The correct answer is that the KQL query identifies the most frequent high-severity alerts over the past week. This is because the query filters on `AlertSeverity == 'High'` and `TimeGenerated > ago(7d)`, then uses `summarize count()` by `AlertName` and `top 5 by count_ desc` to rank the alert names by frequency, directly surfacing the most common critical alerts. On the Microsoft Cybersecurity Architect exam, this tests your ability to read and interpret KQL in Sentinel, often appearing in scenario-based questions where you must match a query’s logic to its business purpose. A common trap is confusing `top` with `sort`—remember that `top` both sorts and limits results, while `sort` alone requires a separate `take` or `limit`. Memory tip: think “High 7, top 5” to recall the severity filter, time range, and ranking limit.
SC-100 Practice Question: Design security operations, identity, and compliance capabilities
This SC-100 practice question tests your understanding of design security operations, identity, and compliance capabilities. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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.
Exhibit
Refer to the exhibit.
```kusto
SecurityAlert
| where TimeGenerated > ago(7d)
| where AlertSeverity == "High"
| summarize AlertCount = count() by AlertName, bin(TimeGenerated, 1d)
| order by AlertCount desc
```
The exhibit shows a KQL query in Microsoft Sentinel. What is the primary purpose of this query?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "primary"
Why it matters: Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.
Refer to the exhibit.
```kusto
SecurityAlert
| where TimeGenerated > ago(7d)
| where AlertSeverity == "High"
| summarize AlertCount = count() by AlertName, bin(TimeGenerated, 1d)
| order by AlertCount desc
```
A
Find alerts that were not investigated
Why wrong: No investigation data is queried.
B
Analyze entities associated with alerts
Why wrong: No entity data is included.
C
Identify the most frequent high-severity alerts over the past week
Summarizes counts and orders by highest count.
D
Correlate alerts by time and alert name
Why wrong: Correlation is not the primary purpose.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Identify the most frequent high-severity alerts over the past week
The query uses `summarize` with `count()` and `top 5 by count_ desc` to rank alert names by frequency, filtered to `AlertSeverity == 'High'` and `TimeGenerated > ago(7d)`. This directly identifies the most common high-severity alerts over the past week, making option C correct.
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.
✗
Find alerts that were not investigated
Why it's wrong here
No investigation data is queried.
✗
Analyze entities associated with alerts
Why it's wrong here
No entity data is included.
✓
Identify the most frequent high-severity alerts over the past week
Why this is correct
Summarizes counts and orders by highest count.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Correlate alerts by time and alert name
Why it's wrong here
Correlation is not the primary purpose.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may misinterpret the `bin(TimeGenerated, 1h)` as correlating alerts by time and name (option D), but the query only aggregates counts per alert name, not correlating alerts across different time windows or names.
Detailed technical explanation
How to think about this question
The `summarize` operator in KQL groups rows by `AlertName` and `bin(TimeGenerated, 1h)`, creating hourly buckets, then counts rows per bucket. The `top 5 by count_ desc` returns the five alert names with the highest total count across all hourly buckets, effectively ranking by frequency. In Microsoft Sentinel, this pattern is commonly used in workbooks or hunting queries to surface dominant alert patterns, but it does not account for alert deduplication or entity correlation, which would require additional joins or `make_set` operations.
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this SC-100 question in full detail.
Design security operations, identity, and compliance capabilities — This question tests Design security operations, identity, and compliance capabilities — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Identify the most frequent high-severity alerts over the past week — The query uses `summarize` with `count()` and `top 5 by count_ desc` to rank alert names by frequency, filtered to `AlertSeverity == 'High'` and `TimeGenerated > ago(7d)`. This directly identifies the most common high-severity alerts over the past week, making option C correct.
What should I do if I get this SC-100 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "primary". Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Refer to the exhibit. You run this KQL query in Microsoft Sentinel. What is the primary purpose?
hard
A.Correlate alerts across different data sources
B.Identify new high-severity alerts in the last 7 days
✓ C.Detect entities that have been repeatedly targeted by high-severity alerts
D.Find entities with fewer than 5 high-severity alerts
Why C: The KQL query uses the `make_set` function to aggregate distinct alert names per entity (e.g., host or user) and then filters for entities that have been hit by more than 5 distinct high-severity alerts. This directly identifies entities repeatedly targeted by high-severity alerts, which is the primary purpose.
Last reviewed: Jun 24, 2026
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