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Metric alert rule
Action group
Diagnostic setting
Activity log alert
Log Analytics workspace
AZ-104 Monitor and Maintain Azure Resources Practice Question
A team manages a production VM and its supporting storage account. Match each operational requirement to the Azure Monitor component that should be configured.
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
✓
Azure Monitor Metrics: Stores numerical performance data
Azure Monitor Metrics stores numerical performance data, Log Analytics enables KQL queries, Alerts notify on conditions, Workbooks provide dashboards, the Azure Monitor Agent collects guest OS logs, and Storage analytics logs capture storage access data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Azure Monitor Metrics: Stores numerical performance data
Why this is correct
Azure Monitor Metrics is specifically a time-series database optimized for numeric performance data such as CPU percentage, memory utilization, and disk IOPS. These metrics are collected at regular intervals (often every minute) and are ideal for near-real-time alerting and autoscale decisions. Unlike logs, metrics do not support KQL queries and are primarily visualized in Metric Explorer.
- ✓
Log Analytics: Enables KQL queries against collected log data
Why this is correct
Log Analytics is the component of Azure Monitor that ingests and stores log data from various sources, including application logs, custom logs, and Azure activity logs. Users write Kusto Query Language (KQL) queries against this workspace to filter, aggregate, and troubleshoot issues across large volumes of semi-structured data. It is fundamentally a log-analysis platform, not a numerical metric store, and it powers log search alerts and workbooks.
- ✓
Alerts: Notify administrators when conditions are met
Why this is correct
Azure Monitor Alerts are rule-based mechanisms that continuously evaluate metric thresholds, log search results, or activity log events and then trigger a notification whenever the specified conditions are met. They rely on action groups to deliver alerts via email, SMS, webhook, ITSM, or automated responses. Alerts themselves do not collect or store data—they simply react to data already gathered by Metrics or Log Analytics.
- ✓
Azure Monitor Agent: Collects guest OS performance and event logs
Why this is correct
The Azure Monitor Agent (AMA) is a newer unified data-collection agent that installs inside the guest OS of virtual machines. It collects performance counters (from the OS) and event logs (like Windows Event Log or Linux Syslog) and sends them to Azure Monitor Metrics and Log Analytics. AMA replaces the older Log Analytics agent and Microsoft Monitoring Agent, offering centralized configuration via data collections rules (DCRs). This is a data-ingestion role, distinct from analysis or alerting.
- ✗
Azure Monitor Metrics: Enables KQL queries against collected log data
Why it's wrong here
Azure Monitor Metrics does not provide KQL query capabilities because it is designed for numeric time-series storage with its own charting and metric explorer interface. KQL is exclusively used with Log Analytics workspaces, which store log data and support complex queries across events, strings, and tables. Attributing KQL to Metrics confuses the distinct data platforms—Metrics handles numeric series, while Logs handle text-heavy events.
- ✗
Log Analytics: Stores numerical performance data
Why it's wrong here
Log Analytics does not store numerical performance data in the same manner as Azure Monitor Metrics; its primary role is to store log and event records, which are queryable via KQL. While some numeric values may appear inside log entries, performance counters like CPU or memory are routed to the Metrics database for low-latency trend analysis and metric alerts. Log Analytics is optimized for unstructured log search, not for high-frequency numerical time-series data.
Go deeper
Related to this question
Learn chapter
Managed Identities for Azure Resources
Key term
Storage account
A cloud storage account is a container that holds a set of cloud storage services and their data, providing a unique namespace and access policies for storing and managing unstructured data.
Key term
KQL
Kusto Query Language is a powerful read-only query language used to explore, analyze, and visualize large datasets, most notably in Azure Data Explorer and Microsoft Sentinel.
About these practice questions
Courseiva writes every AZ-104 question from scratch — 1,049 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more way this is tested on AZ-104
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. An operations team monitors a group of Azure VMs and storage accounts. Match each Azure Monitor component to the behavior it provides in day-to-day operations.
medium- ✓ A.Metrics: Collects numeric performance data from Azure resources.
- B.Action Groups: Automatically adjusts the number of instances.
- ✓ C.Logs: Collects text-based event logs and traces from resources.
- D.Autoscale: Defines the notification preferences for alerts.
- ✓ E.Alerts: Sends proactive notifications based on metric or log rule conditions.
- F.Workbooks: Stores log data for long-term retention.
Why A: Metrics give real-time performance; Logs store detailed events; Alerts trigger notifications; Workbooks visualize data; Autoscale adjusts capacity; Action Groups configure alert responses.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AZ-104 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AZ-104 exam.