About
Cribl Search is a next-generation log investigation platform designed to help security and IT operations teams get fast answers from all their telemetry—without the cost and complexity of traditional SIEM architectures. It provides a single, unified search experience that queries data wherever it lives: cloud storage, data lakes, object stores, analytics services, and API endpoints—eliminating the need to rehydrate or move data before searching. At the core of Cribl Search is an AI-native investigation engine that understands dataset semantics, enabling conversational, plain-language querying that democratizes access to investigations beyond just expert analysts. Agentic AI guides users through intelligent pivots, surfacing patterns and root causes without requiring complex query languages. Automatic parsing reduces manual schema engineering and dramatically shortens the path from raw data to actionable insights. Cribl Search consolidates collection, storage, search, dashboards, and alerting into a single product, cutting tool sprawl and infrastructure management overhead. Workloads can be shifted off expensive legacy logging tools, reducing log management costs while maintaining speed and flexibility. Designed for enterprises facing rising query volumes from AI-driven workflows, it scales to meet modern investigation demands with an ingest-to-investigation architecture that keeps compute close to the data.
Key Features
- Unified Multi-Source Search: Query all telemetry—data lakes, object stores, cloud storage, API endpoints—through a single interface without moving or rehydrating data.
- Agentic AI Investigation: Ask questions in plain language and let AI guide investigations from start to finish, intelligently pivoting to uncover patterns and root causes automatically.
- Automatic Parsing & Schema-Free Ingestion: Data flows directly into search-optimized storage with automatic parsing, eliminating manual schema engineering and reducing investigation setup from 10–15 steps to just two.
- Consolidated Observability Stack: Collection, storage, search, dashboards, and alerting are unified in one product, removing the need to stitch together multiple tools.
- In-Place Search Without Rehydration: Eliminates costly and slow rehydration workflows by searching data where it already lives, cutting MTTR and operational overhead significantly.
Use Cases
- Security operations teams investigating incidents across distributed cloud and on-premises log sources without SIEM ingestion costs.
- IT operations reducing mean time to resolution by using AI-guided, plain-language queries instead of manual log parsing.
- Enterprises consolidating fragmented observability tools—logging, dashboards, and alerting—into a single unified platform.
- Organizations shifting log investigation workloads off expensive legacy SIEM systems to cut operational costs.
- Analysts searching historical and real-time telemetry stored in data lakes or object stores without rehydration delays.
Pros
- Dramatic Cost Reduction: Offloads workloads from expensive SIEM and legacy logging tools, directly reducing log ingestion and storage costs.
- Democratized Investigations: Plain-language AI querying lowers the barrier for non-expert team members to run investigations without mastering complex query languages.
- Fast Time to Value: Data can be onboarded in minutes with immediate searchability, enabling rapid deployment without lengthy pipeline configuration.
- No Data Movement Required: Searches data in-place across heterogeneous storage environments, avoiding rehydration delays and unnecessary data duplication.
Cons
- Enterprise-Focused Pricing: As an enterprise product, Cribl Search is not suited for small teams or individuals with limited budgets—pricing is not publicly listed.
- Ecosystem Lock-In Risk: Consolidating collection, storage, search, and alerting into one platform may create dependency on Cribl's ecosystem over time.
- Learning Curve for Advanced Features: While AI lowers the bar for basic queries, fully leveraging agentic workflows and advanced capabilities may require onboarding and training.
Frequently Asked Questions
What is Cribl Search and how does it differ from a SIEM?
Cribl Search is an AI-native log investigation platform that searches data in-place across any storage environment without requiring SIEM ingestion. Unlike SIEMs, it avoids costly data centralization and rehydration, enabling faster and cheaper investigations.
Does Cribl Search require data to be moved or rehydrated before searching?
No. Cribl Search queries data wherever it lives—cloud storage, data lakes, object stores, or API endpoints—without rehydration or data movement.
How does the AI-assisted investigation work?
Users can ask questions in plain language. Cribl's agentic AI understands dataset semantics, guides intelligent investigation pivots, and surfaces patterns and root causes automatically—no complex query language required.
Who is Cribl Search designed for?
It is primarily designed for enterprise security operations (SecOps) and IT operations teams that handle high volumes of log and telemetry data and need to reduce investigation time and logging costs.
Can Cribl Search replace my existing logging and alerting tools?
Cribl Search consolidates collection, storage, search, dashboards, and alerting in one product, making it a viable replacement for multiple point solutions, though integration with existing workflows is also supported.
