Confluent CCDAK Exam Prep
Confluent Certified Developer for Apache Kafka Certification Examination (Page 7 )

• The application stores data on Amazon EBS volumes, so the encryption should be applied directly to those volumes.
• EBS encryption uses AWS-managed cryptographic operations and is designed to provide encryption at rest with minimal performance impact.
• The volumes are created during initial deployment, so they can be configured as encrypted when provisioned.

• B: Moving data to an encrypted S3 bucket changes the storage design and does not encrypt the EBS data the application uses.
• C: A custom encryption algorithm adds application overhead and is unnecessary.
• D: Ephemeral disks are temporary storage and can lose data when instances stop or terminate. Encrypting only the AMI’s root volume does not protect data stored elsewhere.

• A. IDS attack signatures: Detects suspicious network activity, but is not primarily designed to scan uploaded files for malware.
• C. Load balancer: Distributes traffic among servers and improves availability; it does not inspect files for threats.
• D. WAF: Protects web applications from attacks such as SQL injection and command injection, but its primary role is not malware scanning of uploaded documents.

• The ERSPAN source is the device or interface whose traffic is being copied.
• The ERSPAN destination is the device receiving the encapsulated copy and forwarding it to the traffic analyzer.
• The local monitor session number is locally significant. Therefore, the source and destination do not need matching session IDs such as 47 or 48.
• The erspan-id identifies the ERSPAN stream and must correspond between the source and destination configuration.

• End-user training: Important for recognizing phishing, but it depends on users consistently making the right decision.
• Installing antivirus rule updates: Helps detect malware, but may not stop phishing links or newly emerging threats.
• Disabling HTML in email content: Can reduce some email-based risks, but it is less practical and comprehensive than filtering web destinations.

• Incident and problem management
• Change management
• Service-level management
• Configuration management
• Continual improvement

• Kanban: A workflow and task-visualization method; useful within service teams but not a complete service-management framework.
• Lean Six Sigma: Focuses on reducing waste and process variation; broader process-improvement methodology.
• ITSM: The overall discipline of managing IT services, not a specific framework or process model.

• Microsoft manages the physical datacenter, hardware, and virtualization.
• You manage the virtual machine’s operating system, installed software, configuration, and data.
• You choose the VM size, storage, networking, and scaling options.

• SaaS: You consume a complete application managed by the provider, such as Microsoft 365.
• PaaS: You deploy applications without managing the underlying operating system or VM infrastructure, such as Azure App Service.

• IaaS: você gerencia a VM e o sistema operacional.
• PaaS: o Azure gerencia a infraestrutura; você se concentra no aplicativo.

• AB’s own PPE: $100m
• CD’s PPE in its individual accounts: $50m
• Fair value uplift at acquisition: $40m
• Remaining useful life: 10 years
• Extra depreciation each year: $40m ÷ 10 = $4m
• Four years’ extra depreciation to 31 December 20X4: 4 × $4m = $16m
• Remaining fair value uplift: $40m - $16m = $24m

• 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.

• Guest access: Controls external users invited into your teams as guests. It is not the primary setting for restricting federated communication by domain.
• Messaging policy: Controls messaging features, such as chat or message editing, rather than which organizations users can communicate with.
• Org-wide Teams settings: Contains broad Teams-wide configuration, but domain-based external communication is configured under External access.

• 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.

• 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.

• 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.

• PC A: 192.168.1.10/24
• PC B: 192.168.2.10/24

• Both PCs have a correct default gateway
• A router or Layer 3 switch connects the subnets
• Routing and firewall rules allow the traffic

• Identifies which user or department owns the device
• Supports inventory and compliance requirements
• Enables tracking of lost, stolen, retired, or unauthorized devices
• Helps enforce security controls such as mobile-device management and secure configuration

• 50% memory utilization baseline: The environment can be provisioned with excess capacity, leaving room for growth and workload spikes.
• Storage scalability: Cloud storage can generally be expanded as needed without redesigning the physical platform.
• Single circuit failure resilience: A properly designed IaaS provider uses redundant power circuits and infrastructure, so failure of one circuit should not take the platform offline.

• A — Dual PDUs: Helps with power redundancy but does not provide storage scalability.
• C — Network load balancing: Provides network-path resilience, not memory or storage scalability, and does not address a power-circuit failure.
• D — Multiple NAS devices: May improve storage capacity, but does not inherently provide power resilience or the required compute-capacity baseline.

• 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.

• Report on the discount approval time for quotes

• Dashboard of opportunity stage duration

• Lead conversion trends measure lead-generation effectiveness, not opportunity closing time.
• Campaign ROI evaluates marketing performance, not delays in the sales process.

• C. Case after-insert trigger that publishes a Platform Event

• D. Custom Apex controller that publishes a Platform Event

• A. Trigger with a callout: Salesforce triggers should not make direct synchronous callouts, and this tightly couples transaction processing to the external system.
• B. Workflow Rule with Outbound Message: This can react to record changes, but it cannot reliably capture a user clicking a menu item. It also does not provide the same flexible event-driven model as Platform Events.

• Floating IP must be enabled on the load-balancing rule.
• Session persistence should normally remain None.
• The health probe determines which replica should receive traffic.
• Client-IP persistence is unnecessary and can cause connections from the same client to remain associated with a backend replica longer than intended.

• Q9 — Client IP session persistence: No
• Q10 — Floating IP: Yes

• Admin access to the deployment pipeline
• Contributor access to the Development and Test workspaces
• Viewer access to the Production workspace

• 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 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.

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

• C. The agent orchestration method
• D. The average session time per agent

• Orchestration method: Classic and generative orchestration can have different processing and credit-consumption patterns. Changing the method can affect estimated operating costs.
• Average session time: Longer sessions generally involve more interaction processing, which affects projected usage, credits, and ultimately ROI.

• GPT models used: Important for technical design, but not the primary usage-estimator factor identified in this scenario.
• Average characters in a chat message: Message length alone is not the key business-use projection requested here.

• 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.

• SOSL searches text across objects and is not appropriate for selecting Account table columns.
• describeSObjects() provides metadata about objects and fields, but it does not itself build or execute the query.
• Dynamic Schema binding supports runtime determination of object and field information, which is required here.
• REST API is unnecessary because this is being implemented in Apex.

• Shared capacity

• Fabric capacity — F SKUs

• Fabric trial capacity

• Existing Power BI Premium — P SKUs

• 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.

• 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.

• 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.

• Maintain head office control: Transfer pricing generally supports decentralisation rather than direct head-office control.
• Establish centralised decision making: This conflicts with divisional autonomy.
• Develop a top-down culture: Transfer pricing is intended to support empowered divisions and goal congruence, not impose purely top-down management.

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.

• 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.

• 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.

• Lower order numbers appear first.
• For example, a variable with order 100 appears before one with order 200.
• The Sequence field is not the control used for catalog variable display order.
• The Default Value sets a value, not placement.
• The Choice field defines selectable options, not the variable’s position.

• One physical NIC is active and carries traffic.
• Another NIC remains on standby.
• If the active uplink fails, traffic switches to the backup uplink.
• This provides redundancy without requiring special switch-side link aggregation configuration.

• Balance-SLB: Distributes traffic based on source load balancing; not the default.
• Balance-TCP: Uses dynamic TCP traffic balancing and generally requires appropriate network-switch configuration.
• No Uplink Bond: Incorrect because vs0 is normally configured with redundant uplinks.

• Red team: Simulates attackers and tests exploitability.
• Blue team: Defends, monitors, detects, and responds to attacks.
• Purple team: Combines red- and blue-team activities to improve cooperation and defenses.
• White team: Manages and oversees the rules, scope, and authorization of the exercise.

• 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.

• 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 
    } 
}

• Extracted text and images
• Page numbers and bounding polygons for citation or grounding
• Structured tables, including tables that continue across multiple pages
• Document structure such as sections and figures

• Document Extraction: Extracts basic text and images, but does not provide the full layout and structural metadata required here.
• Azure Content Understanding in Foundry Tools: A broader content-analysis service, not the single built-in Azure AI Search skill expected by this question.
• GenAI Prompt: Can transform or interpret content but does not inherently produce reliable document geometry and page-level polygons.

• JobTitle: User1 and User3 only
• UsageLocation: User1, User2, and User3

• For a user whose source of authority is Windows Server Active Directory, attributes such as JobTitle are synchronized to Microsoft Entra ID. You must change them in on-premises AD; editing them in Entra ID is not allowed or will be overwritten.
• UsageLocation is a cloud-managed attribute used mainly for licensing and service availability. It can be set or changed in Microsoft Entra ID, including for synchronized users.

• Security
• Availability
• Processing integrity
• Confidentiality
• Privacy

• Whether controls are suitably designed, and
• Whether they operated effectively over a period of time

• Tracking who accessed or changed customer information
• Detecting unauthorized activity
• Supporting accountability and investigations
• Providing evidence for compliance and incident response

• Single sign-on not enabled: SSO improves convenience and centralized authentication, but it is not essential for access control.
• Complex passwords not required: This weakens authentication, but other controls may reduce the risk.
• Security baseline not consistently applied: A concern, but it is less specific and less immediately damaging than having no activity records at all.

• 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.

• Accept: Acknowledge the risk and take no additional action.
• Mitigate: Reduce the likelihood or impact of the risk through controls.
• Avoid: Eliminate the activity or situation causing the risk.
• Transfer: Shift responsibility or financial impact to another party, such as through insurance or a contract.

• Liability accounts (2000–2999) would incorrectly require dimensions, although they should have none.
• Expense accounts (6000–6998) would incorrectly require Customer, which should be optional.
• Account 6999 needs a separate rule because it requires all four dimensions, including Customer.

• 2000–2999: no dimensions
• 4000–4999: Department and Division required; Project and Customer optional
• 6000–6998: Department, Division, and Project required; Customer optional
• 6999: Department, Division, Project, and Customer required

• Azure Machine Learning Studio is designed to build, test, train, and deploy machine-learning models, including predictive analytics.
• Azure Cosmos DB is a globally distributed NoSQL database. It can store data used by an AI solution, but it is not the primary service for developing and deploying predictive models.
• Therefore, the appropriate recommendation is Azure Machine Learning Studio, as shown in Question 15.

• A: Not expanding would increase its dependence.
• B: More business from the same corporation would make dependence worse.
• D: Passing work to other minority businesses does not solve its own dependence.
• E: The passage does not suggest that it can force or influence the corporation to give work to others.

• O File Gateway fornece uma interface de compartilhamento de arquivos usando protocolos como SMB ou NFS.
• Os usuários continuam acessando os arquivos localmente, aproveitando a baixa latência e o cache local.
• Os dados são armazenados de forma durável no Amazon S3, enquanto os arquivos acessados com frequência permanecem em cache no ambiente local.
• Isso amplia a capacidade de armazenamento sem exigir a substituição completa da infraestrutura existente.

• A: Montar buckets S3 diretamente não oferece uma experiência de compartilhamento de arquivos local tão adequada.
• C: Amazon WorkSpaces fornece desktops virtuais, não é uma solução principal de armazenamento compartilhado.
• D: Um volume EBS pertence a uma instância EC2 e não deve ser compartilhado diretamente entre vários usuários como um sistema de arquivos comum.