Quick Answer
The answer is the `summarize` operator. This is the correct choice because `summarize` groups rows by a specified key—in this case, the source IP address—and then applies an aggregation function like `count()` to produce a single output row per group, which is exactly what you need to aggregate failed sign-ins. On the Microsoft Security Operations Analyst SC-200 exam, this scenario tests your ability to write KQL for custom analytics rules in Microsoft Sentinel, where you must count events over a time window and trigger alerts based on thresholds. A common trap is confusing `summarize` with `project` or `extend`, which do not group data; `summarize` is the only operator that collapses rows into aggregated results. For a memory tip, think of “summarize” as “sum it up by group”—it always pairs with an aggregation function like `count()`, `sum()`, or `dcount()` to condense logs into actionable insights.
This SC-200 practice question tests your understanding of mitigate threats using microsoft sentinel. 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.
A security analyst in Microsoft Sentinel wants to create a custom analytics rule that triggers when more than 10 failed logon attempts from a single source IP address occur within 5 minutes. The analyst writes a KQL query to aggregate sign-in logs. Which KQL operator should the analyst use to group events by source IP and count each failure?
extend
Why wrong: extend adds new calculated columns to each row but does not group or aggregate data.
project
Why wrong: project selects a subset of columns, it does not group rows.
summarize
summarize groups rows by specified columns and applies aggregation functions like count(), making it the correct operator for this use case.
where
Why wrong: where filters rows based on a condition but does not perform grouping or counting.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
summarize
The `summarize` operator is correct because it groups rows by a specified key (source IP) and applies an aggregation function (like `count()`) to produce a single output row per group. In this scenario, the analyst needs to count failed logon attempts per source IP, which requires grouping and counting—exactly what `summarize` does.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
extend
Why it's wrong here
extend adds new calculated columns to each row but does not group or aggregate data.
project
Why it's wrong here
project selects a subset of columns, it does not group rows.
summarize
Why this is correct
summarize groups rows by specified columns and applies aggregation functions like count(), making it the correct operator for this use case.
Related concept
Read the scenario before looking for a memorised answer.
where
Why it's wrong here
where filters rows based on a condition but does not perform grouping or counting.
Common exam traps
The trap here is that candidates often confuse `extend` or `project` with aggregation, thinking they can count events by adding a column, but only `summarize` performs the required grouping and counting operation.
Detailed technical explanation
The `summarize` operator in Kusto Query Language (KQL) uses a hash-based grouping mechanism to partition rows by the specified key(s), then applies aggregation functions like `count()`, `sum()`, or `dcount()` to each group. In Microsoft Sentinel, this is commonly used in analytics rules to detect patterns like brute-force attacks, where you group by `SourceIP` and use `count()` with a `where` filter for `ResultType == 'Failure'` to count failed logons within a time window.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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
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FAQ
Mitigate threats using Microsoft Sentinel — This question tests Mitigate threats using Microsoft Sentinel — Read the scenario before looking for a memorised answer..
The correct answer is: summarize — The `summarize` operator is correct because it groups rows by a specified key (source IP) and applies an aggregation function (like `count()`) to produce a single output row per group. In this scenario, the analyst needs to count failed logon attempts per source IP, which requires grouping and counting—exactly what `summarize` does.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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