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| Section | Objectives |
|---|---|
| Topic 1: Develop containerized solutions on Azure | - Implement containerized applications
|
| Topic 2: Connect to and consume Azure services | - Integrate Azure services
|
| Topic 3: Develop AI solutions by using Azure data management services | - Work with Azure data platforms for AI workloads
|
| Topic 4: Secure, monitor, troubleshoot Azure solutions | - Operate AI cloud solutions
|
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NEW QUESTION # 115
Drag and Drop Question
You are configuring sampling for a distributed application that sends traces to Azure Monitor.
The solution must
- Preserve upstream sampling decisions across distributed traces.
- Capture all spans during local testing.
- Sample 10 percent of traces in production.
You need to apply the appropriate sampling configuration for each requirement.
What should you do? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: ParentBasedSampler
ParentBasedSampler is the correct setup to use because it inspects incoming trace context and honors the sampling decision made by an upstream parent span.
Conserves Decisions: If an upstream service marks a trace as sampled or dropped, the ParentBasedSampler delegates the exact same decision to downstream child services.
Prevents Broken Traces: It avoids gaps in end-to-end telemetry by ensuring entire transaction chains are kept or discarded together.
Box 2: AlwaysOnSampler
AlwaysOnSampler is the correct setup to use because it samples every single span (100% trace capture rate) without dropping any telemetry, making it ideal for local development, debugging, and testing.
AlwaysOnSampler: Samples and records 100% of all traces and spans regardless of volume or upstream decisions.
Box 3: TraceIdRatioBasedSampler(0.1)
To capture exactly 10 percent of traces in production using OpenTelemetry and Azure Monitor, you should use TraceIdRatioBasedSampler(0.1).
Fixed-Rate Sampling: Azure Monitor and standard OpenTelemetry configurations achieve a fixed percentage rate by evaluating the randomly generated 128-bit Trace ID.
Ratio Representation: A sampling ratio between 0 and 1 represents the percentage. Passing a parameter of 0.1 mathematically translates to capturing exactly 10% of your production traffic.
Reference:
https://medium.com/@varun_0K/sampling-strategies-in-distributed-tracing-a-comprehensive-guide-6e80092068c3
https://learn.microsoft.com/en-us/azure/azure-monitor/app/application-insights-faq
NEW QUESTION # 116
You deploy a GPT-4o model in Azure AI Foundry. Users report inconsistent completions for the same prompt. You need to make outputs more deterministic without changing the prompt. What should you do?
Answer: B
Explanation:
Temperature controls randomness in token selection. Setting it near 0 makes the model consistently choose the highest-probability next token, producing more deterministic and repeatable output for identical prompts.
NEW QUESTION # 117
You need to secure an Azure OpenAI resource so that it is only reachable from your virtual network and not from the public internet. What should you configure?
Answer: B
Explanation:
Private Link/private endpoints assign the Azure OpenAI resource a private IP within your VNet and allow disabling public network access, ensuring traffic stays on the Microsoft backbone network and isn't reachable from the public internet.
NEW QUESTION # 118
You deploy a production Azure Function app that connects to an Azure SQL Database.
The solution must provide the following functionality:
- Prevent secrets from being exposed in source control.
- Support secret rotation without redeploying the function app.
- Avoid downtime during credential updates.
You need to configure secure and maintainable secret management.
What should you configure?
Answer: B
Explanation:
To meet all requirements, you should configure Application settings with Key Vault references.
Source Control Protection: The Function App source code and configuration files only store a reference URI (e.g., @Microsoft.KeyVault(SecretUri=...)) rather than the actual connection string, keeping secrets entirely out of source control.
Seamless Secret Rotation: Azure Key Vault handles secret rotation natively. When a database password changes, you simply update the secret in Key Vault.
Zero Downtime: By using versionless Key Vault references (omitting the specific version GUID from the URI), the Azure Function App will automatically fetch the latest secret version within 24 hours without requiring a code redeployment or app restart.
References:
https://oneuptime.com/blog/post/2026-02-16-how-to-configure-managed-identity-for-azure-app-service-to-access-key-vault-secrets-without-credentials/view
NEW QUESTION # 119
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals.
You are preparing a production deployment for an Azure Function app. The app will run across multiple environments.
The solution must support environment-specific configuration and prevent secrets from being stored in source control.
You need to develop the solution.
Solution: Store connection strings in the Function app application settings configured in the Azure Portal.
Does the solution meet the goal?
Answer: A
Explanation:
Azure Functions application settings are the correct mechanism for keeping environment-specific configuration outside the application source code. Microsoft documents that application settings, including connection strings and other configuration values, are defined separately for each function app . This allows development, test, staging, and production deployments to use different values without modifying the application code.
At runtime, Function app settings are exposed to the application as environment variables , so code can retrieve the required connection string or configuration value without embedding it in a configuration file committed to source control. This directly satisfies the requirement to prevent secrets from being stored in the Git repository.
For production-grade secret management, Azure Key Vault references are often preferable because they provide centralized secret lifecycle management and can be combined with managed identities. However, the question asks only whether the proposed solution meets the stated goals. Storing connection strings in Azure Function application settings does satisfy both: values can vary by deployed environment and remain outside source-controlled application files.
Study Guide references: Azure Functions configuration; application settings; environment variables; secure application configuration.
NEW QUESTION # 120
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