Microsoft's AI-Powered SIEM Migration Tool: A Strategic Analysis for Splunk and QRadar Transitions

Migrating from legacy SIEM platforms represents one of the most complex operational challenges in modern security operations. Traditional transitions from systems like Splunk or IBM QRadar to cloud-native platforms typically require 12-15 months of coordinated effort, involving hundreds of detection rules, diverse data sources, and maintaining continuous security coverage during the transition. At Ignite 2025, Microsoft unveiled an AI-powered SIEM migration experience designed to address these challenges, initially supporting Splunk migrations. Today, the company announced public preview support for QRadar migrations, marking a significant expansion of its migration capabilities.

The Strategic Shift: From Syntax Translation to Intent-Based Mapping

Traditional SIEM migration tools focused primarily on syntax translation—converting one platform's query language to another. Microsoft's approach fundamentally differs by employing intent-based mapping. The AI-powered tool analyzes uploaded legacy SIEM data, matches techniques and rules to out-of-the-box (OOTB) Sentinel detections, and suggests missing connectors to ensure complete coverage.

This represents a paradigm shift in how organizations approach SIEM transitions. Instead of merely translating existing rules, the tool evaluates the underlying security intent and maps it to Microsoft Sentinel's native detection capabilities. This approach not only accelerates migration but often improves detection coverage by leveraging Sentinel's advanced correlation capabilities.

The Four Pillars of the Migration Experience

The migration framework is built around four foundational pillars, each addressing critical stages of the transition:

1. Discovery & Planning: The system automatically identifies origin SIEM detections and data sources, creating an actionable inventory. This eliminates the error-prone manual analysis phase where teams traditionally relied on spreadsheets and documentation reviews. The discovery phase establishes a reliable foundation for planning and eliminates one of the most time-consuming steps in traditional migrations.

2. Detection Mapping: The AI-assisted analysis matches existing SIEM detections to Microsoft Sentinel analytics rules, highlighting supported mappings and gaps. Early adopters report significantly higher detection match rates compared to previous tools, with improved accuracy through conservative, high-confidence recommendations.

3. Data Source Integration: The tool automatically identifies and recommends data connectors required to activate selected analytics rules. This removes guesswork from onboarding and ensures teams enable the right data sources at the right time, supporting both coverage and cost-efficient ingestion.

4. Holistic SOC Engineer Experience: A comprehensive, phased onboarding process with progress tracking, onboarding targets, and SOC optimization enhancements. This pillar recognizes that SIEM migration is not a one-time event but a phased journey requiring continuous visibility and collaboration across stakeholders.

Technical Implementation and Workflow

The migration experience follows a six-step process designed to guide security teams from assessment to operational excellence:

Step 1: Automated Environment Discovery

The process begins with automatic discovery of the existing SIEM environment. Teams upload exported configurations from their legacy platform, and the system ingests this data to build an actionable inventory. This automated analysis replaces manual discovery efforts that typically require weeks of cross-team coordination.

Step 2: Migration Recommendations Review

Once the environment is analyzed, the system generates migration recommendations. Teams review the progress and outcomes, gaining visibility into the quality and completeness of recommendations. This proactive assessment reduces surprises and builds confidence as the migration journey continues.

Step 3: Guided, Use-Case-Based Planning

The experience provides a stateful, guided migration plan aligned to Sentinel solutions and SOC use cases. Teams can track progress, prioritize work, and collaborate across stakeholders with full transparency. This phased approach allows organizations to migrate gradually while maintaining operational continuity.

Step 4: Detection Matching and Enablement

One of the most challenging aspects of SIEM migration is recreating detection coverage. The AI-assisted analysis matches existing SIEM detections to Microsoft Sentinel analytics rules, highlighting supported mappings and gaps. By focusing on high-confidence, maintainable mappings, the experience helps teams migrate faster while building trust in the outcome.

Step 5: Data Connector Identification

Detections are only effective when the right data is connected. The SIEM Migration experience automatically identifies and recommends the data connectors required to activate selected analytics rules. This ensures teams enable the right data sources at the right time, supporting both coverage and cost-efficient ingestion.

Step 6: Continuous SOC Optimization

Beyond migration, the experience integrates with SOC Optimization to provide a unified view of migration progress alongside ongoing optimization recommendations. This helps organizations move seamlessly from migration into continuous improvement, maximizing the value of Microsoft Sentinel and Microsoft Defender XDR together.

Strategic Business Impact

Time-to-Value Acceleration

Early adopters report faster, streamlined migrations to Microsoft Sentinel with deeper visibility into migration progress. The guided, automated experience reduces migration time by up to 50%, helping security teams realize value faster. This acceleration translates directly to reduced operational risk during transition periods and faster realization of cloud-native security benefits.

Cost Considerations

The migration experience is powered by Security Copilot, bringing AI-assisted reasoning directly into the migration workflow. While Security Copilot must be enabled in the tenant, the migration experience itself does not consume Security Compute Units (SCUs), so customers can use it without incurring additional costs. This pricing model makes the tool accessible to organizations of various sizes.

Free Migration Support

Eligible customers receive expert hands-on assistance through the Cloud Accelerate Factory Program to quickly deploy Sentinel and migrate from Splunk and QRadar alongside their preferred partner. This program provides specialized expertise that can be critical for complex enterprise migrations.

Provider Comparison: Splunk vs. QRadar vs. Sentinel

Splunk Migration Considerations

Splunk has long been the market leader in SIEM solutions, particularly for organizations with complex, custom use cases. However, its on-premise or hybrid deployment model often results in significant infrastructure costs and operational overhead. The Microsoft migration tool addresses this by:

• Translating Splunk Search Processing Language (SPL) to Sentinel Analytics Rules
• Mapping Splunk data models to Sentinel's data ingestion model
• Recommending appropriate Azure Monitor agents and connectors
• Preserving existing detection logic while leveraging Sentinel's native AI capabilities

QRadar Migration Considerations

IBM QRadar presents different challenges, particularly around its proprietary event pipeline and rule language. The migration tool addresses QRadar-specific considerations:

• Translating QRadar's rule expressions and AQL queries
• Mapping QRadar's log sources to Sentinel data connectors
• Addressing QRadar's reference set and asset model dependencies
• Preserving QRadar's correlation capabilities while leveraging Sentinel's advanced analytics

Sentinel's Strategic Advantages

Microsoft Sentinel offers several strategic advantages that justify migration:

Cloud-Native Architecture: Built on Azure, Sentinel eliminates the need for on-premise infrastructure management and scales automatically with organizational needs.

Integrated Security Ecosystem: Sentinel integrates seamlessly with Microsoft Defender XDR, providing unified visibility across endpoints, identities, email, and cloud workloads.

AI-Powered Analytics: Built-in machine learning and AI capabilities reduce false positives and identify sophisticated threats that traditional rule-based systems might miss.

Cost-Effective Ingestion: Flexible data ingestion options and pay-as-you-go pricing can reduce total cost of ownership compared to traditional SIEM licensing models.

Migration Challenges and Mitigations

Data Source Complexity

Organizations often have dozens or hundreds of data sources, each with unique formats and ingestion requirements. The migration tool mitigates this by:

• Automatically identifying required data connectors
• Providing pre-built connectors for common data sources
• Offering guidance for custom data sources
• Recommending optimal ingestion strategies to control costs

Detection Rule Translation

Legacy SIEMs often contain hundreds or thousands of custom detection rules. The AI-powered matching system addresses this by:

• Analyzing rule logic and intent rather than just syntax
• Recommending Sentinel OOTB rules that provide equivalent or better coverage
• Highlighting gaps where custom rules are still needed
• Providing guidance for rule optimization

Operational Continuity

Maintaining security coverage during migration is critical. The phased approach allows organizations to:

• Run both systems in parallel during transition
• Gradually shift data sources and detection workloads
• Validate new detections before fully decommissioning legacy systems
• Maintain compliance and audit requirements throughout

Future Roadmap and MITRE ATT&CK Alignment

The migration experience is designed to support MITRE ATT&CK framework alignment, which is coming soon. This will enable organizations to:

• Map existing detections to ATT&CK techniques and tactics
• Identify coverage gaps across the ATT&CK matrix
• Prioritize migration efforts based on threat coverage
• Measure security posture improvement post-migration

Getting Started

To begin using the new SIEM Migration experience:

1. Ensure Microsoft Sentinel is enabled in the Microsoft Defender portal
2. Enable Security Copilot in your tenant
3. Navigate to SOC Optimization → Set up your new SIEM
4. Upload your Splunk or QRadar exported SIEM configuration data
5. Follow the guided experience through the six-step process

For detailed instructions, refer to the official documentation.

Conclusion

Microsoft's AI-powered SIEM migration experience represents a significant evolution in how organizations approach cloud security transitions. By moving beyond simple syntax translation to intent-based mapping and automated planning, the tool addresses the fundamental challenges that have historically made SIEM migrations complex, time-consuming, and risky.

For organizations considering a move from Splunk or QRadar to Microsoft Sentinel, this tool provides a structured, AI-assisted pathway that can reduce migration time by up to 50% while improving detection coverage. The integration with Security Copilot and the SOC Optimization framework ensures that the migration is not just a technical transition but a strategic step toward a more modern, efficient security operations center.

The public preview of QRadar support expands the tool's applicability, making it relevant to a broader range of organizations. As the tool matures and gains broader provider support, it has the potential to reshape the SIEM migration market, making cloud transitions more accessible and less risky for security teams worldwide.

For organizations ready to begin their migration journey, the combination of automated tooling, expert support through the Cloud Accelerate Factory Program, and the strategic advantages of Microsoft Sentinel's cloud-native architecture provides a compelling case for modernization.

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Learn More:

• Use the SIEM migration experience - Microsoft Sentinel
• Microsoft Sentinel Blog
• Microsoft Sentinel Official Page