Question 440 of 881
AZ-204 Practice Question: Monitor, troubleshoot, and optimize Azure solutions
You are monitoring a web application with Application Insights. The application occasionally returns HTTP 500 errors. You want to be notified immediately when the error rate exceeds 5% of all requests in a rolling 5-minute window. Which feature of Application Insights should you configure?
⚠ Common exam trap
Test-takers frequently confuse metric alerts (which work on absolute counts or rates) with log alerts (which can compute custom ratios like percentages), leading them to choose Option B without realizing that the 'Failed requests' metric cannot be configured to alert on a percentage threshold.
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
✓
Create a log alert using a Kusto query that calculates the percentage of failed requests over the last 5 minutes, with an alert condition when the result exceeds 0.05.
A log alert using a Kusto query allows you to calculate the exact percentage of failed requests over a rolling 5-minute window and trigger when that percentage exceeds 0.05 (5%). This is the only option that supports a dynamic, percentage-based threshold on a rolling time window, which is required for the stated condition. Metric alerts on 'Failed requests' measure absolute counts, not percentages, and Smart Detection does not allow custom percentage thresholds.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create a Smart Detection rule for anomalous failures.
Why it's wrong here
Smart Detection leverages machine learning to automatically establish a baseline of normal application behavior and then identifies statistically significant deviations or anomalies in failure rates. While it excels at alerting on unusual spikes or drops, it is not designed to be configured with a specific, fixed percentage threshold like 5%. Its purpose is adaptive anomaly detection rather than static threshold monitoring.
- ✗
Create a metric alert on the 'Failed requests' metric with a threshold of 5%.
Why it's wrong here
A standard metric alert in Azure Monitor operates directly on pre-aggregated metrics, such as the absolute count of failed requests or the total number of requests. It lacks the inherent capability to perform complex calculations or aggregations across multiple distinct metrics to derive a ratio, such as the percentage of failed requests. Therefore, you cannot directly set a threshold on a calculated percentage using a simple metric alert.
- ✓
Create a log alert using a Kusto query that calculates the percentage of failed requests over the last 5 minutes, with an alert condition when the result exceeds 0.05.
Why this is correct
Log alerts allow complex queries. For example: 'requests | where timestamp > ago(5m) | summarize total=count(), failures=countif(success == false) | extend percent = failures * 100.0 / total | where percent > 5'. This triggers an alert when the condition is met.
- ✗
Create an availability test that checks for HTTP 200 responses and alert on failures.
Why it's wrong here
Availability tests, including URL ping tests or multi-step web tests, are designed to proactively monitor the external reachability and responsiveness of a web application from various geographic locations. While they can detect if a synthetic probe receives a non-200 HTTP status code, they only measure the success or failure of their own external checks. These tests do not analyze or report on the percentage of failed requests occurring from actual user traffic within the application itself.
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Last reviewed: Jun 11, 2026
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