Microsoft AI-200 Exam Prep
Developing AI Cloud Solutions on Azure (Page 6 )

• 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.

• UPS battery-backed outlets: Connect only essential devices needed during an outage:

• Surge-protector-only outlets: Connect nonessential devices, especially the printer. Printing does not need to continue while you are saving work and shutting down.
• UPS power source: Plug the UPS directly into a wall outlet.
• Surge protector power source: Plug it directly into a wall outlet as well. Do not normally plug a surge protector into the UPS, because that creates a daisy chain and can overload the UPS.

• 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.

• 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.

• 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.

• Render thousands of animation frames
• Generate product images in multiple sizes
• Apply filters or transformations to a large image collection
• Produce visual effects for a video

• Transport and handling
• Storage and warehousing
• Refrigeration
• Shelf-stacking or replenishment
• Other costs directly attributable to product P

• 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.

• 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.

• Deterministic approve/reject results
• Strict adherence to predefined rules
• Consistent, reproducible outcomes
• Auditability and regulatory compliance

text 
user<TAB>action<TAB>status

text 
user|action|status

• Colons: Although colons commonly appear in log data, they are not a supported delimiter choice in the FX workflow described by this exam question.
• Spaces: Spaces are not treated as a supported delimiter for this extraction method; ordinary text often contains variable spacing.

• Confirming the data has the required columns and data types
• Handling missing or duplicate records
• Converting data into a suitable format
• Selecting or engineering useful features
• Splitting it into training, validation, and test sets

1. Prepare the training data
2. Select an algorithm or configure AutoML
3. Train the model
4. Evaluate its performance
5. Tune hyperparameters if needed
6. Deploy the model

• Product recall: Premature before confirming a violation or assessing risk.
• Notify the regulatory authority: May be required later, especially if the discrepancy affects safety or compliance, but first investigate and verify the facts.
• Inform production: Not the initial regulatory assessment step; production may become involved if a packaging or manufacturing error is identified.

• Key-based authentication: Provides an endpoint secured with API keys.
• Real-time REST access: Supports online inference through an HTTP/REST endpoint.
• No VM vCPU quota consumption: Microsoft hosts and manages the underlying infrastructure, so your subscription’s VM quota isn’t used.

• Batch: Intended for asynchronous, large-volume processing rather than real-time requests.
• Self-hosted container: You manage the infrastructure and typically need compute resources and quota.
• Standard: This is not the clearest deployment type for the stated requirements; the specific Foundry option is serverless API.

Manager role

DAX 
Country[Manager] = USERPRINCIPALNAME()

• Sales
• Human Resources

CFO role

• See sales for all countries
• See no Human Resources data

• Do not restrict the Country table or Sales table.
• Apply a filter to Human Resources that always returns false, such as:

DAX 
FALSE()

• \Pipeline1
• \Folder1\Lakehouse1

• Pipeline1 remains at the workspace root in Workspace1, so it is deployed to the root of Workspace2.
• Lakehouse1 was moved into Folder1, so its full path is preserved as \Folder1\Lakehouse1.
• Fabric deployment pipelines preserve folder paths because an item’s full path is treated as part of its name.

• Type 1 hypervisor: Runs directly on the physical hardware (“bare metal”).
• Type 2 hypervisor: Runs inside the host OS as an application.

• Bare-metal installation: Type 1
• Local management only: Not a defining characteristic
• Specific hardware requirements: Not the key distinction

• 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.

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

• Relationship cardinality:

• Filter direction:

• Active versus inactive relationships: only active relationships automatically propagate filters.
• Blank or unmatched values: a fact-table value without a matching dimension row can create the model’s blank/unknown member.
• Uniqueness: the “one” side must contain unique values; duplicate keys generally belong on the “many” side.

• JDBC
• SnowSQL
• Snowflake Web Interface (UI)
• ODBC
• Python connector

DAX 
Sales % of Total = 
DIVIDE( 
    [Total Sales], 
    CALCULATE( 
        [Total Sales], 
        ALLSELECTED(Products) 
    ) 
)

DAX 
Total Sales = 
SUM(Sales[SalesAmount])

Why ALLSELECTED is required

• The numerator, [Total Sales], is evaluated for the current product.
• ALLSELECTED(Products) removes the current product’s visual filter when calculating the denominator.
• It preserves filters applied at the report, page, or slicer level.

Why not ALL(Products)?

DAX 
CALCULATE([Total Sales], ALL(Products))

• Review the risk register.
• Check the documented risk response strategy, such as using a backup resource, reallocating work, or adjusting sequencing.
• Implement the planned response promptly.

• B: Moving the task may affect the critical path and should not be done without first evaluating the planned response and impacts.
• C: Excluding a required task would change scope and business requirements without proper analysis or approval.
• D: Updating lessons learned and the risk log may be appropriate later, but it does not address the immediate problem. First, execute the response.

• Scanning is not essential during a power outage.
• A scanner can consume UPS battery power without helping the user save cloud documents or shut down safely.
• The UPS should be reserved for the computer, monitor, and necessary network equipment.
• The surge protector helps protect the scanner from voltage spikes, but it will not keep it running during an outage.

• Packet loss
• Latency
• Jitter
• Call quality by user, device, network, location, or building

• Teams Usage Report: Shows adoption and usage statistics, not detailed call-quality metrics.
• Teams Device Usage Report: Reports which devices are being used and how, but does not provide detailed packet-loss analysis.
• Microsoft Network Testing Companion: Helps assess network readiness before deployment, but it is not the primary tool for analyzing packet loss from actual Teams calls.

• Containment policy: controls permitted communication during containment.
• Detection/response configuration: determines when containment is initiated.

• Outer packet: 10.5.1.1 > 52.165.16.154
• IPv4 protocol field: 41, which indicates IPv6 encapsulation
• Inner packet: IPv6 traffic between 2001:... addresses

• MAC address spoofing: Changes Layer 2 addressing; it does not explain the IPv6-in-IPv4 structure.
• Steganography: Hides data inside files or media, not visibly in a tunneled protocol.
• Broken encryption: No evidence of encryption being cracked.
• On-path sniffing: Involves intercepting traffic, not sending data to an external host.

• Delete the City column
• Remove duplicates from the Country column

1. ???? City ??? ????? ?? ???? ?????? ???? ?????.
2. ???? ???? Country ?????? Remove duplicates ?????? ??? ?? ???? ??? ?????.

• Attack simulator — Used to run phishing and other attack simulations for user awareness training.
• Hunting — Used to proactively query security data and investigate potential threats.
• Incidents — Used to investigate and manage related alerts and active security events.

• 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.

• Unrestricted data mining: Data mining is not automatically a privacy violation. It becomes an issue when personal data is collected or used improperly.
• Identity theft: This is a possible consequence of inadequate privacy protection, but it is not the central focus of privacy regulations.
• Human rights protection: Privacy can be considered a human right, but this option is broader than the specific regulatory focus.
• Identifiable personal data: Regulations such as HIPAA focus directly on controlling the collection, use, disclosure, and protection of personal information.

• The table is large.
• Queries frequently filter or join on particular columns.
• The table’s natural data order does not support good micro-partition pruning.
• Clustering improves performance enough to justify its maintenance cost.

• A class/teacher fact should contain one row per Class ID. It can support the count of classes and contain attributes such as Teacher First Name and Period Number.
• An attendance fact should contain one row per attendance event, such as Class ID + student + date. It supports attendance counts by day and monthly averages.

• Teacher First Name ? Teacher fact
• Period Number ? Attendance fact

• AWS Network Firewall can inspect and block traffic across a VPC when traffic is routed through the firewall. A Drop action rule can deny traffic from the suspicious source IP.
• GuardDuty findings are sent to Security Hub.
• A Lambda function can be invoked when Security Hub receives a new GuardDuty finding, extract the source IP, and update the Network Firewall policy with a blocking rule.

• GuardDuty threat lists: Used to identify or increase the severity of findings; they do not directly block VPC traffic.
• AWS WAF: Protects supported web applications, such as CloudFront or Application Load Balancers. It does not provide general VPC-wide traffic blocking.
• GuardDuty suppression rules: Suppress or hide findings. They do not block the suspicious traffic.

• A — Windows 11 with Azure CLI installed: Yes

• D — Chrome OS using Azure Cloud Shell: Yes

• E — Windows 10 with the Azure PowerShell module installed: Yes

• B — Linux with only Azure CLI: No, because the option does not state that PowerShell is installed.
• C — macOS with PowerShell Core only: No, because it does not state that Azure PowerShell modules or Azure CLI are installed.

• Job Links ? URL ID: Mainly summarizes link performance; it is not the easiest place to retrieve individual email addresses by alias.
• Tracking Overview ? Clicks: Provides aggregate click metrics, not a targeted list for one aliased link.
• Click Activity ? Link View: Focuses on link-level reporting, but the question’s intended workflow for locating clicks tied to a specific placement/alias is Email Overlay.

• 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.

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.

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.

• 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.

• Plenum: Describes a fire-resistant cable jacket rating, not a transmission medium or speed.
• Ethernet: Describes a networking technology; Ethernet can use copper or fiber, so the term alone does not identify the fastest cable type.
• DAC (Direct Attach Copper): Uses copper and is typically intended for short-distance, high-speed connections in data centers.

• ?? ?? ?? ??
• ?? NFS ?? SMB ?? ??
• ?? ???? ???
• ?? IP ??? ???? ?? ???
• ??? ?? ???? ?????

• B: ????? NFS ? Snowball Edge? ?? ?? ? AWS? ?? ? S3
• D: ????? NFS ? ????/Direct Connect ? File Gateway ? S3

1. The specific table — for example, incident
2. The parent table — for example, task
3. The wildcard table — *, which applies broadly

• Un AG puede tener réplicas en Windows y Linux desde SQL Server 2017; por tanto, una réplica Windows y otra Linux es posible.
• Sin embargo, las réplicas de un AG deben utilizar normalmente la misma versión principal de SQL Server. Una instancia SQL Server 2017 no puede tener directamente una réplica secundaria SQL Server 2019 como configuración normal y permanente.
• En tu escenario, SQL Server 2017 en Windows y SQL Server 2019 en Linux no se pueden añadir directamente como réplicas equivalentes de AG1. Primero habría que realizar un proceso de actualización/migración compatible, por ejemplo mediante una actualización gradual o una tecnología de migración como log shipping o distributed availability groups, según el diseño.

• Tipo de clúster y mecanismo de quorum.
• Failover normalmente manual en configuraciones multiplataforma.
• Edición y características compatibles.
• Configuración de endpoints y permisos.
• Limitaciones específicas de SQL Server en Linux.

• Root path cost
• Port priority
• Port ID

text 
interface GigabitEthernet0/1 
 spanning-tree vlan 10 port-priority 64

• Interface number: Helps form the port ID but is not normally configured as the preference value.
• VLAN priority: Not used to select a preferred forwarding interface.
• Hello time: Controls how often BPDUs are sent; it does not select a preferred port.

• Highly polished, organization-wide presentations
• Advanced dashboard design and customization
• Broader business-user distribution and interaction
• Specialized BI governance and modeling features

• Use the grant-date fair value: $30
• Do not remeasure to the year-end value of $45
• Update the estimate of employees expected to vest

• Dr Share-based payment expense $450,000
• Cr Equity/share option reserve $450,000

• Box 1: No — The rule requires user.department to equal Engineering. Engineer does not match, so User1 is not in AU1. Admin1 cannot reset User1’s password.
• Box 2: No — Admin1’s role is scoped to AU1 and cannot manage users outside that AU.
• Box 3: Yes — Admin2 is a Global Administrator and can reset User3’s password.

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