Microsoft DevOps Engineer Expert AZ-400 Practice Question
You run load tests against an Azure App Service that is instrumented with Application Insights. During the test, the /api/checkout operation occasionally exceeds its 5-second SLA. You need to determine whether the excessive latency originates inside the app or inside a downstream dependency. Which Kusto Query Language (KQL) statement should you run in Log Analytics to generate a time-series chart that shows the average request duration together with the average duration of related dependency calls for the same operation?
traces | where message contains '/api/checkout' | summarize avg(duration) by bin(timestamp, 1m)
requests | where name == '/api/checkout' | summarize avg(duration) by bin(timestamp, 1m)
requests | where name == '/api/checkout' | project operation_Id, requestDuration = duration, timestamp | join kind=inner ( dependencies | project operation_Id, dependencyDuration = duration ) on operation_Id | summarize avg(requestDuration), avg(dependencyDuration) by bin(timestamp, 1m)
dependencies | where target contains '/api/checkout' | summarize avg(duration) by bin(timestamp, 1m)
The requests and dependencies tables store data for incoming requests and outgoing calls, respectively. Both tables share the same correlation identifier, operation_Id, which enables end-to-end analysis of a single transaction. By projecting the identifier from each table and performing an inner join on operation_Id, you can correlate each /api/checkout request with its dependency calls. After the join, summarizing the two duration columns over a time bin produces a single chart that compares the average server processing time (requestDuration) with the average time spent in external calls (dependencyDuration). Queries that look only at requests or only at dependencies-or that filter on the wrong column-cannot expose which side contributes more to the total latency.
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Microsoft DevOps Engineer Expert AZ-400
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