AZ-204 Monitor, troubleshoot, and optimize Azure solutions — 50 Questions

Question 1

You have an App Service app that uses Azure SQL Database. Users report that some queries are slow. You need to monitor query performance and receive alerts when the average query duration exceeds 1 second. Which two Azure services should you use?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Azure Monitor Alerts. Application Insights (D) provides built-in SQL dependency tracking for your App Service app, enabling you to monitor individual query durations and collect metrics like average query duration. Azure Monitor Alerts (B) is then used to configure and receive alerts based on these metrics collected by Application Insights. When the average query duration (from Application Insights) exceeds 1 second, Azure Monitor Alerts will trigger, fulfilling both the monitoring and alerting requirements using two distinct Azure services.

Answer

Azure Advisor

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Azure Monitor Logs

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Azure SQL Analytics

Question 2

You have an Azure Front Door Premium instance with a Web Application Firewall (WAF) policy. The exhibit shows a custom rule. What is the effect of this rule?

Accepted Answer

Blocks traffic that does NOT originate from 192.168.1.0/24 or 10.0.0.0/8. The rule blocks requests that do NOT originate from the specified IP ranges (negateCondition: true). Option A is wrong because it allows all traffic. Option B is wrong because it blocks only those IPs. Option D states that traffic from the specified IPs is allowed. While this is the net outcome, the rule itself is configured to *block* traffic that *does not* match the specified IPs (due to 'action: Block' and 'negateCondition: true'). Option C directly describes this blocking mechanism.

Answer

Allows all traffic

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Blocks traffic from 192.168.1.0/24 and 10.0.0.0/8

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Allows traffic from 192.168.1.0/24 and 10.0.0.0/8

Question 3

You have an Azure Policy as shown in the exhibit. The roleDefinitionId corresponds to the 'Contributor' role. What does this policy do?

Accepted Answer

Denies Contributors from creating or modifying virtual machines. The premise of the policy as described is flawed. Azure Policy evaluates conditions based on the resource properties and request context, but it does not have a direct field or alias to check the 'roleDefinitionId' of the user performing the action for resource operations. Therefore, a policy cannot be constructed to selectively deny virtual machine creation/modification *only* for users with the Contributor role based on their 'roleDefinitionId' in the policy's 'if' condition. Preventing Contributors from creating VMs is typically handled by not assigning them the Contributor role, or by assigning a custom role with more restrictive permissions. If the intent was to deny *all* VM creation/modification, the policy would simply target 'Microsoft.Compute/virtualMachines' with a 'deny' effect, without a condition on 'roleDefinitionId'.

Answer

Allows Contributors to create virtual machines

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Audits when Contributors create virtual machines

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Deploys a virtual machine when a Contributor action occurs

Question 4

Which TWO actions should you take to optimize costs for an Azure SQL Database that is underutilized? (Choose two.)

Accepted Answer

Purchase reserved capacity. Purchasing reserved capacity for Azure SQL Database allows you to commit to a one- or three-year term, which provides a significant discount (up to 40-60%) compared to pay-as-you-go pricing. This is a cost optimization strategy for a database that is underutilized because you are already paying for the current service tier and can reduce the per-unit cost without changing the performance level. Scaling down to a lower service tier (or a lower DTU/vCore configuration within the same tier) directly addresses underutilization by reducing the provisioned capacity to better match actual usage. Since you pay for the provisioned capacity, reducing it when it's not fully utilized leads to immediate cost savings.

Answer

Enable geo-replication

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Increase the DTU or vCore limit

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Enable read scale-out

Question 5

Which THREE metrics should you monitor to determine if an Azure Kubernetes Service (AKS) cluster is running optimally? (Choose three.)

Accepted Answer

Node CPU usage percentage. Node CPU usage percentage (A) is a critical metric because sustained high CPU usage on nodes indicates resource contention, which can degrade pod performance and trigger the kubelet to evict pods. Monitoring this helps ensure the cluster has sufficient compute capacity and that horizontal pod autoscalers or node autoscalers are configured correctly. Similarly, Pod memory usage percentage (E) is vital as high memory consumption can lead to Out-Of-Memory (OOM) errors, pod evictions, and application crashes, directly impacting workload stability and performance. Finally, Disk I/O throughput (D) is crucial for applications that are disk-intensive. Poor disk performance can create bottlenecks, slowing down data processing and overall application responsiveness, even if CPU and memory resources appear sufficient. Together, these three metrics provide a comprehensive view of the cluster's resource health and workload performance.

Answer

API server request latency

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Network bytes sent and received

Question 6

Which TWO approaches can help you optimize the cost of Azure Storage accounts that store infrequently accessed data? (Choose two.)

Accepted Answer

Use Cool or Archive storage tier. Cool and Archive storage tiers are specifically designed for infrequently accessed data, offering significantly lower storage costs compared to the Hot tier. Cool tier is optimized for data accessed less than once per month, while Archive tier is for data that is rarely accessed and has a retrieval latency of several hours, making them cost-effective choices. Azure Blob Storage lifecycle management allows you to automate the transition of blobs between these tiers (e.g., from Hot to Cool, then to Archive) based on rules like age or last access time, ensuring that data is always stored in the most cost-effective tier for its current access pattern, thereby optimizing costs over time.

Answer

Use Premium storage tier

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Enable geo-redundant storage (RA-GRS)

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Enable Azure Storage encryption

Question 7

You are optimizing an Azure SQL Database that runs a heavy reporting workload. Queries are slow due to high logical reads. Which index strategy should you recommend?

Accepted Answer

Use columnstore indexes on fact tables. High logical reads in a heavy reporting workload are often best addressed by columnstore indexes. Columnstore indexes provide significant data compression, reducing the number of pages that need to be read from disk. They also enable batch mode processing and segment elimination, which dramatically improve performance for analytical queries involving large scans and aggregations, thereby directly reducing logical reads across the workload.

Answer

Create nonclustered indexes with included columns

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Disable auto-update statistics

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Rebuild clustered indexes with higher fill factor

Question 8

Which THREE actions should you take to optimize cost for an Azure Functions app that processes messages from a queue?

Accepted Answer

Use Consumption plan instead of Premium. The three actions that optimize cost are: A) Consumption plan charges per execution and scales to zero when idle, minimizing cost for variable workloads. B) Batch processing reduces the number of function executions by processing multiple messages in a single invocation, lowering total execution count. C) If a Premium plan is chosen, configuring auto-scale to reduce instances during off-peak periods minimizes costs by avoiding payment for *unnecessary* fixed capacity, though a base cost for minimum instances still applies. Options D (Always On) keeps the app running continuously, increasing cost. Option E (increased timeout) does not reduce cost; it may increase costs by allowing longer running executions.

Answer

Enable Always On to keep the app warm

Answer

Increase function timeout to reduce retries

Question 9

You are troubleshooting a slow web application hosted on Azure App Service. The application uses Azure SQL Database. You suspect that the database queries are taking too long. Which Azure Monitor feature should you use to identify slow queries?

Accepted Answer

Azure SQL Insights. Azure SQL Insights (part of Azure Monitor) is the correct choice because it provides dedicated monitoring for Azure SQL Database. It uses Log Analytics workspaces and offers prebuilt dashboards showing query performance, wait statistics, and resource utilization to identify slow-running or resource-intensive queries.

Answer

Azure Activity Log

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Azure Advisor

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Azure Monitor Metrics

Question 10

Which THREE features of Azure Monitor can help you diagnose a performance issue in an Azure Virtual Machine?

Accepted Answer

Log Analytics workspace queries. Log Analytics workspace queries (A) allow you to analyze performance data collected from Azure VMs, such as CPU, memory, and disk metrics, using Kusto Query Language (KQL) to identify trends, anomalies, or bottlenecks. VM Insights (B) is a feature within Azure Monitor specifically designed to provide a consolidated view of VM performance, health, and dependencies, leveraging Log Analytics for data. Diagnostic settings (E) are crucial as they enable the configuration of VMs to send performance counters directly to a Log Analytics workspace, making the data available for analysis by queries and VM Insights. These three features are core to diagnosing VM performance issues within Azure Monitor.

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Azure Network Watcher

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Azure Backup reports

Question 11

You are monitoring an Azure App Service web app that is experiencing intermittent high CPU usage. You need to configure alerts and troubleshoot the issue. Which TWO actions should you take? (Choose two.)

Accepted Answer

Create a metric alert rule that triggers when average CPU exceeds 90% over 5 minutes.. Configuring diagnostic settings to send platform logs to a Log Analytics workspace allows you to analyze detailed logs (e.g., HTTP requests, errors, and performance counters) to identify the root cause of intermittent high CPU usage. This is a standard troubleshooting step for Azure App Service, as it provides historical and real-time data beyond simple metrics.

Answer

Scale up the App Service plan to a higher tier to ensure sufficient resources.

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Enable Application Insights and configure autoscale based on custom metrics.

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Create an autoscale rule for the App Service plan to scale out when CPU > 80%.

Question 12

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.

Answer

Fixed-rate sampling with a 1% rate

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Ingestion sampling

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Head-based sampling

Question 13

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.

Answer

Logs

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Alerts

Answer

Workbooks

Question 14

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.

Answer

Live Metrics.

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Snapshot Debugger.

Answer

Availability tests.

Question 15

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.

Answer

Event Hubs metrics.

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Stream Analytics job.

Answer

Log Analytics query on function logs.

Question 16

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.

Answer

Fixed-rate sampling

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Ingestion sampling

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Head-based sampling

Question 17

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%.

Answer

Log Analytics Workspace

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Application Insights

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Azure Monitor for VMs

Question 18

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.

Answer

Metrics Explorer

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Live Metrics Stream

Answer

Smart Detection

Question 19

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 captures memory dumps (snapshots) of a production web app when an exception occurs or when configured to trigger on specific conditions, such as high memory usage, without restarting the app. It is specifically designed for debugging memory leaks and high CPU/memory issues in Azure App Service by providing detailed snapshots of the process state, including the heap, at the point of interest. While not strictly time-based periodic, if the high memory condition occurs repeatedly, the debugger can be configured to capture multiple snapshots over time for analysis.

Answer

Application Insights Profiler

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Diagnostic Settings

Answer

Auto-healing

Question 20

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.

Answer

SQL

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PowerShell

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Azure CLI