Types of Monitoring in Azure — and When You Should Use What

When you’re building modern data solutions on Azure, monitoring isn’t a “nice-to-have.” It’s essential. But Azure has a lot of monitoring tools — and it’s not always obvious when to use what, and for which layer.

So here’s a quick guide I’ve used in real-world Azure data engineering projects — outlining which tool serves what purpose, and how to use them effectively.

1. Azure Monitor — Your Central Monitoring Hub

What it is: Azure Monitor is the umbrella service for collecting metrics, logs, and diagnostics from pretty much any Azure resource — including VMs, ADF pipelines, Synapse, Databricks, SQL pools, and more.

When to use: Use Azure Monitor when you want to:

• Get performance metrics (CPU, memory, latency, etc.)
• Set up alert rules for failure or threshold breaches
• Route data to Log Analytics, Event Hub, or Storage for deeper analysis

Typical use case: You’re running Synapse pipelines or Spark jobs, and you want to monitor success/failure rates, latency, and resource usage — Azure Monitor is your first stop.

2. Log Analytics — Custom Monitoring & Root Cause Analysis

What it is: Log Analytics is where you store and query logs and telemetry data — using Kusto Query Language (KQL). It’s integrated with Azure Monitor.

When to use: Use Log Analytics when you need:

• Custom log ingestion (from Databricks notebooks, ADF logs, storage logs, etc.)
• Deep root cause analysis via KQL
• Custom dashboards and alerts

Typical use case: You build an ADF pipeline with multiple validation steps. You log detailed telemetry (like row counts, nulls, failures) and push it into Log Analytics to track patterns or anomalies over time.

3. Application Insights — For App-Level Monitoring

What it is: This is focused on monitoring custom apps — APIs, web apps, function apps — but it can also work with Databricks or custom PySpark apps if instrumented properly.

When to use: Use it when you want to:

• Trace request-level logs or response times
• Monitor exceptions, failures, or user behavior in custom apps
• Visualize dependencies (e.g., Function App → Data Lake → SQL pool)

Typical use case: You’re using Azure Functions to trigger pipeline runs or validations — Application Insights helps you trace failures and understand latency issues at the function level.

4. Azure Diagnostic Logs — For Platform-Level Events

What it is: These are logs generated by Azure services themselves — covering operational events like access attempts, read/write failures, permission changes, etc.

When to use: Enable diagnostics when you want to:

• Monitor access logs (e.g., who accessed your ADLS or Synapse?)
• Track internal errors from Azure services
• Audit permission or role-based changes

Typical use case: You’re working with sensitive data and need to ensure no unauthorized access happens on Blob Storage or SQL — diagnostic logs feed this data into Log Analytics or Sentinel.

5. Azure Sentinel — For Security Monitoring

What it is: Sentinel is a SIEM (Security Information and Event Management) solution. It’s used to detect, investigate, and respond to security threats.

When to use: Use it when you need to:

• Correlate events from multiple sources for threat detection
• Set up threat intelligence rules
• Automate responses to suspicious activity

Typical use case: You're handling PII and need security monitoring across storage, SQL, and RBAC changes — Sentinel pulls logs from Log Analytics and triggers alerts when something suspicious happens.

6. Cost Management + Advisor — For Cost & Optimization Monitoring

What it is: These tools monitor your Azure usage and help optimize resources and cost.

When to use: Use when you need to:

• Track spend per resource or service
• Identify underutilized clusters or services
• Apply budgets and alerts to avoid overruns

Typical use case: You’re running heavy Spark jobs or large Synapse pools. These tools help detect cost spikes and optimize cluster sizing or scheduling.

7. Service Health & Resource Health — For Platform Outages

What it is: These services notify you of Azure-side outages or issues — region-specific or service-wide.

When to use: Use when:

• You want alerts if an Azure service (like ADF or ADLS) goes down
• You need incident-level diagnostics or SLA violations
• You want to monitor availability regionally

Typical use case: Your pipeline failed but logs show nothing wrong — Service Health can tell you if Azure itself had a downtime in that region or service.

Summary: What to Use When