Suggested Answer:D🗳️
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. References: https://docs.microsoft.com/en-us/azure/azure-monitor/app/sampling
I agreed the answer should be C, but with a different reason.
Option B & D are both wrong because sampling is only useful to reduce telemetry data (CPU %, # of requests, etc); the issue in this question however is about trace output (User created! File uploaded! Permission denied! etc), not telemetry.
Capacity issue -
During busy periods, employees report long delays between the time they upload the receipt and when it appears in the web application.
busy hours and long delays doesn't impose CPU and therefore telemetry?
im confused
This is not a capacity issue question but Logging. One of the requirements is that App Insights must always contain all log messages. The issue is lost log msgs.
I'll go with Sampling.
I think the answer is correct it is D:
https://docs.microsoft.com/en-us/azure/azure-monitor/app/sampling
Adaptive sampling
Adaptive sampling affects the volume of telemetry sent from your web server app to the Application Insights service endpoint.
I think it's correct
https://docs.microsoft.com/en-us/azure/azure-monitor/learn/tutorial-performance
Find and diagnose performance issues with Azure Application Insights
Identify the performance of server-side operations
Analyze server operations to determine the root cause of slow performance
Identify slowest client-side operations
Analyze details of page views using query language
public async static Task<SqlDataReader> ExecuteReaderWithRetryAsync(this SqlCommand command)
{
GuardConnectionIsNotNull(command);
var policy = Policy.Handle<Exception>().WaitAndRetryAsync(
retryCount: 3, // Retry 3 times
sleepDurationProvider: attempt => TimeSpan.FromMilliseconds(200 * Math.Pow(2, attempt - 1)), // Exponential backoff based on an initial 200 ms delay.
onRetry: (exception, attempt) =>
{
// Capture some information for logging/telemetry.
logger.LogWarn($"ExecuteReaderWithRetryAsync: Retry {attempt} due to {exception}.");
});
// Retry the following call according to the policy.
await policy.ExecuteAsync<SqlDataReader>(async token =>
{
// This code is executed within the Policy
if (conn.State != System.Data.ConnectionState.Open) await conn.OpenAsync(token);
return await command.ExecuteReaderAsync(System.Data.CommandBehavior.Default, token);
}, cancellationToken);
}
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A (35%)
C (25%)
B (20%)
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