AZ-204 Monitor, troubleshoot, and optimize Azure solutions — Timed 10 Questions

Question 1

An e-commerce application emits a high volume of telemetry data to Azure Application Insights. You need to reduce the cost of data ingestion while preserving statistical accuracy for performance metrics. Which sampling technique should you use?

Accepted Answer

Adaptive sampling. Adaptive sampling is the correct choice because it automatically adjusts the sampling rate based on the volume of telemetry data, ensuring that during low-traffic periods all data is retained for statistical accuracy, while during high-traffic periods it reduces the rate to control costs. This technique is specifically designed for high-volume scenarios like e-commerce telemetry, where preserving statistical accuracy for performance metrics (e.g., request durations, failure rates) is critical, and it avoids the manual tuning required by fixed-rate sampling.

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Fixed-rate sampling with a 1% rate

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Ingestion sampling

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Head-based sampling

Question 2

You need to monitor the real-time CPU utilization of an Azure virtual machine. Which Azure Monitor feature is designed for this purpose?

Accepted Answer

Metrics. Azure Monitor Metrics is the correct feature because it collects and stores numeric time-series data from Azure resources, including CPU utilization, at near-real-time intervals (typically every 1 minute for Azure VMs). Metrics are lightweight, low-latency, and designed for real-time monitoring and alerting, making them ideal for tracking CPU usage without the overhead of log ingestion.

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Logs

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Alerts

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Workbooks

Question 3

You have an Azure App Service web app that experiences intermittent slowness. You enable Application Insights and notice that the "Failed Requests" metric is low, but "Server Response Time" is high for a subset of requests. You want to identify the specific code path causing the delay. Which feature should you use?

Accepted Answer

Profiler.. C is correct because the Application Insights Profiler captures detailed call stacks and execution timing for slow requests, allowing you to pinpoint the exact code path causing high server response time. Unlike other features, Profiler is specifically designed for performance troubleshooting by tracing request execution at the code level.

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Live Metrics.

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Snapshot Debugger.

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Availability tests.

Question 4

An Azure Function processes events from Event Hubs. You need to monitor the number of events that were successfully processed and those that were dropped due to processing errors. Which approach should you use?

Accepted Answer

Custom metrics in Application Insights.. Custom metrics in Application Insights allow you to track business-specific counters like successfully processed events and dropped events directly from your Azure Function code. By using the `TelemetryClient.TrackMetric()` API within the function's event processing logic, you can increment counters for success and failure scenarios, giving you precise, real-time monitoring of processing outcomes. This approach is more granular than built-in metrics because it reflects your application's custom error handling, not just infrastructure-level throughput.

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Event Hubs metrics.

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Stream Analytics job.

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Log Analytics query on function logs.

Question 5

Your e-commerce application sends telemetry to Application Insights. You need to reduce ingestion costs while preserving the ability to detect trends in performance metrics. Which sampling type should you configure?

Accepted Answer

Adaptive sampling. Adaptive sampling is the correct choice because it automatically adjusts the volume of telemetry data collected based on the application's activity level, ensuring that performance trends are preserved while reducing ingestion costs. Unlike fixed-rate sampling, adaptive sampling dynamically increases or decreases the sampling rate to maintain a target volume, making it ideal for e-commerce applications with variable traffic patterns.

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Fixed-rate sampling

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Ingestion sampling

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Head-based sampling

Question 6

You need to monitor the CPU utilization of an Azure VM in real-time and set up an alert when it exceeds 90%. Which Azure Monitor feature should you use?

Accepted Answer

Metrics Explorer. Metrics Explorer is the correct Azure Monitor feature for real-time monitoring of CPU utilization on an Azure VM because it provides near real-time metric collection (typically every 1 minute) and supports alerting based on threshold conditions. It allows you to chart performance counters like Percentage CPU and configure metric alerts that trigger when the value exceeds 90%.

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Log Analytics Workspace

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Application Insights

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Azure Monitor for VMs

Question 7

You need to diagnose a slow-performing Azure Function. Application Insights shows that the function's dependency calls to an external API take an unusually long time. Which Application Insights feature should you use to visualize the end-to-end request flow?

Accepted Answer

Application Map. Application Map is the correct feature because it provides a visual representation of the end-to-end request flow across distributed components, including dependency calls to external APIs. It shows the latency and failure rates for each dependency, allowing you to pinpoint where the slowdown occurs in the overall transaction.

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Metrics Explorer

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Live Metrics Stream

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Smart Detection

Question 8

An Azure web app is experiencing high memory usage. You want to collect memory dumps periodically to analyze the issue without restarting the app. Which Azure App Service diagnostic feature should you use?

Accepted Answer

Application Snapshot Debugger. The Application Snapshot Debugger is the correct feature because it captures memory dumps (snapshots) of a production web app at the point of an exception or high memory usage without restarting the app. It is specifically designed for debugging memory leaks and high CPU/memory issues in Azure App Service, providing a periodic snapshot of the process heap.

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Application Insights Profiler

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Diagnostic Settings

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Auto-healing

Question 9

An application uses Azure Application Insights for monitoring. You need to write a query to analyze the number of failed requests and exceptions over the past hour. Which query language should you use?

Accepted Answer

Kusto Query Language (KQL). Azure Application Insights stores telemetry data in a Log Analytics workspace, which is queried using Kusto Query Language (KQL). KQL is the native query language for Azure Data Explorer and is specifically designed for time-series analysis, filtering, and aggregation of log data. To analyze failed requests and exceptions over the past hour, you would use KQL operators like `where`, `summarize`, and `bin` to filter by timestamp and count events.

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SQL

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PowerShell

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Azure CLI

Question 10

Your web app hosted on Azure App Service is experiencing high memory usage. You need to capture a memory dump for analysis without restarting the app. Which diagnostic feature should you use?

Accepted Answer

Azure App Service Diagnostics (Diagnose and solve problems). Azure App Service Diagnostics (Diagnose and solve problems) provides a built-in 'Memory Dump' tool that allows you to capture a full or mini memory dump of your app's process without requiring a restart. This is accessed through the Azure portal under the 'Diagnose and solve problems' blade, specifically via the 'Collect Memory Dump' diagnostic tool, which uses the Windows Debugging Tools to snapshot the w3wp.exe process while the app continues running.

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Application Insights Profiler

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Snapshot Debugger

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Diagnostic settings