AZ-204 Monitor, troubleshoot, and optimize Azure solutions Practice Test 6 — 15 Questions

Question 1

You are developing a web app that experiences intermittent slow responses. You enable Application Insights and notice that the server-side request duration is normally under 200ms, but some requests take over 5 seconds. Which diagnostic tool should you use to identify the root cause?

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

Accepted Answer

Application Insights Profiler. The Application Insights Profiler is the correct tool because it provides a flame chart of per-request CPU and wall-clock time, allowing you to identify which code path is causing the 5-second latency. Unlike other tools, the Profiler captures detailed execution traces for slow requests, pinpointing the exact method or dependency that is blocking the thread.

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Availability Tests

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Snapshot Debugger

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Live Metrics Stream

Question 2

You are deploying a microservices application on Azure Kubernetes Service (AKS). You need to monitor the resource consumption of each pod and set up alerts when CPU usage exceeds 80% for 5 minutes. What should you use?

Accepted Answer

Azure Monitor Container Insights. Azure Monitor Container Insights is the correct choice because it is specifically designed to monitor the performance of container workloads running on Azure Kubernetes Service (AKS). It collects memory and processor metrics from controllers, nodes, and containers, and supports setting metric alerts based on CPU usage thresholds, such as 80% for 5 minutes.

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Azure Monitor VM Insights

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Application Insights

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Azure Service Health

Question 3

You have an Azure Function app that processes messages from a Service Bus queue. Under high load, some messages are not processed within the expected time. You need to identify whether the function is throttling due to high CPU or due to a downstream dependency. Which Application Insights feature should you use?

Accepted Answer

Application Map. Application Map is the correct choice because it provides a visual representation of the dependencies and telemetry flow across your distributed application. By examining the Application Map, you can see the health and performance of downstream dependencies (e.g., databases, external APIs) and correlate any slowdowns or failures with the function's processing time, helping you determine if the bottleneck is due to a dependency rather than CPU throttling.

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Live Metrics Stream

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Application Insights Profiler

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Search

Question 4

You are optimizing an Azure API Management instance that handles 10,000 requests per second. You notice that caching is not effective. The cache hit ratio is below 10%. You need to increase the cache hit ratio. What should you do?

Accepted Answer

Configure cache key to include only relevant query parameters. The low cache hit ratio indicates that cache keys are too specific, causing each request to miss the cache. By configuring the cache key to include only relevant query parameters, you group similar requests under the same cache key, increasing the likelihood of cache hits. This directly addresses the root cause of poor cache utilization in Azure API Management.

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Use external Azure Cache for Redis

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Disable caching for low-traffic APIs

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Increase the cache size to 5 GB

Question 5

You have an Azure Logic App that processes orders. Occasionally, the Logic App fails due to a transient error from a downstream API. You want to automatically retry the failed action after 10 seconds, up to 3 times, with exponential backoff. Which configuration should you set on the action?

Accepted Answer

Set retry policy to default with interval of 10 seconds and count of 3. The default retry policy in Azure Logic Apps uses exponential backoff, which automatically increases the delay between retries. Setting the interval to 10 seconds and count to 3 configures the initial delay and maximum retry attempts, while the exponential backoff behavior is inherent to the default policy. This matches the requirement to retry after 10 seconds initially, up to 3 times, with exponential backoff.

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Set retry policy to fixed interval with 10-second delay and 3 retries

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Set retry policy to none and implement custom retry logic

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Set retry policy to custom with exponential interval and 3 retries

Question 6

You have an Azure Cosmos DB container with a high number of physical partitions. You observe that some partitions are hitting the request unit (RU) limit while others are underutilized. What should you do to better distribute the workload?

Accepted Answer

Choose a different partition key that evenly distributes workload. The root cause of uneven RU consumption is a poorly chosen partition key that creates a hot partition. By selecting a partition key with high cardinality and even distribution, you ensure that requests and storage are spread uniformly across all physical partitions, preventing any single partition from throttling while others remain idle.

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Add more composite indexes

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Increase the total provisioned throughput

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Change the default consistency level to eventual

Question 7

You are troubleshooting an Azure App Service that runs a Node.js application. The application returns HTTP 500 errors intermittently. Application Insights is configured. Which telemetry item should you examine first to find the root cause?

Accepted Answer

Exceptions. HTTP 500 errors indicate server-side failures, and Application Insights captures these as Exception telemetry when an unhandled exception occurs in the Node.js runtime. Examining the Exception telemetry first allows you to see the stack trace, error message, and call details, which directly point to the root cause of the intermittent failures.

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Traces

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Dependencies

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Requests

Question 8

You query Application Insights with the KQL query in the exhibit. The chart shows a spike in 500 errors at 2:00 PM. What is the next step to diagnose the cause?

Accepted Answer

Query exceptions and traces for the 2:00 PM hour. When a spike in 500 errors is detected in Application Insights, the next logical step is to query exceptions and traces for the specific time period (2:00 PM). This allows you to correlate the error count with detailed exception messages, stack traces, and dependency calls, which directly reveal the root cause of the failures. KQL queries like `exceptions | where timestamp between (datetime(14:00) .. datetime(15:00))` or joining with `traces` provide the granular data needed for diagnosis.

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Check availability tests for the same period

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Scale up the App Service plan

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Run a profiler on the 2:00 PM time range

Question 9

You have an Azure Function app that uses Durable Functions. You notice that some orchestrations are taking longer than expected. You need to monitor the history of orchestration instances. What should you use?

Accepted Answer

Durable Functions HTTP management APIs. D is correct because the Durable Functions HTTP management APIs provide direct access to the orchestration instance history, including status queries, raise events, and terminate operations. These APIs return the full execution history of an orchestration instance, allowing you to inspect each step and identify delays. This is the most targeted way to monitor the history of specific orchestration instances without additional configuration.

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Application Insights

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Azure Monitor Metrics

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Azure Storage Explorer

Question 10

You are using Azure Monitor to collect logs from multiple Azure resources. You need to query logs to find all error events from the last 24 hours. Which query language should you use?

Accepted Answer

Kusto Query Language (KQL). Azure Monitor uses Kusto Query Language (KQL) as its native query language for log analytics. KQL is specifically designed for querying large volumes of structured and semi-structured data in Azure Data Explorer and Log Analytics workspaces, making it the correct choice for retrieving error events from the last 24 hours.

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Transact-SQL (T-SQL)

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PromQL

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PowerShell

Question 11

You have an Azure CDN profile that caches content from a storage account. Users in Europe report that images load slowly. You need to improve performance for European users. What should you do?

Accepted Answer

Add an additional CDN endpoint with a European origin. Adding an additional CDN endpoint with a European origin (e.g., an Azure Storage account in a European region) reduces latency by serving content from a geographically closer point of presence (PoP). Azure CDN uses a global network of edge servers, but if the origin server is far from the users, the first-hop latency from the edge to the origin can still be high. By placing an origin in Europe, the CDN can fetch content from a nearby origin, minimizing the distance data must travel and improving load times for European users.

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Enable compression on the CDN

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Enable prefetching on the CDN

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Configure caching rules to cache longer

Question 12

You are monitoring an Azure App Service using Application Insights. You want to alert when the average server response time exceeds 2 seconds over a 5-minute window. What should you create?

Accepted Answer

A metric alert with 'Server response time' as the signal. A metric alert is the correct choice because 'Server response time' is a pre-aggregated performance metric emitted by Azure App Service to Application Insights. Metric alerts evaluate this signal against a static threshold (e.g., >2 seconds) over a specified time window (e.g., 5 minutes) without needing custom queries, making them ideal for simple threshold-based monitoring of latency.

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An availability alert

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A log alert with a custom KQL query

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An activity log alert

Question 13

Which TWO actions can help you reduce latency for a globally distributed web application? (Choose two.)

Accepted Answer

Use Azure Traffic Manager with performance routing. Azure Traffic Manager with performance routing directs user traffic to the closest endpoint based on the lowest network latency, reducing response times for globally distributed users. Option E is correct because Azure Front Door uses anycast and global edge points of presence (PoPs) to route traffic to the nearest region, providing both latency reduction and application acceleration.

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Use Azure Application Gateway with Web Application Firewall

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Scale up the App Service plan to a higher tier

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Enable multi-region writes on Azure Cosmos DB

Question 14

Which THREE tools can you use to diagnose performance issues in an Azure App Service? (Choose three.)

Accepted Answer

Application Insights. Application Insights is a feature of Azure Monitor that provides application performance management (APM) and telemetry for live web applications. It automatically detects performance anomalies, includes powerful analytics tools to help diagnose issues, and allows you to understand how an app is performing and being used. For an Azure App Service, you can enable Application Insights with just a few clicks to start collecting request rates, response times, failure rates, and dependency tracking.

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Azure Monitor for VMs

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Azure SQL Analytics

Question 15

Your team monitors Azure Functions with Application Insights. After a recent deployment, cold start latency increased. Which feature should you enable to mitigate this?

Accepted Answer

Migrate from Consumption plan to Premium plan. Cold start latency occurs when a function app is idle and needs to be loaded from scratch. The Consumption plan can cause cold starts because it scales to zero when idle. Migrating to the Premium plan eliminates cold starts by keeping instances warm, as it provides pre-warmed workers and always-on instances, reducing latency after deployment.

Answer

Set FUNCTIONS_WORKER_RUNTIME to 'dotnet-isolated'

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Enable Azure Monitor alerts on function execution count

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Enable Always On in the function app configuration