Explanation
Scenario, the log capacity issue: Developers report that the number of log message in the trace output for the processor is too high, resulting in lost log messages.
Sampling is a feature in Azure Application Insights. It is the recommended way to reduce telemetry traffic and storage, while preserving a statistically correct analysis of application data. The filter selects items that are related, so that you can navigate between items when you are doing diagnostic investigations. When metric counts are presented to you in the portal, they are renormalized to take account of the sampling, to minimize any effect on the statistics.
Sampling reduces traffic and data costs, and helps you avoid throttling.
Reference:
https://docs.microsoft.com/en-us/azure/azure-monitor/app/sampling

Explanation


Box 1: Service bus queue
You are developing a back-end Azure App Service that scales based on the number of messages contained in a Service Bus queue.
Box 2: ActiveMessage Count
ActiveMessageCount: Messages in the queue or subscription that are in the active state and ready for delivery.
Box 3: Count
Box 4: Less than or equal to
You need to add a new rule that will continuously scale down the App Service as long as the scale up condition is not met.
Box 5: Decrease count by

Explanation
A service SAS is secured with the storage account key. A service SAS delegates access to a resource in only one of the Azure Storage services: Blob storage, Queue storage, Table storage, or Azure Files.
Stored access policies give you the option to revoke permissions for a service SAS without having to regenerate the storage account keys.
Reference:
https://docs.microsoft.com/en-us/azure/storage/common/storage-sas-overview

Explanation

Explanation
You can form a partition key by concatenating multiple property values into a single artificial partitionKey property. These keys are referred to as synthetic keys.
Another possible strategy to distribute the workload more evenly is to append a random number at the end of the partition key value. When you distribute items in this way, you can perform parallel write operations across partitions.
Note: It's the best practice to have a partition key with many distinct values, such as hundreds or thousands.
The goal is to distribute your data and workload evenly across the items associated with these partition key values. If such a property doesn't exist in your data, you can construct a synthetic partition key.
References:
https://docs.microsoft.com/en-us/azure/cosmos-db/synthetic-partition-keys