- A
Scheduled query rule
Scheduled query rules can run KQL queries on a schedule and trigger based on result counts over defined time windows.
- B
Fusion rule
Why wrong: Fusion rules correlate multiple alerts, not custom log queries.
- C
Near-real-time (NRT) analytics rule
Why wrong: NRT rules are for immediate response but cannot aggregate over an hour.
- D
Machine learning (ML) behavioral analytics rule
Why wrong: ML rules detect anomalies, not fixed thresholds.
Question 1,346 of 1,411
SC-900 Practice Question: Describe the capabilities of Microsoft security solutions
This SC-900 practice question tests your understanding of describe the capabilities of microsoft security solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. 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.
Your organization uses Microsoft Sentinel. You need to create a custom analytics rule that triggers an incident when a user fails to sign in more than five times within an hour. Which rule type should you use?
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
✓
Scheduled query rule
A scheduled query rule is the correct choice because it allows you to define a KQL query that counts sign-in failures per user over a specified time window (e.g., 1 hour) and triggers an incident when the count exceeds a threshold (e.g., 5). This rule type runs on a schedule you define, making it ideal for detecting patterns like brute-force attempts that require aggregation over time.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Scheduled query rule
Why this is correct
Scheduled query rules can run KQL queries on a schedule and trigger based on result counts over defined time windows.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Fusion rule
Why it's wrong here
Fusion rules correlate multiple alerts, not custom log queries.
- ✗
Near-real-time (NRT) analytics rule
Why it's wrong here
NRT rules are for immediate response but cannot aggregate over an hour.
- ✗
Machine learning (ML) behavioral analytics rule
Why it's wrong here
ML rules detect anomalies, not fixed thresholds.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse 'near-real-time' with 'real-time aggregation over a window,' but NRT rules cannot perform time-based aggregation like counting events over an hour, which is a key differentiator from scheduled query rules.
Detailed technical explanation
How to think about this question
Under the hood, a scheduled query rule in Microsoft Sentinel uses a KQL query that leverages the `bin()` function to group events into 1-hour time buckets and the `summarize` operator with `count()` to tally failures per user. The rule's `TriggerThreshold` property defines the incident creation condition (e.g., `NumberOfEvents > 5`), and the schedule interval (e.g., every 5 minutes) determines how often the query runs, with a lookback period equal to the query window to avoid missing events. A real-world scenario is detecting a password spray attack where an attacker tries a few common passwords against many accounts; the scheduled query rule can aggregate failures per user across all sign-in logs to catch the pattern.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
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
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this SC-900 question test?
Describe the capabilities of Microsoft security solutions — This question tests Describe the capabilities of Microsoft security solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Scheduled query rule — A scheduled query rule is the correct choice because it allows you to define a KQL query that counts sign-in failures per user over a specified time window (e.g., 1 hour) and triggers an incident when the count exceeds a threshold (e.g., 5). This rule type runs on a schedule you define, making it ideal for detecting patterns like brute-force attempts that require aggregation over time.
What should I do if I get this SC-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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