AZ-204 Practice Question: Monitor, troubleshoot, and optimize Azure solutions
You have a web application monitored by Application Insights. You want to receive an alert when the average server response time exceeds 2 seconds for a rolling 5-minute period. Which alert rule type should you create?
⚠ Common exam trap
Watch out — candidates often confuse metric alerts (which evaluate pre-aggregated performance counters in near-real-time) with log alerts (which require querying raw telemetry data and have higher latency), leading candidates to incorrectly choose the log-based option for a simple threshold-based metric condition.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Application Insights metric alert on 'Server response time' with condition 'Greater than 2' and evaluation frequency 5 minutes
A metric alert on 'Server response time' is the correct choice because it continuously evaluates the average server response time over a rolling 5-minute window and triggers when the value exceeds 2 seconds. Metric alerts are designed for near-real-time monitoring of performance counters like response time, with a fixed evaluation frequency that matches the aggregation window, making them ideal for this scenario.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Application Insights metric alert on 'Server response time' with condition 'Greater than 2' and evaluation frequency 5 minutes
Why this is correct
This option correctly identifies the most appropriate monitoring tool for the requirement. An Application Insights metric alert on 'Server response time' directly monitors the average duration of server-side request processing, which is a standard metric collected by the Application Insights SDK. Setting a condition 'Greater than 2' with a 5-minute evaluation frequency ensures that an alert will fire efficiently when the average response time consistently exceeds 2 seconds over that period, precisely matching the scenario's need for threshold-based monitoring.
- ✗
Log alert based on a Kusto query that measures average response time in 5-minute windows
Why it's wrong here
A log alert based on a Kusto query is incorrect for this scenario because average server response time is a standard metric natively collected by Application Insights. Metric alerts are specifically designed to efficiently monitor such pre-aggregated metrics over rolling time windows, which precisely matches the requirement. This option is tempting due to Kusto's powerful analytical capabilities, making it the correct choice when the alert condition requires analysing custom log properties, correlating data across multiple log types, or performing complex calculations not available as standard metrics.
- ✗
Smart Detection alert on response time degradation
Why it's wrong here
Smart Detection is an AI-driven feature designed to identify unusual patterns and sudden degradations in application performance by establishing a dynamic baseline of normal behavior. It alerts on anomalies and deviations from this learned baseline, rather than monitoring against a fixed, static threshold. Therefore, it would not reliably trigger an alert for a consistent response time exceeding a specific 2-second limit if that value falls within its learned 'normal' operating range or if the degradation is gradual and not considered anomalous.
- ✗
Availability test alert for HTTP response time
Why it's wrong here
Availability tests, also known as web tests, are synthetic monitoring tools that simulate user traffic from various global locations to check the uptime and performance of a web application's external endpoints. While they measure response time, this measurement reflects the performance of a synthetic transaction from a specific test location, not the actual server response time experienced by real users interacting with the application. The question specifically asks to monitor the web application's server response time, implying real user traffic, which is captured by the Application Insights SDK.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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