- A
extend
Why wrong: Extend creates calculated columns, but it is not the main operator for filtering or trimming output.
- B
join
Why wrong: Join combines data from multiple tables, which is unnecessary for a simple failure search.
- C
project
Project keeps only the columns you want to display in the query results.
- D
summarize
Why wrong: Summarize is useful for aggregation, but not for listing individual failed jobs directly.
- E
where
Where filters rows so the query returns only backup jobs with a failure status.
Question 117 of 1,170
AZ-104 Monitor and Maintain Azure Resources Practice Question
This AZ-104 practice question tests your understanding of monitor and maintain azure resources. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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 support engineer is narrowing a Log Analytics query to only failed backup jobs and wants to show only the needed columns. Which two KQL operators should they use? Select two.
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
✓
project
The `where` operator filters rows based on a condition, so it is used to narrow results to only failed backup jobs (e.g., `where Status == "Failed"`). The `project` operator selects a subset of columns, allowing the engineer to display only the needed columns (e.g., `project JobName, Status, StartTime`). Together, they achieve both row filtering and column selection in a Kusto Query Language (KQL) query.
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.
- ✗
extend
Why it's wrong here
Extend creates calculated columns, but it is not the main operator for filtering or trimming output.
When this WOULD be correct
A question asks: 'You need to add a new column that calculates the duration of each backup job in hours based on existing start and end time columns. Which KQL operator should you use?' In that scenario, 'extend' is correct because it creates a calculated column without removing other columns.
- ✗
join
Why it's wrong here
Join combines data from multiple tables, which is unnecessary for a simple failure search.
When this WOULD be correct
A question that asks: 'You need to combine backup job logs from two different Azure regions into a single result set based on job ID. Which KQL operator should you use?' In that scenario, 'join' would be correct.
- ✓
project
Why this is correct
Project keeps only the columns you want to display in the query results.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
summarize
Why it's wrong here
Summarize is useful for aggregation, but not for listing individual failed jobs directly.
When this WOULD be correct
A question asks: 'You need to count the number of failed backup jobs per day. Which KQL operator should you use?' In that scenario, 'summarize' with count() and bin() would be correct.
- ✓
where
Why this is correct
Where filters rows so the query returns only backup jobs with a failure status.
Related concept
Read the scenario before looking for a memorised answer.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The AZ-104 exam frequently reuses these exact scenarios with slightly different constraints.
✓projectCorrect answer▾
Why this is correct
Project keeps only the columns you want to display in the query results.
✗extendWrong answer — click to see why▾
Why this is wrong here
The 'extend' operator adds a new calculated column to the result set, but it does not filter rows or remove existing columns. The question requires narrowing to only failed backup jobs (filtering) and showing only needed columns (projection), which is achieved by 'where' and 'project', not 'extend'.
★ When this WOULD be the correct answer
A question asks: 'You need to add a new column that calculates the duration of each backup job in hours based on existing start and end time columns. Which KQL operator should you use?' In that scenario, 'extend' is correct because it creates a calculated column without removing other columns.
Why candidates choose this
Candidates may think 'extend' can both add columns and limit output, confusing it with 'project'. They might also believe that extending the query to include only certain columns is possible, but 'extend' always retains all original columns.
✗joinWrong answer — click to see why▾
Why this is wrong here
The 'join' operator is used to combine rows from two tables based on a matching key, not to filter rows or select columns. The question asks for narrowing results to only failed backup jobs (filtering) and showing only needed columns (projection), which require 'where' and 'project'.
★ When this WOULD be the correct answer
A question that asks: 'You need to combine backup job logs from two different Azure regions into a single result set based on job ID. Which KQL operator should you use?' In that scenario, 'join' would be correct.
Why candidates choose this
Candidates may confuse 'join' with 'project' because both can reshape the result set, or they might think joining multiple tables is necessary to get the required columns, even though the question only involves a single table.
✗summarizeWrong answer — click to see why▾
Why this is wrong here
The 'summarize' operator aggregates data into groups, but the question requires filtering rows (failed jobs) and selecting columns, not aggregation. It does not filter or project columns.
★ When this WOULD be the correct answer
A question asks: 'You need to count the number of failed backup jobs per day. Which KQL operator should you use?' In that scenario, 'summarize' with count() and bin() would be correct.
Why candidates choose this
Candidates may think 'summarize' can reduce columns by grouping, but they overlook that it changes the row structure and doesn't simply select columns like 'project' does.
Analysis generated from the official AZ-104blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse `project` with `extend` (thinking both are for column manipulation) or incorrectly assume `summarize` can filter rows, when in fact `summarize` aggregates and loses row-level detail.
Trap categories for this question
Command / output trap
Extend creates calculated columns, but it is not the main operator for filtering or trimming output.
Detailed technical explanation
How to think about this question
In KQL, `where` evaluates a Boolean expression against each row, leveraging indexes in Log Analytics for efficient filtering; for example, `where BackupStatus == "Failed"` can use a string equality index. The `project` operator reorders and limits columns, and it can also rename columns (e.g., `project JobName, Status = BackupStatus`), which is useful for reducing data transfer and improving query performance in large log datasets. A real-world scenario is an engineer troubleshooting backup failures by filtering to only failed jobs and projecting only the timestamp, job name, and error message to quickly identify patterns.
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 AZ-104 question test?
Monitor and Maintain Azure Resources — This question tests Monitor and Maintain Azure Resources — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: project — The `where` operator filters rows based on a condition, so it is used to narrow results to only failed backup jobs (e.g., `where Status == "Failed"`). The `project` operator selects a subset of columns, allowing the engineer to display only the needed columns (e.g., `project JobName, Status, StartTime`). Together, they achieve both row filtering and column selection in a Kusto Query Language (KQL) query.
What should I do if I get this AZ-104 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.
About these practice questions
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Last reviewed: Jun 11, 2026
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