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You are building a website that uses Azure Blob storage for data storage. You configure Azure Blob storage lifecycle to move all blobs to the archive tier after 30 days.
Customers have requested a service-level agreement (SLA) for viewing data older than 30 days.
You need to document the minimum SLA for data recovery.
Which SLA should you use?
The archive access tier has the lowest storage cost. But it has higher data retrieval costs compared to the hot and cool tiers. Data in the archive tier can take several hours to retrieve depending on the priority of the rehydration. For small objects, a high priority rehydrate may retrieve the object from archive in under 1 hour.
https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blob-storage-tiers?tabs=azure-portal
You are developing a software solution for an autonomous transportation system. The solution uses large data sets and Azure Batch processing to simulate navigation sets for entire fleets of vehicles.
You need to create compute nodes for the solution on Azure Batch.
What should you do?
A Batch job is a logical grouping of one or more tasks. A job includes settings common to the tasks, such as priority and the pool to run tasks on. The app uses the BatchClient.JobOperations.CreateJob method to create a job on your pool.
Incorrect Answers:
C, D: To create a Batch pool in Python, the app uses the PoolAddParameter class to set the number of nodes, VM size, and a pool configuration.
https://docs.microsoft.com/en-us/azure/batch/quick-run-dotnet
https://docs.microsoft.com/en-us/azure/batch/quick-run-python
You have an Azure API Management (APIM) Standard tier instance named APIM1 that uses a managed gateway.
You plan to use APIM1 to publish an API named API1 that uses a backend database that supports only a limited volume of requests per minute. You also need a policy for AP11 that will minimize the possibility that the number of requests to the backend database from an individual IP address you specify exceeds the supported limit.
You need to identify a policy for API1 that will meet the requirements.
Which policy should you use?
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. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
You are implementing an application by using Azure Event Grid to push near-real-time information to customers.
You have the following requirements:
* You must send events to thousands of customers that include hundreds of various event types.
* The events must be filtered by event type before processing.
* Authentication and authorization must be handled by using Microsoft Entra ID.
* The events must be published to a single endpoint.
You need to implement Azure Event Grid.
Solution: Publish events to a partner topic. Create an event subscription for each customer.
Does the solution meet the goal?
You are developing a web application that uses Azure Cache for Redis. You anticipate that the cache will frequently fill and that you will need to evict keys.
You must configure Azure Cache for Redis based on the following predicted usage pattern: A small subset of elements will be accessed much more often than the rest.
You need to configure the Azure Cache for Redis to optimize performance for the predicted usage pattern.
Which two eviction policies will achieve the goal?
NOTE: Each correct selection is worth one point.
B: The allkeys-lru policy evict keys by trying to remove the less recently used (LRU) keys first, in order to make space for the new data added. Use the allkeys-lru policy when you expect a power-law distribution in the popularity of your requests, that is, you expect that a subset of elements will be accessed far more often than the rest.
C: volatile-lru: evict keys by trying to remove the less recently used (LRU) keys first, but only among keys that have an expire set, in order to make space for the new data added.
Note: The allkeys-lru policy is more memory efficient since there is no need to set an expire for the key to be evicted under memory pressure.
