Azure Log Analytics Overview

🔍 What is Azure Log Analytics?

Azure Log Analytics is a service within Azure Monitor that collects, correlates, and analyzes log and telemetry data from various sources, providing actionable insights for monitoring, troubleshooting, and operational intelligence.

⚙️ Key Features

• Centralized log collection from Azure resources, on-premises systems, and custom sources.
• Powerful query engine using Kusto Query Language (KQL) for deep analysis.
• Integration with dashboards, alerts, and automation workflows.
• Support for multi-tenant and modular architectures via resource tagging and partitioning.
• Data retention and export capabilities for compliance and historical analysis.

📊 Common Use Cases

• Monitoring application performance and usage patterns.
• Tracking infrastructure health and availability.
• Analyzing security events and incidents (integration with Microsoft Sentinel).
• Root cause analysis for operational issues.
• Creating interactive dashboards for multi-tenant SaaS environments.

🛠 How It Works

1. Collect logs and metrics from Azure resources, on-prem systems, or custom applications using agents or APIs.
2. Store all telemetry in a centralized Log Analytics Workspace.
3. Use KQL queries to filter, summarize, and analyze the data.
4. Visualize insights via Azure Monitor Workbooks, dashboards, or integrate with custom applications.
5. Set alerts or trigger automated actions based on query results.

✅ Benefits

• Single source of truth for telemetry data across resources.
• Faster troubleshooting and proactive issue detection.
• Flexible queries and visualizations for operations and business insights.
• Scalable for small deployments or large multi-tenant environments.
• Supports compliance and auditing requirements with long-term data retention.

💡 Example

Query the last 24 hours of failed logins from all monitored systems:

SigninLogs
| where ResultType != 0
| where TimeGenerated > ago(24h)
| summarize FailedLogins = count() by IPAddress
| top 10 by FailedLogins desc
  

🧠 What is Azure Log Analytics?

Azure Log Analytics is a data analysis tool within Azure Monitor that lets you collect, query, and analyze log and telemetry data from:

• Azure resources (VMs, App Services, AKS, etc.)
• On-premises or hybrid machines
• Applications (via Application Insights)
• Security and network devices

It’s powered by the Kusto Query Language (KQL), giving you the ability to run advanced queries, detect patterns, troubleshoot issues, and create visual dashboards. Think of it as your central brain for operational intelligence — all logs and metrics flow into a Log Analytics Workspace, where you can slice, dice, and correlate them.

🔍 Key Capabilities

• Centralized Data Store — All telemetry in one place (workspace-based).
• Powerful Querying — Use KQL for filtering, aggregation, joins, and anomaly detection.
• Cross-Resource Analysis — Query across subscriptions, tenants, or external sources.
• Integration — Works with Azure Monitor Alerts, Workbooks, Microsoft Sentinel, and Power BI.
• Custom Logs — Ingest your own application or system logs.
• Security & Access Control — RBAC and table-level permissions.

⚙️ How It Works

Data Collection

• Enable Diagnostic Settings on Azure resources.
• Install Azure Monitor Agent (AMA) on VMs or servers.
• Connect Application Insights, Security Center, or Sentinel.

Data Storage

• Data is stored in a Log Analytics Workspace.
• Retention period is configurable (default 30 days, can extend to 2 years+).

Data Analysis

• Use the Logs blade in Azure Portal to run KQL queries.
• Build Workbooks for visualization.
• Create Alerts that trigger on query results.

📘 Example Use Case

Scenario: You manage a multi-tenant SaaS platform and want to monitor failed login attempts across all tenants.

SigninLogs
| where ResultType != 0
| summarize Failures = count() by TenantId, UserPrincipalName
| order by Failures desc
  

Outcome: You instantly see which tenants or users are experiencing the most failed logins — useful for security monitoring and proactive support.

🛡 Best Practices

• Tag Resources — Use TenantId, Environment, ServiceType for easy filtering.
• Filter at Source — Collect only necessary log categories to control costs.
• Parameterize Queries — Make Workbooks reusable for different tenants.
• Archive Long-Term — Move older logs to Azure Storage for compliance.
• Integrate Alerts — Turn critical queries into proactive notifications.

💡 Architecture Tip

You can design a multi-tenant monitoring layer where all telemetry flows into a central Log Analytics Workspace, but queries and dashboards are filtered by tenant tags. This gives you one source of truth while maintaining data isolation.