-source formats: common data lakes commonly use open formats such as Parquet.
• Scalable storage: cloud data lakes already provide scalable storage.

• Red team: Offensive security; simulates attackers and validates exploitability.
• Blue team: Defensive security; monitors, detects, and responds to attacks.
• Purple team: Helps red and blue teams collaborate and improve defenses; not usually the primary testing role.
• White team: Oversees and coordinates the rules, scope, and authorization of an exercise.

• STIX: A standardized format for exchanging cyber-threat intelligence.
• OVAL: A language and framework for describing and assessing system vulnerabilities and configuration issues.
• Threat intelligence feed: Provides current indicators or threat information, but is not specifically a reference for common application exploitation techniques.
• CVE: A catalog of publicly disclosed vulnerabilities, identified by unique CVE numbers.