You are developing an application that use an Azure blob named data to store application data. The application creates blob snapshots to allow application state to be reverted to an earlier state. The Azure storage account has soft deleted enabled.
The system performs the following operations in order:
*The blob is updated
*Snapshot 1 is created.
*Snapshot 2 is created.
*Snapshot 1 is deleted.
A system error then deletes the data blob and all snapshots.
You need to determine which application states can be restored.
What is the restorability of the application data? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation

Box 1: Can be restored
When enabled, soft delete enables you to save and recover your data when blobs or blob snapshots are deleted.
This protection extends to blob data that is erased as the result of an overwrite.
Box 2: Cannot be restored
It has been deleted.
Box 3: Can be restored
It has not been deleted.
References:
https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blob-soft-delete

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You are developing a new page for a website that uses Azure Cosmos DB for data storage. The feature uses documents that have the following format:

You must display data for the new page in a specific order. You create the following query for the page:

You need to configure a Cosmos DB policy to the support the query.
How should you configure the policy? To answer, drag the appropriate JSON segments to the correct locations. Each JSON segment 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.

Correct Answer:

Explanation:

Box 1: compositeIndexes
You can order by multiple properties. A query that orders by multiple properties requires a composite index.
Box 2: descending
Example: Composite index defined for (name ASC, age ASC):
It is optional to specify the order. If not specified, the order is ascending.
{
"automatic":true,
"indexingMode":"Consistent",
"includedPaths":[
{
"path":"/*"
}
],
"excludedPaths":[],
"compositeIndexes":[
[
{
"path":"/name",
},
{
"path":"/age",
}
]
]
}

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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 in the review screen.
You are developing an Azure solution to collect point-of-sale (POS) device data from 2,000 stores located throughout the world. A single device can produce 2 megabytes (MB) of data every 24 hours. Each store location has one to five devices that send data.
You must store the device data in Azure Blob storage. Device data must be correlated based on a device identifier. Additional stores are expected to open in the future.
You need to implement a solution to receive the device data.
Solution: Provision an Azure Event Grid. Configure the machine identifier as the partition key and enable capture.
Does the solution meet the goal?

• A.Yes
• B.No

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Drag and Drop Question
You are a developer for a software as a service (SaaS) company that uses an Azure Function to process orders. The Azure Function currently runs on an Azure Function app that is triggered by an Azure Storage queue.
You are preparing to migrate the Azure Function to Kubernetes using Kubernetes-based Event Driven Autoscaling (KEDA).
You need to configure Kubernetes Custom Resource Definitions (CRD) for the Azure Function.
Which CRDs should you configure? To answer, drag the appropriate CRD types to the correct locations. Each CRD type 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.

Correct Answer:

Explanation:
Box 1: Deployment
To deploy Azure Functions to Kubernetes use the func kubernetes deploy command has several attributes that directly control how our app scales, once it is deployed to Kubernetes.
Box 2: ScaledObject
With --polling-interval, we can control the interval used by KEDA to check Azure Service Bus Queue for messages.
Example of ScaledObject with polling interval
apiVersion: keda.k8s.io/v1alpha1
kind: ScaledObject
metadata:
name: transformer-fn
namespace: tt
labels:
deploymentName: transformer-fn
spec:
scaleTargetRef:
deploymentName: transformer-fn
pollingInterval: 5
minReplicaCount: 0
maxReplicaCount: 100
Box 3: Secret
Store connection strings in Kubernetes Secrets.
Example: to create the Secret in our demo Namespace:
# create the k8s demo namespace
kubectl create namespace tt
# grab connection string from Azure Service Bus
KEDA_SCALER_CONNECTION_STRING=$(az servicebus queue authorization-rule keys list \ -g
$RG_NAME \
--namespace-name $SBN_NAME \
--queue-name inbound \
-n keda-scaler \
--query "primaryConnectionString" \
-o tsv)
# create the kubernetes secret
kubectl create secret generic tt-keda-auth \
--from-literal KedaScaler=$KEDA_SCALER_CONNECTION_STRING \
--namespace tt
Reference:
https://www.thinktecture.com/en/kubernetes/serverless-workloads-with-keda/

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You have a workspace-based Azure Application Insights resource named Insightsl and an Azure App Service Web App named Appl. Insights! collects telemetry generated by Appl.
You plan to test the availability of Appl by using Insightsl. The test must include the following tasks:
* Parse dependent requests.
* Validate TLS certificates.
* Configure custom request headers.
You must minimize development and implementation efforts.
You need to implement the Application Insights availability test that will deliver the required functionality. Which availability test should you implement?

• A.Standard test
• B.Custom TrackAvailability test
• C.Multi-step web test
• D.URL ping test

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