The answer is the `where` and `project` operators. The `where` operator filters rows based on a condition, such as `where Status == "Failed"`, which narrows results to only failed backup jobs, while the `project` operator selects a subset of columns, allowing you to display only the needed fields like JobName, Status, and StartTime. On the AZ-104 exam, this tests your ability to construct efficient KQL queries in Log Analytics, often in scenarios where you must isolate specific events and reduce noise. A common trap is confusing `project` with `extend`, but remember that `project` drops unlisted columns, whereas `extend` adds new ones. For a quick memory tip, think of `where` as the gatekeeper for rows and `project` as the spotlight for columns.
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 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.
✗
join
Why it's wrong here
Join combines data from multiple tables, which is unnecessary for a simple failure search.
✓
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.
✓
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.
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.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AZ-104 question in full detail.
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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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. A support engineer is investigating a failed Azure VM backup job in Log Analytics. Match each KQL operator to the result it produces.
medium
Why : These are common KQL operators. 'where' filters, 'project' selects columns, 'extend' adds columns, 'summarize' aggregates, 'join' merges tables, and 'order by' sorts results.
Variation 2. In Log Analytics, you need to find AzureActivity records for VM stop or deallocate operations from the last 24 hours. Which query should you use?
easy
✓ A.AzureActivity | where TimeGenerated > ago(24h) | where OperationNameValue has_any ("Microsoft.Compute/virtualMachines/deallocate/action", "Microsoft.Compute/virtualMachines/powerOff/action")
B.AzureActivity | summarize count() by OperationNameValue
C.AzureActivity | where ResourceType == "Microsoft.Compute/virtualMachines" | project TimeGenerated, ResourceGroup
D.AzureActivity | sort by TimeGenerated asc
Why A: Option A is correct because it uses the `has_any` operator to filter AzureActivity records for the exact operation names corresponding to VM stop (powerOff) and deallocate actions, and it restricts the time range to the last 24 hours using `ago(24h)`. This directly matches the requirement to find VM stop or deallocate operations within the specified timeframe.
Variation 3. A VM named VM01 stopped sending Heartbeat records to Log Analytics 15 minutes ago. Which KQL query should you run to confirm the VM's recent heartbeat entries?
easy
✓ A.Heartbeat | where Computer == "VM01" and TimeGenerated > ago(15m)
B.AzureActivity | where ResourceProviderValue == "Microsoft.Compute/virtualMachines"
C.Heartbeat | summarize count() by Computer
D.Perf | where CounterName == "% Processor Time"
Why A: The Heartbeat table in Log Analytics stores records sent by the Azure Monitor Agent (AMA) or Log Analytics agent every 5 minutes by default. Querying Heartbeat with a filter for Computer == 'VM01' and TimeGenerated > ago(15m) directly checks if any heartbeat records were generated in the last 15 minutes, confirming whether the VM is still reporting. This is the correct approach because Heartbeat is the dedicated table for agent health, and the time filter matches the 15-minute window specified in the question.
Last reviewed: Jun 11, 2026
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