VAST
A data pipeline engine for security teams to collect, transform, enrich, and route telemetry data at scale.
What is VAST?
Tenzir is a data pipeline engine specifically designed for security teams to manage security telemetry dataflows at scale. It enables collection, parsing, shaping, normalization, aggregation, storage, querying, and routing of security data from numerous sources. The platform helps teams quickly onboard data, reduce volumes to optimize costs, and execute detections and analytics in-stream.
Security operations teams and security engineers who need to process, analyze, and manage large volumes of security telemetry data from multiple sources.
Tenzir provides a unified platform specifically tailored for security data workflows, offering comprehensive data pipeline capabilities with built-in cost optimization and in-stream analytics designed for security use cases.
Overview
Tenzir is the data pipeline engine for security teams.
Use Cases
Best For
- Processing and analyzing security telemetry data at scale
- Reducing cloud and data costs for security operations
- Building unified data pipelines for multiple security data sources
- Executing security detections within data streams
- Normalizing and enriching security data from diverse formats
- Routing processed security data to appropriate analytics platforms
Not Ideal For
- Teams processing non-security data like IoT sensor streams or business analytics
- Organizations with simple logging needs that don't require complex data transformations
- Projects prioritizing minimal setup and broad ecosystem support over security-specific optimizations
Pros & Cons
Pros
Integrates collection, transformation, enrichment, and routing into a single platform, specifically designed for security telemetry workflows as highlighted in the README.
Explicitly reduces data volumes to lower cloud and data costs, a key feature for managing expensive security operations data.
Enables executing security detections and analytics directly within data pipelines, supporting real-time threat hunting without separate processing steps.
Built to handle complex dataflows at scale, making it suitable for large-scale security environments with high telemetry volumes.
Cons
Tailored exclusively for security telemetry, limiting its applicability for general data engineering tasks outside the security domain.
Requires expertise in both data pipeline engineering and security operations, which can be a barrier for teams without dedicated resources.
As a specialized tool, it may have fewer community resources and integrations compared to broader solutions like Apache Kafka or Flink.
Frequently Asked Questions
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