BICSI RCDDv14.1 Exam Actual Questions
BICSI Registered Communications Distribution Designer Exam (Page 22 )

• Business
• People
• Governance
• Platform
• Security
• Operations

• Cloud financial management
• Portfolio and program management
• Risk management
• Data governance
• Compliance and oversight

• The connecting host keeps the private key securely.
• The destination host stores the corresponding public key in its authorized keys.
• Authentication can occur without a person entering credentials each time.
• SSH also provides encrypted communication and host authentication.

• Biometric: Requires a human user and is difficult to automate.
• Smart card: Often requires user interaction or card access.
• Hard-coded password: Unsafe because passwords stored in scripts or applications can be exposed, reused, or difficult to manage securely.

• The two correct options are:

• The two incorrect options:

• The 99.99% availability SLA for VMs is achieved when you run VMs across two or more Availability Zones.
• Two VMs in a single Availability Zone do not meet the 99.99% target (their SLA is lower, e.g., around 99.95% or less depending on configuration).

• Deploy at least two VMs across two different Availability Zones (one VM in each zone, or both in two zones with a load balancer).
• This provides the required zone redundancy and the 99.99% SLA.

• Answer: No (B)

• SaaS (Software as a Service) delivers applications over the internet; you don’t manage the underlying infrastructure or OS.
• Deploying Azure virtual machines requires provisioning and managing virtual machines, OS, updates, and networking—this is classic IaaS (Infrastructure as a Service).
• PaaS is for managed runtime environments (apps hosted on a platform), not for VM deployment.

• A. Number ? Decimal — Correct. Salesforce Number fields are represented in Apex as Decimal.
• D. Date/Time ? Datetime — This is correct conceptually, but “Dateline” is not an Apex type. If the option literally says “Dateline,” it is incorrect.
• E. Checkbox ? Boolean — Correct. A checkbox contains true or false.

• Number ? Integer — A Number field maps to Decimal, even when its scale is zero.
• Text Area ? List<String> — A text area maps to a single String, not a list.

• The standard Enterprise Architecture domains are: Business, Data, Application, Technology (BDAT).

• A: Business, strategy, application and technology — includes business and application/tech but uses “strategy” instead of data.
• B: Zachman, TOGAF, Cobit, and Heath architectures — names frameworks, not domains.
• C: Business, data, infrastructure and technology — has business, data, and technology; lacks a distinct application domain (uses “infrastructure” instead).
• D: Process, database, software and technology — covers data (database), application (software), and technology, but omits business.

• The four BDAT domains (business, data, application, technology) is the conventional model you should study.
• None of the options perfectly lists all four BDAT domains. The closest are C (if you map infrastructure to technology) and D (data/application/technology but no business).

• D. Provide public endpoints to store and retrieve data

• E. Manage the infrastructure layer and the operating system

• Classifying data
• Configuring access permissions, such as IAM policies
• Selecting or configuring available encryption options, depending on the requirement

• 25 — Traditional SMTP server-to-server mail transfer; not normally used for secure client submission.
• 110 — POP3, used to retrieve email and typically unencrypted.
• 143 — IMAP, used to access email and typically unencrypted.

• 6-phone boxes: 6x
• 8-phone boxes: 8x

• The inference container image or built-in algorithm
• The location of model artifacts in Amazon S3
• IAM permissions through the execution role
• Optional environment variables and networking settings

1. Create AWS::SageMaker::Model
2. Create an AWS::SageMaker::EndpointConfig that references the model
3. Create AWS::SageMaker::Endpoint that references the endpoint configuration

• AWS::SageMaker::Endpoint hosts a model but does not define the model itself.
• AWS::SageMaker::NotebookInstance provides a development environment.
• AWS::SageMaker::Pipeline orchestrates ML workflow steps.

• Le rôle n’a pas de clés propres. Des identifiants temporaires (via STS) sont émis lorsque quelqu’un ou quelque chose « assume » le rôle.
• La trust policy déclare qui peut assumer le rôle (par ex. une instance EC2, un utilisateur IAM, ou un service comme Lambda).
• Une fois attaché à une ressource (par exemple comme un instance profile sur une EC2), l’application peut appeler les services AWS avec les permissions du rôle.

• Respect du principe du moindre privilège: on accorde uniquement ce qui est nécessaire.
• Pas de stockages de clés sur les instances; les credentials se renouvellent automatiquement.

• Rôles pour EC2, rôles pour Lambda, accès cross-compte, etc.

• Why: A multi-modal embedding model maps both text and images into a shared vector space, enabling cross-modal similarity and retrieval (e.g., find images matching a text query or text matching an image).

• What it does: Enables efficient similarity search using a vector database or nearest-neighbor indexing.

• Why the other options aren’t suitable:

• Quick implementation note: you’d typically pair the embeddings with a vector store (e.g., ANN index) and possibly fine-tune on domain data for better alignment across modalities.

• Network Security Groups (NSGs) control network traffic to and from Azure resources.
• By applying NSGs to the web tier and the database tier (subnets or NICs), you can:

• NSGs provide the necessary granularity (source/destination, port, protocol) to enforce the desired traffic patterns between tiers.
• For easier management you can use separate subnets for each tier or, optionally, use Application Security Groups to simplify rule management.

• Correct answer: B — From the code repository, modify Startup.cs (in ASP.NET Core you configure the Application Insights SDK in code, not with ApplicationInsights.config).

• Why the other options aren’t correct:

• How to implement fixed-rate sampling (ASP.NET Core):

var builder = WebApplication.CreateBuilder(args); 


    builder.Services.Configure<TelemetryConfiguration>(telemetryConfiguration => 
    { 
        var builder = telemetryConfiguration.DefaultTelemetrySink.TelemetryProcessorChainBuilder; 
        double fixedSamplingPercentage = 10; // 10% sampling 
        builder.UseSampling(fixedSamplingPercentage); 
    }); 


    builder.Services.AddApplicationInsightsTelemetry(new ApplicationInsightsServiceOptions 
    { 
        EnableAdaptiveSampling = false 
    }); 


    var app = builder.Build();

• wyjasnic istniejace pytania z tej strony,
• wskazac, dlaczego dana odpowiedz jest poprawna lub bledna (z uwzglednieniem celów egzaminu),
• omówic koncepcje zwiazane z Google Cloud AI.

• Business
• People
• Governance
• Platform
• Security
• Operations

• Program and project management
• Risk management
• Cloud financial management
• Data governance
• Portfolio management

• Sustainability
• Performance efficiency
• Reliability

• Forecasting lets sales leaders predict revenue for upcoming fiscal periods, compare forecasts with targets, and review performance by salesperson or team.
• Opportunity Stages help determine the likelihood that opportunities will close. Each stage can have a probability, which contributes to forecast calculations.

• Sales Quotes: Used to present pricing or product proposals to customers; they do not provide revenue forecasting.
• Opportunity List View: Helps users filter and view opportunities, but it is not the forecasting tool.

• App Tag: a label that reflects the app’s enterprise readiness based on its Cloud Confidence Index (CCI) rating. It lets you quickly group apps (e.g., Poor, Average, Good) for policy decisions.
• App Score: a numeric value representing the CCI score. It provides a precise threshold you can use to enforce policies (e.g., block apps with Score below 50).

• You can create policies that block or restrict apps with a Poor App Tag or with an App Score under a chosen threshold.
• These two aspects let you filter cloud apps by CCI ratings during policy evaluation.

• CCL isn’t described as a real-time policy facet in this scenario.
• GDPR Readiness is a separate consideration and not the two CCI aspects used for real-time protection policy in this context.

• Strongest encryption algorithms: Choose the strongest available encryption and integrity options, typically AES with the largest key size and a secure integrity algorithm.
• Encrypt all traffic: Select tunnel mode rather than transport mode. Tunnel mode encrypts the entire original IP packet, which is appropriate for a site-to-site VPN between branch networks.
• Secret-password authentication: Configure a pre-shared key (PSK) on both VPN concentrators. The key must match at both ends.

• Ensure that only users who manage the production environment sign in to the Azure portal from a hybrid Entra-joined device and authenticate with MFA.

• Use Microsoft Entra ID Protection (Identity Protection) to enforce MFA enrollment:

• Update the existing Capolicy1 (a Conditional Access policy):

• Identity Protection MFA registration policy ensures users are enrolled in MFA (Box 1 choice).
• CA policy Capolicy1 with aGrant control of “Require MFA” enforces MFA during sign-in (Box 2 choice).
• Both work together with the hybrid-joined device requirement to satisfy the authentication/authorization rules.

• Apply the MFA registration policy to the production-management users.
• Apply the MFA grant to Capolicy1 for those same users/groups.

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• A ??????? system software ????????????????????????????????? ??????????????????????????????????
• B ?????????????????????????? ????????????????????????? ?????????????????????????????
• D ????????????????????????? ?????????????? ?????????????????????????????????????????

• Transact-SQL (T-SQL) is used to query relational data in Azure SQL Database, not telemetry data from monitoring services.
• To analyze monitoring data from Azure SQL Database Intelligent Insights and Azure Application Insights, you should use the Kusto Query Language (KQL) in Azure Monitor Logs/Log Analytics (and in Application Insights Analytics).
• Using KQL lets you query telemetry tables such as requests, dependencies, pageViews, and customEvents (from App Insights) and any integrated monitoring data you’ve ingested into Log Analytics.

• Ensure Intelligent Insights and Application Insights data is available in a Log Analytics workspace or accessible via Application Insights Analytics.
• Go to Azure Monitor > Logs (or Application Insights > Analytics) and write KQL queries, e.g.:

• a) True — To add a field to the form layout, drag the field from the Fields tab to the desired destination on the form. This adds to the form view only, without changing the table definition.
• b) True — To create a new field on the form’s table, drag a data type from the Field Types tab to the form and configure it. This creates a new column on the table and adds the field to the form view.
• c) True — To remove a field from the form layout, hover to enable the action buttons and select Delete. This removes the field from the form view but does not remove it from the table definition.
• d) False — You cannot add a section by dragging from the Field Types tab. Sections are added via the Add Section option (toolbar or right-click menu), not from the Field Types tab.

• In Azure, the typical cost approach for pay-as-you-go VMs is an Operational Expenditure (OPEX) model. You’re billed for actual usage each month.
• The term “elastic expenditure model” isn’t a standard Azure cost category. Elasticity describes scaling capacity, not the billing category itself.
• So recommending the elastic expenditure model is not correct for this goal.

• The solution does not meet the goal. Answer: No (B).

• Pay-as-you-go aligns with OPEX because costs vary with usage.
• Elasticity is about scaling resources, which affects performance and capacity, not the fundamental cost model.

• runParallel is defined as async, so it returns a Promise.
• To use the result, you attach a then handler (or use await inside another async function).

• A: “Async runParallel() .then(data);” is invalid. “async” is a keyword for function declarations, not something you put in front of a call, and you’d need a function as the then-argument.
• B: “runParallel().done(function(data){return data;});” .done is not standard in native Promises (it exists in some libraries). Without a compatible library, this won’t work.
• C: “runParallel().then(data);” is invalid because then expects a function as its argument; data is not a function.
• D: “runParallel().then(function(data){ return data; });” is valid (or equivalently, runParallel().then(data => data);).

• The robust, standard option is D.
• B could work only with a library that provides .done; otherwise it’s not reliable.

• Multiple AWS accounts: Create a separate account for each department or workload. This provides clear isolation and makes it easier to track each department’s usage and costs for chargeback.
• Consolidated billing: AWS Organizations can combine billing for multiple accounts into one central payer account. The company can still view costs by account while managing payment centrally.

• Placement groups: Control how EC2 instances are physically placed for networking or performance; they do not provide departmental billing separation.
• Edge locations: Infrastructure used by services such as Amazon CloudFront; unrelated to chargeback.
• AWS Config: Records and evaluates resource configurations and compliance; it is not a billing-separation mechanism.

• Developed and maintained independently
• Deployed without changing the entire application
• Scaled separately based on demand
• More resilient when another service has problems

• A: Functional testing is useful, but it is not the main practice described.
• B: Automation helps deployment, but the scenario focuses on architectural decomposition.
• C: Multiple locations improve availability, not application modularity.

• An IDS monitors network traffic for signs of attacks and raises alerts. It can be deployed out-of-band (via a SPAN/mirror port or a tap) so it analyzes traffic without being inline, meaning it doesn’t measurably affect latency.
• An IPS (intrusion prevention system) is inline and can block threats, but that processing can introduce some latency and potential throughput impact.
• A firewall also inspects traffic and can add latency, though usually modest with proper hardware, but its primary purpose isn’t continuous passive analysis.
• A load balancer distributes traffic and isn’t used for intrusion analysis.

• Answer:

• Why:

• Why the other centers aren’t the right fit here:

• Answer: C – netstat -an

• netstat -an lists all active connections and listening ports with numeric addresses, without resolving names. This lets you spot DoS patterns such as a flood of connections to a specific port or many connections from a single or few IPs.
• The other options don’t help as directly:

• Windows: netstat -an and look for numerous ESTABLISHED connections to a service or many SYNs to a port.
• Filter by port, e.g., netstat -an | findstr :80, or on Linux: ss -tunap | grep ':80'.

• Netstat provides a snapshot. DoS detection often benefits from continuous monitoring, flow data, and IDS/IPS logs.

• What it says: you can add a cost when you adjust inventory, and that cost is posted automatically to a specific GL account.
• Reality: yes, you can adjust both quantity and value via an inventory adjustment journal. The cost on the journal line affects the inventory value.

• The general ledger postings are not arbitrary. the actual accounts used are determined by your item posting group and the system’s posting definitions. In practice, the adjustment debits/credits the appropriate inventory-related accounts (e.g., Inventory asset and a related offset such as an adjustment or COGS account) based on configuration.
• So, the cost change does not go to a single “manual” GL account you pick per line unless your posting setup maps to that account.

• The concept is true (you can adjust cost and have GL impact), but the claim that it posts to a single, specific GL account is oversimplified—the accounts come from your posting configuration.

• Correct answer: A. System characterization

• Why the other options are not correct:

• Server — provides services or resources
• Endpoint — a user device connected to the network
• Ethernet — a networking technology, not a filtering device
• Firewall — filters and controls traffic

• Answer: Data enhancement.

• Why: Augmenting gold-layer tables with an additional dataset is enriching or enhancing the existing data to support the ad-hoc analysis. The other options don’t capture the idea of adding external data to improve the dataset (ad-hoc improvements = tweaks, last-mile dashboarding = building dashboards, last-mile ETL = ETL steps at the end of the pipeline). In practice, this is often also called data enrichment.

• Recovery procedures actually work
• Recovery time and recovery point objectives can be met
• Staff understand their responsibilities
• Contact details, dependencies, and technical configurations are accurate
• Gaps or conflicts exist in the plan

• Not version-controlled: Creates a risk of using an outdated copy, but the plan might still be effective.
• Contact information needs updating: This is a specific weakness that can be corrected, often identified during testing.
• Not approved by senior management: Approval is important for authority and resource commitment, but an untested plan presents the most direct risk that recovery will fail when needed.

• IPsec: Protects traffic at the network layer, commonly for VPNs; it is not WPA2’s authentication protocol.
• SSL: Protects specific application sessions and has largely been replaced by TLS.
• SSH: Secures remote command-line administration.

• Amazon Kendra is a managed enterprise search service that can index content stored in S3 and support natural-language queries to find text inside documents (PDFs, Word files, etc.).

• Rekognition analyzes images/videos, not document text search.
• Polly is a text-to-speech service.
• Lex is a chatbot service.

• Create a Kendra index.
• Add a data source of type S3 and point it to your bucket (with an IAM role that allows access).
• Configure/document conversion if needed, then index the data.
• Use the Kendra API or console to run natural-language queries against your indexed documents.

• The answer: Question 51: C — Request trigger.

• To invoke a Logic App from an external service (here, the Azure Application Insights availability test) you need a trigger that starts on an incoming HTTP request. In Logic Apps, this is the trigger that exposes an HTTP endpoint — typically shown as "When a HTTP request is received" and referred to as the Request trigger.
• The other options aren’t appropriate:

• Create a Logic App with the Request trigger to generate a URL.
• Configure Application Insights to post the degraded-availability payload to that URL.
• Add actions (e.g., send email, follow-up) in the Logic App to notify the customer services team.

• IaaS: You deploy and manage virtual machines, operating systems, disks, and networking. Azure manages the physical datacenter and host infrastructure.
• PaaS: Azure manages the operating system and runtime so you can focus on deploying applications, such as with Azure App Service or Azure Functions.
• SaaS: You consume a complete, provider-managed application.

• The correct setting to configure is the Enrollment Status Page (ESP) profile.
• Why: ESP tracks the enrollment progress and logs during Autopilot provisioning. You can enable log collection within the ESP policy so that, if ESP times out, the user can collect and share the logs with support.
• Optional enhancement: In the ESP policy (or the Autopilot diagnostics settings), you can enable:

• Automatic enrollment settings: control how devices auto-enroll, not log collection.
• Windows Autopilot deployment profile: controls deployment steps but not ESP log collection.
• Device configuration profile: applies settings but doesn’t provide ESP log collection mechanics.

• VPC: A logically isolated virtual network in a cloud environment; it describes networking, not shared application access.
• NFV: Replaces dedicated network appliances with virtualized network functions.
• SaaS: A cloud service model in which users consume an application without managing its infrastructure. It could describe how the application is delivered, but the question emphasizes serving multiple user groups, which points to multitenancy.

• A — IDS attack signatures: An IDS generally detects suspicious network activity but does not necessarily scan uploaded PDF files or prevent them from being accepted.
• C — Load balancer: Distributes traffic among servers; it does not inspect files for malware.
• D — WAF command-injection blocking: A WAF can help block web attacks such as command injection, SQL injection, and cross-site scripting, but this option does not specifically address malicious PDF uploads.

• Why this is correct: In Azure Virtual Desktop, user access to a host pool is controlled through App Groups. The default app group for a host pool publishes the full desktop, so adding members to that app group grants them sign-in and access to the desktop (and any RemoteApps in that group). This is the standard way to give users access to AVD resources.

• Why the other options are not correct:

• Practical steps (high level):

• A separate scope using a /32 subnet: A /32 identifies one host, but it is not a practical DHCP scope for this purpose.
• A static IP within the DHCP range: This can cause an IP address conflict if DHCP assigns that address to another device.
• SLAAC: Used for automatic IPv6 address configuration, not for assigning a predictable IPv4 address through DHCP.

• A Storage Gateway File Gateway provides an on-premises NFS/SMB file share that's backed by objects in S3. This is exactly what you need to migrate an NFS workload: applications continue using NFS, while the actual data moves to and is stored in S3.
• It can cache frequently accessed data locally for performance, while uploads go to an S3 bucket.
• Why the other options aren’t suitable:

Why

cmd 
PowerShell.exe -ExecutionPolicy Bypass -File C:\Scripts\ConfigureVM.ps1

Why the other options are less suitable

• GPO logon script: Runs only when a user logs on and may not run during initial VM provisioning.
• GPO startup script: Can work, but requires the VM to be joined to the domain and the policy to be applied. It is also normally evaluated at each startup.
• Place scripts in a VHD: Merely placing scripts on a disk does not cause them to execute.

• User1 can sign in because the account is cloud-only. It does not depend on the on-premises domain.
• User3 can sign in because the account uses Password Hash Synchronization (PHS). Azure AD has a synchronized password hash and can validate the sign-in even when connectivity to on-premises Active Directory is unavailable.
• User2 cannot sign in because the account relies on Pass-through Authentication (PTA). PTA sends the authentication request to an on-premises PTA agent, which must contact a domain controller. With the internet connection from on-premises lost, that validation cannot occur.

• The diagnostic output shows that the protocol is TCP (proto=6) and the session state is 2.
• In FortiGate’s session output, state=2 maps to SYN_SENT. This means the TCP SYN has been sent but the handshake hasn’t completed yet.
• Therefore, the session is not ESTABLISHED, FIN/ACK-related states, or other states; it’s in SYN_SENT.

• Goal: Identify the host that originated the infection, then label each remaining host as infected or clean based on log evidence.

• Logs to review (across hosts and firewall):

• How to identify the origin:

• How to classify other hosts:

• Quick tip: use the Reset All option if you want to re-run the scenario and practice again.