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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Develop AI solutions using Azure data services | 30% | - Implement vector-enabled databases
|
| Topic 2: Integrate backend services and build event-driven architectures | 25% | - Implement messaging and event systems
|
| Topic 3: Secure, monitor, and optimize AI solutions | 20% | - Implement observability and reliability
|
| Topic 4: Develop containerized AI solutions on Azure | 25% | - Implement container hosting environments
|
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NEW QUESTION # 80
A large retail company operates online and physical stores. The company tracks inventory levels in real time to manage stock efficiently across all locations. You develop an Azure Event Grid solution to handle events generated by the inventory management system deployed to Azure.
You need to implement a subscription filter that dynamically adjusts to seasonal changes in product demand.
Which event filter should you use?
Answer: C
NEW QUESTION # 81
You are implementing the expiration requirement for AI-generated summaries in the Redis cache.
You need to purge the AI summaries five minutes after creation, regardless of how often they are accessed.
What should you do?
Answer: D
Explanation:
Configure a fixed expiration timeout on each Redis key when the summary is created , such as a five- minute TTL. Azure Managed Redis automatically removes a key when its configured timeout expires.
Critically, ordinary read operations do not extend that expiration period, so a summary created at time T will expire approximately five minutes later regardless of how frequently clients retrieve it.
This is the required absolute-expiration behavior. In Redis, applications can establish expiration when writing the value or by using expiration commands after creation. The important design property is that the expiration deadline is not refreshed whenever the key is read.
An allkeys-lru eviction policy addresses memory pressure , not deterministic five-minute expiration. It may evict less recently used keys when memory is constrained, but it does not guarantee removal exactly five minutes after creation. The PERSIST command is directly incorrect because it removes an existing timeout , potentially causing the summary to remain indefinitely. Sliding expiration is also unsuitable because it renews or resets the expiration window based on activity, allowing frequently accessed summaries to remain longer than five minutes.
Therefore, a per-key absolute five-minute expiration is the correct configuration.
Study Guide references: Azure Managed Redis # key expiration; TTL behavior; cache expiration versus eviction; fixed versus sliding expiration.
NEW QUESTION # 82
An application performs similarity search across 5 million embeddings stored in Azure Database for PostgreSQL with pgvector. Queries often filter by department before ranking by cosine distance.
P95 latency for vector similarity queries exceeds the SLA target. Monitoring shows sustained high CPU use during query execution.
You need to reduce P95 latency for filtered vector similarity queries.
What should you do?
Answer: D
NEW QUESTION # 83
Hotspot Question
You plan to deploy a web app to App Service on Linux. You create an App Service plan. You create and push a custom Docker image that contains the web app to Azure Container Registry.
You need to access the console logs generated from inside the container in real-time.
How should you complete the Azure CLI command? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: config
Modifies the logging configuration settings for the specified Web App.
Box 2: --docker-container-logging
--docker-container-logging: The explicit parameter that defines where or how Docker container console logs are saved (e.g., filesystem).
Configure Logging:
az webapp log config --name ContosoWeb --resource-group ContosoDevRg --web-server-logging filesystem Box 3: webapp webapp specifies the group identifier within the az CLI execution context.
Box 4: tail
tail: Initiates a live, real-time diagnostic log stream directly from the active Linux container.
Reference:
https://learn.microsoft.com/en-gb/answers/questions/2225551/mis-show-azure-container-app-logs
NEW QUESTION # 84
Drag and Drop Question
You are developing a solution for a hospital to support the following use cases:
- The most recent patient status details must be retrieved even if
multiple users in different locations have updated the patient record.
- Patient health monitoring data retrieved must be the current version
or the prior version.
- After a patient is discharged and all charges have been assessed, the patient billing record contains the final charges.
You provision an Azure Cosmos DB for NoSQL database and set the default consistency level for the database account to Strong.
You set the value for Indexing Mode to Consistent.
You need to minimize latency and any impact to the availability of the solution. You must override the default consistency level at the query level to meet the required consistency guarantees for the scenarios.
Which consistency levels should you implement? To answer, drag the appropriate consistency levels to the correct requirements. Each consistency level may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Strong
Strong consistency must be used at the query level to meet this requirement.
Linearizability Guarantee: Strong consistency ensures that a read operation always returns the most recent committed version of an item.
Global Consensus: Because multiple users in different locations are updating the patient record, any reader across any region must wait for the updates to be fully committed globally before reading. This prevents any user from reading stale or out-of-order data, which is critical for patient status details.
Box 2: Bounded Staleness
To minimize latency and maximize availability while ensuring that retrieved patient health monitoring data is either the current version or the immediate prior version, you should override the consistency level at the query level to Bounded Staleness.
Version Guarantee: Bounded Staleness ensures that reads are not older than a specific time window or a configured number of versions K versions behind the latest write). Setting the version staleness to 1 (K=1 )guarantees that the data read is either the current version or the prior version.
Lower Latency: Bounded Staleness offers significantly lower latency than the account's default Strong consistency. Strong consistency requires a global majority acknowledgment before a read or write completes, increasing latency.
Higher Availability: By backing down from Strong consistency to Bounded Staleness for this query, you reduce the strict synchronization requirements, thereby minimizing impacts on availability during localized network disruptions.
Box 3: Eventual
Eventual consistency is the correct consistency level to use at the query level for this scenario.
Maximizes Performance: Eventual consistency offers the lowest latency and highest availability among all consistency levels.
Matches Scenario Needs: The billing record is final and no longer changing, so there is no risk of reading stale, in-progress updates.
Optimizes Costs: Eventual consistency queries consume half the Request Units (RUs) compared to Strong or Bounded Staleness queries.
Reference:
https://learn.microsoft.com/en-us/azure/cosmos-db/consistency-levels
NEW QUESTION # 85
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