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AZ-204 Practice Question: Monitor, troubleshoot, and optimize Azure solutions

You are using Application Insights to monitor a web application. You need to create an alert that triggers when the server response time exceeds 5 seconds for more than 10% of requests in a 5-minute window. Which type of Azure Monitor alert should you create?

⚠ Common exam trap

Candidates often assume a metric alert can handle percentage-based conditions, but metric alerts only support simple aggregations (e.g., average, count, max) and cannot compute a ratio of requests meeting a custom condition without a log query.

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

Log alert

A log alert is correct because the condition involves querying Application Insights trace data to calculate the percentage of requests with a server response time exceeding 5 seconds within a 5-minute window. Log alerts run a Kusto query against the `requests` table, allowing aggregation and threshold evaluation (e.g., >10% of requests), which is not possible with simple metric 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.

  • Metric alert

    Why it's wrong here

    Metric alerts are designed to monitor specific, pre-aggregated time-series data points like CPU usage or request count. While they can track individual metrics, they lack the native capability to perform complex, real-time calculations such as dividing the count of requests exceeding a duration threshold by the total request count within a single alert rule. This makes them unsuitable for directly computing and alerting on a dynamic percentage ratio.

  • Log alert

    Why this is correct

    Log alerts leverage Kusto Query Language (KQL) to execute custom queries against your Application Insights logs. This powerful capability allows you to filter requests by duration, count them, and then calculate the precise percentage of requests exceeding a specific threshold (e.g., 5000 ms) relative to the total requests within the evaluation period. The alert then triggers when this calculated percentage surpasses the defined custom threshold, making it ideal for complex, ratio-based performance monitoring.

  • Activity log alert

    Why it's wrong here

    Activity log alerts are specifically designed to monitor events occurring at the Azure resource level, such as resource creation, deletion, updates, or security-related actions. They operate on the Azure Activity Log, which records control plane operations, not data plane metrics like application performance. Therefore, they cannot be used to track or alert on application-specific performance metrics like request duration or error rates within a web application.

  • Application Insights smart detection alert

    Why it's wrong here

    Application Insights smart detection automatically uses machine learning algorithms to identify unusual patterns, performance degradations, or failure anomalies in your application's telemetry data without requiring manual configuration. While it provides valuable insights into potential issues, it does not allow users to define custom, static thresholds for specific metrics or ratios, such as a precise percentage of slow requests. Its purpose is anomaly detection, not custom threshold-based alerting.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AZ-204 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AZ-204 exam.