Azure Monitor overview - Step-by-Step Execution

Process Flow - Azure Monitor overview

Start: Azure resources generate data

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Data collected by Azure Monitor

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Data categorized: Metrics, Logs, Alerts

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Metrics stored in Metrics database

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Logs stored in Log Analytics workspace

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Alerts configured to watch data

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Notifications sent or actions triggered

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Users analyze data via dashboards and workbooks

Azure Monitor collects data from resources, organizes it into metrics and logs, triggers alerts, and helps users analyze and act on this data.

Execution Sample

Azure

Resource -> Azure Monitor collects data
Data -> Categorized as Metrics or Logs
Metrics -> Stored in Metrics DB
Logs -> Stored in Log Analytics
Alerts -> Triggered on conditions
Notifications -> Sent to users

This flow shows how Azure Monitor collects and processes data from resources to provide monitoring and alerting.

Process Table

Step	Action	Data Type	Storage/Outcome	User Impact
1	Resource generates data	Raw data	Sent to Azure Monitor	No direct user impact
2	Azure Monitor collects data	Raw data	Received for processing	No direct user impact
3	Data categorized	Metrics and Logs	Separated for storage	Enables targeted analysis
4	Metrics stored	Metrics	Metrics database	Fast access for performance monitoring
5	Logs stored	Logs	Log Analytics workspace	Detailed event analysis
6	Alerts configured	Metrics/Logs	Alert rules active	Monitors for issues
7	Alert triggered	Alert condition met	Notification sent	User notified of issue
8	User analyzes data	Metrics/Logs	Dashboards and workbooks	Informed decisions and troubleshooting
9	End	N/A	Monitoring cycle continues	Continuous monitoring

💡 Monitoring cycle is continuous; steps repeat as new data arrives.

Status Tracker

Variable	Start	After Step 3	After Step 5	After Step 7	Final
Raw Data	None	Collected	Collected	Collected	Collected
Metrics	None	Separated	Stored	Stored	Stored
Logs	None	Separated	Stored	Stored	Stored
Alerts	None	None	Configured	Triggered	Configured
Notifications	None	None	None	Sent	Sent

Key Moments - 3 Insights

Why does Azure Monitor separate data into metrics and logs?

Separating data allows Azure Monitor to store and process metrics quickly for performance monitoring, while logs provide detailed event information for deeper analysis, as shown in steps 3 to 5 in the execution table.

What triggers an alert notification to users?

An alert notification is triggered when alert conditions configured on metrics or logs are met, as shown in step 7 where the alert triggers and notifications are sent.

Is the monitoring process a one-time event or continuous?

The monitoring process is continuous, with Azure Monitor constantly collecting new data and repeating the cycle, as noted in the exit note and step 9.

Visual Quiz - 3 Questions

Look at the execution table, at which step are metrics stored in the metrics database?

A Step 6

B Step 3

C Step 4

D Step 7

💡 Hint

Refer to the 'Storage/Outcome' column in the execution table row for Step 4.

According to the variable tracker, when are alerts first configured?

A After Step 5

B After Step 3

C After Step 7

D At Start

💡 Hint

Check the 'Alerts' row and see when its value changes from 'None' to 'Configured'.

If the alert conditions are never met, what happens to notifications according to the execution table?

A Notifications are sent anyway

B Notifications are never sent

C Notifications are stored but not sent

D Notifications are sent only after user analysis

💡 Hint

Look at Step 7 where notifications are sent only when alert conditions are met.

Concept Snapshot

Azure Monitor collects data from resources.
Data is split into metrics (performance numbers) and logs (detailed events).
Metrics go to a fast database; logs go to Log Analytics.
Alerts watch data and notify users on issues.
Users analyze data via dashboards for insights.
This process runs continuously to keep resources healthy.

Full Transcript

Azure Monitor is a service that collects data from your cloud resources. It gathers two main types of data: metrics, which are numbers showing performance, and logs, which are detailed records of events. The service stores metrics in a special database for quick access and logs in a workspace for deep analysis. Users can set up alerts to watch this data and get notified if something needs attention. Finally, users can view dashboards and reports to understand the health and performance of their resources. This monitoring happens continuously to help keep systems running smoothly.