Microsoft AI-200 Exam Prep
Developing AI Cloud Solutions on Azure (Page 13 )

• 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.

bash 
OTEL_SERVICE_NAME=foundry-agent

bash 
OTEL_SERVICE_NAME=langchain-service

python 
import os 


os.environ["OTEL_SERVICE_NAME"] = "langchain-service" 


from azure.ai.openai... # import your tracing components 
from azure.monitor.opentelemetry import configure_azure_monitor 


configure_azure_monitor( 
    connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"] 
)

• Agent application: OTEL_SERVICE_NAME=foundry-agent
• LangChain application: OTEL_SERVICE_NAME=langchain-service

• D — Managers focus on keeping costs low in the short term to maximise profits.

• E — Managers are given incentives to meet or undercut budgets.

• F — Managers delegate responsibility simply to reduce their workload.

apex 
for (Account updatedAccount : Trigger.new) { 
    AccountTriggerHelper.notinyxternalSystem(updatedAccount.Id); 
}

• Too many callouts: The callout occurs asynchronously in the future method, and each future transaction can perform its permitted callouts.
• Too many SOQL queries: The SOQL query is inside the future execution, not repeatedly in the trigger transaction.
• Callout from triggers not supported: Direct callouts from triggers are prohibited, but the trigger delegates the callout to asynchronous Apex, which is the correct pattern.

• 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.

• Unsafe images: Requires image/content moderation before the image is processed.
• Hidden instructions embedded in images: These are indirect prompt injections contained in untrusted image content or extracted text, not necessarily in the user’s typed prompt.

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.

• A — Consumption-based pricing: AWS generally uses a pay-as-you-go model. You pay for the resources you consume rather than purchasing hardware upfront or paying for unused capacity.
• C — Economies of scale: AWS purchases and operates infrastructure at a very large scale, allowing it to reduce costs and pass some savings to customers through lower service prices.

• Perpetual licenses: These involve paying once for permanent software ownership and are not a primary AWS Cloud economic benefit.
• AWS Enterprise Support at no additional cost: Enterprise Support has an additional charge.
• Bring-your-own-hardware model: AWS provides and manages the underlying cloud infrastructure; customers do not normally bring their own physical servers.

• Accept: Acknowledge the risk without taking additional action.
• Transfer: Shift the risk’s impact to another party, such as through insurance or outsourcing.
• Mitigate: Reduce the likelihood or impact, such as by implementing controls.
• Avoid: Eliminate the activity or situation that creates the risk.

• B: Não é preciso implantar o modelo em um endpoint do Amazon SageMaker, pois o Bedrock já oferece a infraestrutura de inferência.
• C: O SageMaker Model Registry é usado para gerenciar modelos no SageMaker, não é requisito para modelos customizados no Bedrock.
• D: Não existe uma etapa geral de “conceder acesso” ao modelo customizado como requisito principal de uso. O ponto essencial é adquirir o Provisioned Throughput.

• The listener uses a virtual IP address shared by the availability-group replicas.
• Floating IP, also called Direct Server Return (DSR), allows the SQL Server nodes to respond using the listener’s IP address rather than their individual VM IP addresses.
• This is required for the availability-group listener to function correctly with an Azure internal load balancer.

• 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.

1. Open the Microsoft Entra Connect wizard.
2. Select Configure.
3. Choose Customize synchronization options.
4. Authenticate when prompted.
5. On the Domain and OU filtering page, select:

1. Complete the wizard.

• Start-ADSyncSyncCycle only starts synchronization; it does not change which OUs are included.
• Manage federation configures federation settings, which are unrelated to OU filtering.
• Add-ADSyncConnectorAttributeInclusion concerns connector attributes, not selecting additional OUs for synchronization.

1. Wireless AP

1. Router

1. Firewall

1. Device placement

• Disabling a compromised account
• Blocking a malicious IP address
• Isolating an endpoint
• Creating or escalating an incident ticket

• Virus signatures: Primarily associated with antivirus or endpoint protection.
• Security agent deployment: Usually handled by endpoint-management or security-agent platforms.
• Vulnerability scanning: Typically performed by vulnerability-management tools.

• MFA: Protects sign-in and authentication.
• Azure Key Vault: Protects deployment secrets and credentials.
• Answer: No (B).

• User2 is in Group1, so CA2 applies.
• CA2 targets Office 365.
• CA2 requires MFA OR an app protection policy.
• User2 has no app protection policy, but if User2 successfully completes MFA, the OR condition is satisfied.
• The device being noncompliant does not matter because CA2 does not require device compliance.
• CA1 applies only to Global Administrators. Unless User2 is also a Global Administrator, CA1 does not apply.

• Customer needs: Primary focus in agile; guides prioritization and decision-making.
• Organization’s needs: Important constraints, but processes should be tailored when they create waste.
• Agile lead/project manager: Their role is to facilitate value delivery, not prioritize their own preferences.

• 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.

• Espionage: Stealing confidential information, often for a competitor or foreign entity.
• Data exfiltration: Unauthorized removal or transfer of data.
• Nation-state attack: A cyberattack sponsored or conducted by a government.
• Shadow IT: Unapproved technology or services used outside IT oversight.

• 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.

• 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.

• If the attachment is safe, it is released to the user.
• If malware is detected, the attachment is blocked or removed according to the policy.
• This reduces delivery delays without disabling malware scanning.

• Replace removes the original attachment and replaces it with a text file explaining that it was blocked. It does not primarily optimize delivery time.
• Block and Enable redirect blocks messages with suspicious attachments and can redirect them for review; it does not provide the required faster delivery experience.
• Monitor and Enable redirect is for observation and does not reliably block malicious attachments.

• Share files with the wrong people
• Use public links unnecessarily
• Fail to classify sensitive data
• Upload data to unauthorized services
• Misunderstand company sharing policies

• A — Step-up authentication: Helps protect administrator accounts, but does not directly address improper file sharing by users.
• C — Password complexity: Helps reduce password attacks, not accidental data disclosure.
• D — Mobile device management: Secures managed mobile devices, but does not directly control file-sharing behavior across the organization.

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

• 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.

• The users currently have Office 365 Enterprise E3 licenses assigned directly.
• Assigning Microsoft 365 Enterprise E5 through a group does not automatically remove their directly assigned E3 licenses.
• From the Licenses blade, you can select the E3 product and remove it from all assigned users in one operation. This requires less effort than editing 2,500 users individually.

• Identity Governance manages access reviews, entitlement management, and related governance—not bulk license removal.
• Set-AzureAdUser does not remove product licenses.
• Set-WindowsProductKey applies Windows product keys and is unrelated to Microsoft 365 licensing.

• B: Developer Edition has limited user, storage, and data-volume capacity, making realistic community testing difficult.
• C: A Developer Edition org cannot contain sandboxes, so it cannot provide separate environments for development, integration, and UAT.
• E: A standalone Developer Edition org is not part of the production org’s deployment path, so change sets cannot be used to deploy from it directly to that production org. The team would need Metadata API, Salesforce CLI, or another deployment method.

• A: Build a custom API — possible, but unnecessary as the primary solution and potentially more costly to develop and maintain.
• B: Use pre-built chatbots — these generally answer questions but may not support the required custom workflow and real-time actions.
• C: Fine-tune with sample data — improves model behavior but does not provide live database access.
• D: Google Cloud databases + Vertex AI — stores current inventory data and lets an AI agent retrieve it and take actions based on up-to-date information.

• Repetitive and time-consuming
• Based on measurable conditions, such as last check-in time
• Easy to automate with alerts, dashboards, or scheduled reports
• Important for ensuring scan coverage

• Assigning custom recommendations usually requires analyst judgment and context.
• Analyzing false positives can sometimes be assisted by automation, but validation often requires human review.
• Rendering an additional executive report increases reporting activity rather than reducing a core operational workload.

• 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.

• MTTC: Time required to contain or limit the incident’s impact — best match.
• MTTR: Time required to remediate or recover from the incident; this may include eradication, restoration, and cleanup, which goes beyond merely stopping spread.
• MTTD: How long it takes to discover the incident.
• MTBF: Average time between failures, generally a reliability metric.

• Determine the project budget — Budget development is a separate cost-management activity.
• Develop a communication plan — This belongs to project communications planning, not schedule completion.
• Establish baselines — Baselines are created after the schedule and related plans have been developed and approved. They formally capture the approved plan.

• File1 contains the evaluation configuration—for example, evaluators, test data, thresholds, or evaluation parameters.
• The GitHub Actions workflow must reference that file through the evaluation-config input so the action knows which evaluation to run.
• project-endpoint identifies the Microsoft Foundry project, but it does not identify the evaluation definition. It is also typically required, but it does not answer the specific requirement about using File1.

• Accept: Acknowledges the risk without taking additional action.
• Transfer: Shifts the risk or financial impact to another party, such as an insurer.
• Mitigate: Reduces the likelihood or impact through controls like patching, MFA, or segmentation.
• Avoid: Eliminates the activity that creates the risk.

• Orders contains order-level information, such as the order date.
• Order Line Items contains the products, quantities, and line amounts associated with each order.
• Merging them on the order key, such as OrderID, places the order date alongside each line item. This allows you to calculate total order value and analyze it over time.
• Product attributes can remain in the Products table and be related to the resulting line-item table through ProductID.

• Merging line items with products addresses product attributes but does not first provide the order-level date and value needed for time analysis.
• DAX calculated columns or lists add unnecessary model complexity.
• Calculating order counts is not the first requirement and does not combine the required order and line-item data.

• 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.

• Group1 — security-enabled: Eligible.
• Group2 — mail-enabled and security-enabled: Eligible because it is still a security group.
• Group3 — Microsoft 365 group: Not eligible for group-based licensing.
• Group4 — Microsoft 365 group, not security-enabled: Not eligible.

• httprint fingerprints Web servers by analyzing their HTTP responses. It can help identify the Web server type and sometimes its version, even when the banner has been modified or hidden.
• Wget is mainly used to download files or Web content.
• WinSSLMiM is associated with SSL man-in-the-middle testing.
• Whisker is an older Web-server vulnerability assessment tool, especially associated with IIS, rather than the expected banner-grabbing tool here.

• Process Builder: Automates actions based on record changes; it does not create interactive user forms.
• Approval Process: Routes records for approval and captures approval decisions.
• Outbound Message: Sends information to an external system; it does not provide a user interface.

• 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.

• Driver node: Coordinates Spark jobs and runs in the compute environment.
• Worker node: Executes tasks and processes data.
• Databricks Filesystem (DBFS): Provides storage access for data used by compute resources.

• Three DHCP scopes: Each VLAN has its own IPv4 subnet. DHCP scopes are subnet-specific, so create one scope for:

• Two DHCP relays: DHCP client discovery begins as a broadcast, and broadcasts do not cross routers or VLAN boundaries. Therefore, configure a DHCP relay on the router or Layer 3 switch interface for each client VLAN.

• Who owns security risks and decisions
• Who is responsible for implementing controls
• Who reports security performance to management
• How security responsibilities align with business objectives

• B — Compliance with audit requirements: Governance may support compliance, but audit compliance is not its main objective.
• C — Monitoring security incidents: This is an operational security activity, not the central purpose of governance.
• D — Creation of tactical solutions: Governance establishes direction and oversight; tactical solutions belong to management and operational teams.

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

• Information sources: Collect security-related data, such as network packets, system logs, audit records, or application events.
• Analysis: Examines the collected data to identify suspicious activity, attacks, or policy violations.
• Response: Takes or recommends action, such as generating alerts, logging the event, or supporting a protective response.

• 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.

• Base table — the table containing common inherited fields
• Parent table — the table directly extended by the child
• Other tables in the hierarchy

• 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.