Microsoft Sentinel is Microsoft’s cloud-native SIEM (Security Information and Event Management) and SOAR (Security Orchestration, Automation, and Response) solution, built on Azure Monitor Log Analytics. It’s designed to help security teams collect, detect, investigate, and respond to threats across an enterprise environment—on-premises, in the cloud, or hybrid.

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🔑 Core Capabilities

1. Data Ingestion (Log Onboarding)

• Connectors: 100+ built-in data connectors for Microsoft services (e.g., Microsoft 365, Azure AD, Defender), third-party tools (e.g., Palo Alto, CrowdStrike, AWS, Cisco), and generic sources (Syslog, CEF, JSON via APIs).
• Ingestion Methods:
  • Agents: Azure Monitor Agent (AMA), legacy Log Analytics Agent (MMA, now deprecated).
  • Direct integrations: REST APIs, Event Hubs, Azure Arc.
  • Custom logs: via HTTP Data Collector API or Data Collection Rules (DCRs).
• Schema: Uses the Azure Monitor schema (e.g., SecurityEvent, Syslog, CommonSecurityLog, AzureActivity). Custom logs map to CustomLog.

💡 Tip: Always use Azure Monitor Agent (AMA) with Data Collection Rules (DCRs)—this is the modern, scalable, and RBAC-friendly approach.

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2. Threat Detection

• Analytics Rules: Create detection logic using:
  • Scheduled queries (KQL-based)
  • Fusion (ML-driven multi-stage attack detection)
  • Microsoft Threat Intelligence
  • ML Behavior Analytics (UEBA-like)
• Workbooks: For visualization and hunting.
• Microsoft Copilot for Security (optional): AI-assisted investigation.

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3. Investigation & Hunting

• Incidents: Automatically grouped alerts with timelines, entities (users, hosts, IPs), and related events.
• Entity Graph: Shows relationships between users, devices, files, and network activity.
• KQL (Kusto Query Language): Powerful query engine for deep log analysis.
• Notebooks (Preview): For advanced threat hunting with Python + KQL.

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4. Automation & Response (SOAR)

• Automation Rules: Trigger playbooks based on incidents or alerts.
• Playbooks: Built on Azure Logic Apps—can integrate with Teams, ServiceNow, email, ticketing, EDR tools, etc.
• Custom Actions: Quarantine hosts, disable accounts, enrich data.

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5. Cost & Governance

• Pricing: Based on volume of data ingested (GB/day) and retention beyond 31 days.
• Cost Controls:
  • Use DCRs to filter at ingestion (e.g., drop verbose logs).
  • Leverage Basic Logs (cheaper, limited querying) for high-volume, low-value data.
  • Table-level pricing tiers (preview): Assign analytics vs. basic tiers per table.

⚠️ Watch out: Unfiltered Syslog or verbose application logs can cause cost spikes.

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🛠️ Best Practices for Sentinel Deployment

1. Plan Your Data Strategy:
   • Onboard only security-relevant logs.
   • Define naming and tagging standards early (e.g., Environment=Prod via DCRs).
2. Use Data Collection Rules (DCRs):
   • Replace legacy agents and workspace-centric configs.
   • Apply transformations, filters, and routing before ingestion.
3. Start with High-Value Sources:
   • Azure AD Sign-in logs
   • Microsoft Defender for Endpoint
   • Firewall/Proxy logs
   • Endpoint EDR (e.g., CrowdStrike, SentinelOne)
4. Tune Detections:
   • Suppress false positives using alert suppression rules.
   • Use watchlists for dynamic allowlists.
5. Leverage Content from GitHub:
   • Microsoft maintains Azure Sentinel GitHub repo with detection rules, parsers, playbooks, and hunting queries.

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🔗 Integration with Other Tools

• Cribl: Often used upstream to filter, parse, and route logs before sending to Sentinel (reduces cost and improves signal-to-noise).
• Microsoft Defender XDR: Native integration—alerts and incidents sync bidirectionally.
• 3rd-party SOARs: Can coexist, but Sentinel’s native Logic App-based playbooks cover most common use cases.