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AZ-204 Practice Question: Application Insights adaptive sampling to reduce…
This AZ-204 practice question tests your understanding of application insights adaptive sampling to reduce…. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. A key principle to apply: application Insights adaptive sampling. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A high-traffic API sends approximately 80,000 telemetry events per second to Application Insights. Monthly ingestion costs are too high. The team wants to reduce data volume by roughly 80 percent while still seeing representative samples of all request types. What should the developer configure?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
Increase the TelemetryClient flush interval from 30 seconds to 5 minutes to batch events
Flush interval controls when buffered events are sent, not how many are sent. Flushing less frequently does not reduce the number of events — it only changes the timing. Total event volume and ingestion cost remain the same.
B
Distractor review
Filter all events with HTTP status code 200 from the telemetry pipeline before sending
Filtering out 200-OK requests removes all evidence of successful operations. Metrics like response time percentiles, throughput, and dependency success rates become meaningless. Sampling preserves proportional representation; hard filtering destroys observability for the majority of traffic.
C
Best answer
Enable adaptive sampling in the Application Insights SDK and set a target events-per-second limit
Adaptive sampling runs in the SDK. It monitors the outgoing telemetry rate and automatically raises or lowers the sample percentage to stay near the target rate. All operation types are sampled proportionally, so statistical trends remain meaningful even at 20 percent of raw volume. Data is reduced before transmission, lowering both network and ingestion costs.
D
Distractor review
Configure ingestion sampling in the Azure portal to retain 20 percent of incoming telemetry
Ingestion sampling discards 80 percent of events after they arrive at the Application Insights endpoint. The data is still transmitted from the application, so network bandwidth is unchanged. It reduces storage and query costs but not the cost of transmitting data from the app.
Common exam trap
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Technical deep dive
How to think about this question
Treat this as a scenario question. Identify the problem, the constraint, and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Application Insights adaptive sampling
- ingestion cost
- representative telemetry
- SDK-side sampling
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Application Insights adaptive sampling
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Question 3
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Question 5
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Question 6
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FAQ
Questions learners often ask
What does this AZ-204 question test?
Application Insights adaptive sampling
What is the correct answer to this question?
The correct answer is: Enable adaptive sampling in the Application Insights SDK and set a target events-per-second limit — Adaptive sampling is built into the Application Insights SDK (ASP.NET, Node.js, Java). It dynamically adjusts the sampling percentage to keep the ingested data rate near a configurable target while preserving statistical representation across all operation types. Because sampling happens in the SDK before data is transmitted, both network bandwidth and ingestion costs decrease proportionally. Ingestion sampling (portal-side) discards data after it has already been transmitted — so it does not reduce network cost.
What should I do if I get this AZ-204 question wrong?
Review application Insights adaptive sampling, then practise related AZ-204 questions on the same topic to reinforce the concept.
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