Azure Sentinel for Beginners

July 25, 2025 👩🏽‍🔬 Letisia Pangata'a

Easy

Azure Sentinel is Microsoft's cloud-native Security Information and Event Management (SIEM) and Security Orchestration, Automation, and Response (SOAR) solution. If you're new to security monitoring or considering a move to cloud-native security tools, this guide will help you understand what Azure Sentinel is, why it matters, and how to get started.

Please refer to this link Microsoft Sentinel Documentation for further information.

What is Azure Sentinel?

Azure Sentinel is a scalable, cloud-native security analytics platform that helps organisations:

  • Collect security data from virtually any source
  • Detect threats using built-in machine learning and analytics
  • Investigate incidents with interactive workbooks and dashboards
  • Respond to threats with automated playbooks and workflows

Think of it as your organisation's security command centre in the cloud, providing a bird's-eye view of your entire digital environment.

Why Choose Azure Sentinel?

1. Cloud-Native Architecture

  • No infrastructure to manage
  • Scales automatically with your needs
  • Pay only for what you use
  • Global availability and reliability

2. Intelligent Security Analytics

  • Built-in machine learning detects sophisticated threats
  • AI reduces false positives
  • Behavioural analytics identify anomalous activities
  • Threat intelligence integration

3. Comprehensive Data Collection

  • Connects to 100+ data sources out-of-the-box
  • Custom connectors for unique environments
  • On-premises and multi-cloud support
  • API-based integrations

4. Built for Modern SOCs

  • Collaboration features for security teams
  • Mobile access for on-the-go monitoring
  • Integration with Microsoft 365 and Azure ecosystem
  • Role-based access control

Core Components Explained

1. Data Connectors

Data connectors are the entry points for your security data. Azure Sentinel offers several types:

  • Microsoft Services: Azure AD, Office 365, Azure Security Centre
  • Security Solutions: Palo Alto, Fortinet, Check Point, CrowdStrike
  • Cloud Platforms: AWS CloudTrail, Google Cloud Platform
  • Network Devices: Firewalls, proxies, DNS servers
  • Custom Connectors: REST APIs, Syslog, CEF (Common Event Format)

2. Analytics Rules

Analytics rules define what constitutes suspicious or malicious activity:

  • Scheduled Rules: Run queries at regular intervals
  • Microsoft Security Rules: Alerts from other Microsoft security products
  • Fusion Rules: ML-powered correlation of multiple weak signals
  • Anomaly Rules: Machine learning-based behavioural analysis

3. Workbooks

Interactive dashboards that provide visual insights into your security data:

  • Pre-built templates for common scenarios
  • Custom visualisations using KQL queries
  • Real-time and historical views
  • Shareable across teams

4. Playbooks

Automated response workflows using Azure Logic Apps:

  • Incident enrichment
  • Notification workflows
  • Automated remediation
  • Integration with third-party tools

Getting Started: Your First Steps

Step 1: Prerequisites

Before setting up Azure Sentinel, ensure you have:

  • Azure subscription with appropriate permissions
  • Log Analytics workspace (Sentinel's data store)
  • Security Reader or Sentinel Contributor role
  • Understanding of your organisation's data sources

Step 2: Enable Azure Sentinel

  1. Navigate to the Azure portal
  2. Search for "Azure Sentinel"
  3. Click "Create Azure Sentinel"
  4. Select or create a Log Analytics workspace
  5. Click "Add Azure Sentinel"

Step 3: Connect Your First Data Source

Start with Microsoft services for the easiest setup:

  1. Go to Data connectors in Sentinel
  2. Select Azure Activity connector
  3. Click Open connector page
  4. Follow the configuration steps
  5. Verify data is flowing in the Logs section

Step 4: Explore Pre-built Content

Azure Sentinel comes with hundreds of pre-built rules and workbooks:

  1. Navigate to Analytics > Rule templates
  2. Browse available detection rules
  3. Enable rules relevant to your environment
  4. Check Workbooks for visualisation templates

Understanding KQL (Kusto Query Language)

KQL is the query language used throughout Azure Sentinel. Here are some beginner-friendly examples:

Basic Query Structure

// Get all Azure Activity logs from the last 24 hours
AzureActivity
| where TimeGenerated > ago(24h)
| take 10

Filtering and Aggregation

// Count login failures by user
SigninLogs
| where ResultType != "0"  // Failed logins
| summarize FailedLogins = count() by UserPrincipalName
| order by FailedLogins desc

Time-based Analysis

// Login activity over time
SigninLogs
| where TimeGenerated > ago(7d)
| summarize LoginCount = count() by bin(TimeGenerated, 1h)
| render timechart

Common Use Cases for Beginners

1. Monitor Failed Login Attempts

Detect potential brute force attacks by monitoring authentication failures:

SigninLogs
| where ResultType != "0"
| where TimeGenerated > ago(1d)
| summarize FailureCount = count() by UserPrincipalName, IPAddress
| where FailureCount > 5
| order by FailureCount desc

2. Track Administrative Activities

Monitor privileged operations in your Azure environment:

AzureActivity
| where CategoryValue == "Administrative"
| where ActivityStatusValue == "Success"
| where TimeGenerated > ago(24h)
| project TimeGenerated, Caller, OperationNameValue, ResourceGroup

3. Identify Unusual Network Traffic

Analyse network connections for anomalous patterns:

CommonSecurityLog
| where DeviceVendor == "Palo Alto Networks"
| where Activity == "TRAFFIC"
| summarize BytesReceived = sum(ReceivedBytes) by SourceIP
| order by BytesReceived desc
| take 20

Best Practices for Beginners

1. Start Small and Scale

  • Begin with 1-2 critical data sources
  • Gradually add more connectors as you gain experience
  • Focus on high-fidelity alerts first

2. Leverage Microsoft's Content

  • Use built-in analytics rules and workbooks
  • Join the Azure Sentinel community for shared content
  • Attend Microsoft security webinars and training

3. Plan Your Data Retention

  • Understand Azure Sentinel pricing model
  • Set appropriate data retention policies
  • Use data archiving for compliance requirements

4. Establish Incident Response Processes

  • Define roles and responsibilities
  • Create playbooks for common scenarios
  • Document escalation procedures
  • Practise incident response regularly

5. Monitor and Tune

  • Review analytics rule performance regularly
  • Adjust thresholds to reduce false positives
  • Archive unused rules and workbooks
  • Monitor query performance and costs

Learning Resources

Official Microsoft Resources

  • Microsoft Learn: Free online courses on Azure Sentinel
  • Azure Sentinel Documentation: Comprehensive technical guides
  • Microsoft Security Blog: Latest features and best practices
  • Azure Sentinel GitHub: Community content and samples

Hands-on Learning

  • Microsoft Defender for Cloud Labs: Free hands-on exercises
  • Azure Sentinel Training Lab: Step-by-step tutorials
  • KQL Tutorials: Interactive query learning
  • Community Workshops: Virtual and in-person training

Certifications

  • Microsoft Security, Compliance, and Identity Fundamentals (SC-900)
  • Microsoft Security Operations Analyst (SC-200)
  • Microsoft Cybersecurity Architect (SC-100)

Common Challenges and Solutions

Challenge 1: Data Ingestion Costs

Problem: Unexpected high costs due to verbose logs
Solution:

  • Use data collection rules to filter unnecessary data
  • Implement log aggregation before ingestion
  • Set up cost alerts and budgets

Challenge 2: Alert Fatigue

Problem: Too many false positive alerts
Solution:

  • Start with high-confidence rules only
  • Tune alert thresholds based on your environment
  • Use machine learning rules to reduce noise

Challenge 3: Complex KQL Queries

Problem: Difficulty writing effective queries
Solution:

  • Start with simple queries and build complexity
  • Use query templates and examples
  • Practise with sample data sets

Next Steps

Once you're comfortable with the basics:

  1. Explore Advanced Analytics: Fusion rules, UEBA, threat intelligence
  2. Automate Responses: Build sophisticated playbooks
  3. Integrate Tools: Connect ITSM, SOAR, and communication platforms
  4. Join the Community: Participate in Azure Sentinel forums and events

Conclusion

Azure Sentinel represents the future of security monitoring – cloud-native, intelligent, and scalable. While the learning curve might seem steep initially, starting with the fundamentals and gradually building your expertise will help you harness its full potential.

Remember, security is a journey, not a destination. Azure Sentinel provides the tools and intelligence you need to stay ahead of evolving threats while simplifying the complexity of modern security operations.

← Go Back