The correct answer is that a Log Analytics workspace supports KQL queries and serves as a centralized log storage repository. These two capabilities are foundational because the workspace ingests log data from diverse Azure sources—such as virtual machines, Activity logs, and resource diagnostics—and stores it in a unified location for monitoring and analysis. Kusto Query Language (KQL) then enables you to perform complex searches, aggregations, and visualizations on that stored data, turning raw logs into actionable insights. On the AZ-104 exam, this concept often appears in questions about monitoring and troubleshooting, where a common trap is confusing Log Analytics with Azure Monitor metrics or assuming it only stores VM logs. Remember the mnemonic “CASK”: Centralized storage and KQL queries are the two key workspace capabilities.
AZ-104 Monitor and Maintain Azure Resources Practice Question
This AZ-104 practice question tests your understanding of monitor and maintain azure resources. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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.
Which two statements about a Log Analytics workspace are correct? Select two.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
It can store logs collected from Azure resources
Option A is correct because a Log Analytics workspace is a centralized repository that can ingest and store log data from various Azure resources, including virtual machines, Azure Activity logs, and resource diagnostics, enabling monitoring and analysis. Option B is correct because Log Analytics workspaces support Kusto Query Language (KQL) queries, which allow users to perform complex searches, aggregations, and visualizations on the stored log data.
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.
✓
It can store logs collected from Azure resources
Why this is correct
The workspace is a central store for logs ingested from Azure services and devices.
Related concept
Read the scenario before looking for a memorised answer.
✓
It supports KQL queries
Why this is correct
You use KQL in Log Analytics to search, filter, and summarize stored log data.
Related concept
Read the scenario before looking for a memorised answer.
✗
It creates backups of Azure virtual machines
Why it's wrong here
Backup operations are handled by Azure Backup, not by a Log Analytics workspace.
✗
It assigns permissions to Azure resources at scope
Why it's wrong here
Permission assignment is an Azure RBAC function, not a workspace function.
✗
It blocks resource creation that violates a rule
Why it's wrong here
Blocking noncompliant deployments is done by Azure Policy, not Log Analytics.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse the monitoring and log storage capabilities of Log Analytics workspaces with other Azure services like Azure Backup, Azure Policy, or RBAC, leading them to select options that describe those separate services instead.
Detailed technical explanation
How to think about this question
Under the hood, a Log Analytics workspace is essentially a data store that uses Azure Data Explorer's engine to handle ingestion and querying, with data retention policies configurable from 30 days to 730 days (or up to 2 years for some tiers). In a real-world scenario, you might configure diagnostic settings on multiple Azure VMs to send performance counters and event logs to a single Log Analytics workspace, then use KQL to correlate CPU spikes across all VMs during a specific time window, enabling rapid troubleshooting.
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 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: It can store logs collected from Azure resources — Option A is correct because a Log Analytics workspace is a centralized repository that can ingest and store log data from various Azure resources, including virtual machines, Azure Activity logs, and resource diagnostics, enabling monitoring and analysis. Option B is correct because Log Analytics workspaces support Kusto Query Language (KQL) queries, which allow users to perform complex searches, aggregations, and visualizations on the stored log data.
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.
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