Our Developing AI Cloud Solutions on Azure (AI-200) practice exam can be modified in terms of length of time and number of questions to help you prepare for the Microsoft real test. We're certain that our AI-200 Questions are quite similar to those on AI-200 real exam since we regularly update and refine the product based on the latest exam content.
| Section | Objectives |
|---|---|
| Topic 1: Connect to and consume Azure services | - Integrate Azure services
|
| Topic 2: Secure, monitor, troubleshoot Azure solutions | - Operate AI cloud solutions
|
| Topic 3: Develop containerized solutions on Azure | - Implement containerized applications
|
| Topic 4: Develop AI solutions by using Azure data management services | - Work with Azure data platforms for AI workloads
|
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NEW QUESTION # 123
Hotspot Question
You have an Azure Functions app using the Consumption hosting plan for a company. The app contains the following functions:
You plan to enable dynamic concurrency on the app. The company requires that each function has its concurrency level managed separately.
You need to configure the app for dynamic concurrency.
Which file or function names should you use? To answer, select the appropriate values in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: host.json
To configure dynamic concurrency for the app, use the host.json configuration file.
host.json: Global metadata file where you enable the app-level dynamic concurrency setting ("dynamicConcurrencyEnabled": true) under the appropriate extension/extension lock configuration.
Box 2: f3
Apply the host.json file to the Azure Queue trigger function (f3), as dynamic concurrency is natively supported and managed per extension for runtime-driven storage and queue triggers rather than HTTP or timer triggers.
Azure Queue trigger function: Dynamic concurrency in Azure Functions specifically targets runtime-driven background bindings like Azure Queue, Blob, and Service Bus storage triggers, allowing individual management and automatic adjustments of processing limits per function.
Reference:
https://learn.microsoft.com/en-us/azure/azure-functions/functions-concurrency
NEW QUESTION # 124
You are designing Azure Functions for three different backend workloads.
Each workload requires one of the following dispatching models:
- Return an immediate response to a client.
- Process background work from a queue.
- Run code on a fixed schedule.
You need to select the trigger for each requirement.
Which triggers should you select? To answer, move the appropriate triggers to the correct requirements. You may use each trigger 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:
* Return an immediate response to a client: HTTP trigger
* Process background work from a queue: Queue Storage trigger
* Run code on a fixed schedule: Timer trigger
Use an HTTP trigger when a function must be invoked by an HTTP request and return a response directly to the calling client. Microsoft documents HTTP triggers as the standard mechanism for building serverless APIs and handling web requests or webhooks. This makes the HTTP trigger the correct fit for synchronous request- response workloads.
For asynchronous background processing, use an Azure Queue Storage trigger . A queue-triggered function runs when messages are added to an Azure Storage queue. This decouples the producer from the consumer and is appropriate for background processing where work can be buffered and processed independently of the original request. Microsoft also documents target-based scaling for Queue Storage triggers on supported Azure Functions hosting plans.
For scheduled execution, use a Timer trigger . Microsoft states that a timer trigger runs a function according to a configured schedule, typically expressed with an NCRONTAB/CRON expression. This makes it the correct choice for periodic maintenance, scheduled synchronization, reporting, or other fixed-time workloads.
Event Grid and Blob Storage triggers are event-driven mechanisms for event notifications and blob changes respectively, but neither matches these three stated dispatching requirements.
Study Guide references: Azure Functions # HTTP triggers; Queue Storage triggers; Timer triggers; event- driven and scheduled execution.
NEW QUESTION # 125
You deploy an AI application across multiple Azure regions.
The application must be able to view writes across all regions within a predictable time window.
You need to determine the appropriate consistency level.
What are two consistency levels you can use to achieve the goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: C,D
Explanation:
The two appropriate consistency levels for a globally distributed AI application needing to view writes within a predictable time window are Bounded Staleness and Strong.
Bounded Staleness: This provides a guarantee that reads will lag behind writes by a user- specified "staleness window" (either in time or number of operations). It delivers high availability and predictable read consistency across all regions, balancing performance with strict read-order guarantees.
Strong: This provides linearizable and absolute consistency, ensuring that writes are seen synchronously across all regions. It features an exact zero-second predictable time window, though it comes at the expense of higher latency for multi-region operations due to the time required to replicate globally.
Reference:
https://learn.microsoft.com/en-us/azure/cosmos-db/consistency-levels
NEW QUESTION # 126
You are building a semantic search feature for a chatbot. You store document embeddings in Redis.
You review the following Python code that connects to Redis and stores an embedding value:
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Verified Answer: Yes; No; Yes.
Detailed Explanation: `HSET` stores the binary embedding as a field in the Redis hash keyed by `doc:1`, so the first statement is true. The code does not create a RediSearch/Redis Query Engine vector index or define a vector field schema; merely storing bytes does not enable similarity search, so the second statement is false.
`EXPIRE doc:1 600` sets a 600-second lifetime, which is ten minutes, making the third statement true.
Study Guide Alignment: AI data-management workloads: Cosmos DB, PostgreSQL, caching, vector storage, vector retrieval, consistency, and connection optimization.
Official Microsoft Learn References: AI-200 Study Guide | Vector search in Azure Managed Redis
NEW QUESTION # 127
You deploy an AI application across multiple Azure regions.
The application must be able to view writes across all regions within a predictable time window.
You need to determine the appropriate consistency level.
What are two consistency levels you can use to achieve the goal? Each correct answer presents a complete solution. Choose two.
NOTE: Each correct selection is worth one point.
Answer: C,D
NEW QUESTION # 128
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