Barracuda makes security logs conversational with Genie

2026-07-06 · Source: Databricks · Field: Technology & Digital — Cybersecurity & Data Privacy, Artificial Intelligence & Machine Learning · Depth: Intermediate, short

Summary

Barracuda has launched AI-Powered Log Search, integrated into its Managed XDR dashboard, to enable security analysts, MSP technicians, and security managers to query vast security logs using natural language. This solution, built on Databricks Genie, addresses the historical bottleneck of needing SQL expertise and navigating diverse vendor schemas (e.g., WatchGuard, Fortinet, Palo Alto, Microsoft 365, AWS). By converting natural language questions like "show me failed login attempts from external IPs in the last 24 hours" into SQL, it provides results in seconds. Barracuda enriched its Unity Catalog with security-specific metadata, allowing Genie to map requests to relevant tables and fields across various firewall vendors. This has reduced time-to-insight from hours to minutes and is projected to free 83 to 100 SOC analyst hours monthly, or 1,000 to 1,200 annually, by shifting recurring requests to self-service. Crucially, multi-tenant isolation is enforced at the data layer using secure views and query validation, preventing cross-customer data access.

Key takeaway

For security analysts and MSP technicians investigating threats, Barracuda's AI-Powered Log Search fundamentally changes how you access critical security data. You can now query diverse log sources using natural language, eliminating the need for SQL expertise and reducing investigation times from hours to minutes. This shift allows you to resolve issues faster and reduces reliance on senior analysts, significantly boosting operational productivity. Consider adopting similar AI-driven conversational interfaces for your log management to empower junior staff and streamline compliance reporting.

Key insights

Barracuda's AI-Powered Log Search uses Databricks Genie and enriched metadata to enable natural language querying of diverse security logs with robust tenant isolation.

Principles

• Contextual metadata improves text-to-SQL accuracy.
• Data layer enforcement ensures multi-tenant isolation.
• Self-service log access reduces analyst workload.

Method

AI-Powered Log Search converts natural language queries into SQL using Databricks Genie, leveraging security-specific metadata in Unity Catalog, and runs them against secure views for tenant isolation.

In practice

• Implement secure views for row-level security in multi-tenant systems.
• Enrich data catalogs with domain-specific metadata for AI tools.
• Log all generated queries for audit trails and compliance (e.g., SOC 2).

Topics

• Security Operations Center
• Extended Detection and Response
• Natural Language Querying
• Databricks Genie
• Unity Catalog
• Multi-tenant Security
• Log Management

Best for: AI Security Engineer, Security Engineer, Consultant

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Editorial summary, takeaway, and curation by AIssential. Original article published by Databricks.