AZ-400 · Domain 5: Implement an instrumentation strategy · 7% of the exam
Task 5.2: Analyze metrics from instrumentation
Reading CPU, memory, disk and network indicators, usage and application performance, distributed traces in Application Insights, and basic KQL queries over logs.
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Analyzing telemetry: infrastructure indicators, usage, distributed traces and KQL
Try each one before opening the answer. Every option is explained, with the Microsoft documentation page that proves it.
Question 1 · choose 1
You need a chart of failed requests per 5-minute interval over the last 24 hours from the Application Insights requests table, where failed requests have success equal to false. Which query produces the counts for that chart?
Arequests | where success == false | take 288
Brequests | where timestamp > ago(24h) and success == false | summarize count() by bin(timestamp, 5m)
Crequests | summarize count() by success | where timestamp > ago(24h)
Drequests | where timestamp > ago(5m) and success == false | count
Show the answer and why
Arequests | where success == false | take 288
Incorrect
That returns rows, not a count per interval.
Brequests | where timestamp > ago(24h) and success == false | summarize count() by bin(timestamp, 5m)
Correct
It filters to the last day's failures, then counts rows in 5-minute bins.
Crequests | summarize count() by success | where timestamp > ago(24h)
Incorrect
After summarize, timestamp no longer exists, and nothing is binned by time.
Drequests | where timestamp > ago(5m) and success == false | count
Incorrect
That counts failures in the last five minutes only.
where filters rows, ago() gives a time relative to now, and summarize count() by bin(timestamp, 5m) groups rows into 5-minute buckets and counts them.
Checkout requests sometimes fail after passing through a front-end API, an orders service and a payments service, each sending telemetry to Application Insights. You need to see, for one failed request, every call it made across the services and which dependency failed. What should you use?
AThe end-to-end transaction details from the Failures view
BUsage funnels for the checkout steps
CThe VM performance charts of the hosts
DLive metrics, watched while waiting for the next failure to happen
Show the answer and why
AThe end-to-end transaction details from the Failures view
Correct
Transaction diagnostics shows the correlated calls of one operation across components, with dependencies and exceptions.
BUsage funnels for the checkout steps
Incorrect
Funnels show where users drop off, not the calls in one request.
CThe VM performance charts of the hosts
Incorrect
Host charts show resource load, not one request's path.
DLive metrics, watched while waiting for the next failure to happen
Incorrect
It doesn't show the call tree of a request that already failed.
Application Insights correlates telemetry for an operation across components. From the Failures or Performance views you can drill into end-to-end transaction details, which show dependencies and exceptions for the operation, to find the root cause.
A chart of errors per hour skips hours with no errors, so the line jumps between gaps. Which operator builds a series with a value for every hour, using 0 where there were no rows?
Amake-series
Btake
Cproject-away
Dparse
Show the answer and why
Amake-series
Correct
make-series assigns a default value, 0 unless set, to bins with no rows.
Btake
Incorrect
take returns rows; it doesn't build a series.
Cproject-away
Incorrect
project-away removes columns.
Dparse
Incorrect
parse extracts values from strings.
make-series creates a series of aggregated values along an axis such as time; where there's no row for a bin, the array gets the default value, which is 0 unless you set another.
A new engineer needs a picture of which services call which, with failure rates and latency on each call, from Application Insights. What should she open?
AApplication map
BUsage cohorts
CAvailability tests
DSmart detection
Show the answer and why
AApplication map
Correct
It shows components and dependencies with performance and failure data.
BUsage cohorts
Incorrect
Cohorts group users.
CAvailability tests
Incorrect
These probe endpoints from outside.
DSmart detection
Incorrect
That reports anomalies.
Application map shows the components of a distributed application and their dependencies, helping you spot performance bottlenecks and failure hotspots across components.
You need the number of distinct users per day from pageViews over the last week. Which aggregation fits?
Acount() by bin(timestamp, 1d)
Bdcount(user_Id) by bin(timestamp, 1d)
Ccountif(user_Id != "") by bin(timestamp, 1d)
Dmax(user_Id)
Show the answer and why
Acount() by bin(timestamp, 1d)
Incorrect
count() counts page views, not distinct users.
Bdcount(user_Id) by bin(timestamp, 1d)
Correct
dcount estimates the number of distinct values per group.
Ccountif(user_Id != "") by bin(timestamp, 1d)
Incorrect
countif counts matching rows, not distinct users.
Dmax(user_Id)
Incorrect
max returns one value, not a count.
dcount() estimates the number of distinct values in a group, such as unique users per day; count() counts rows and countif() counts rows that match a condition.