Real-time, aggregated views across your data sources
Challenges
When organizations rely on siloed data across multiple systems, observability becomes severely compromised. Teams struggle to correlate events, identify root causes, and detect emerging issues across interdependent components.
Value Proposition
Unryo's Topology Data Fabric creates an enriched model from underlying sources, revealing hidden dependencies between elements across domains. This topology information enables powerful cross-correlation capabilities, transforming observability from basic monitoring to comprehensive understanding.
Why Topology Data Fabric?
This is a foundational step that builds a real-time data model abstracted from your infrastructure stack and monitoring tools, in which all elements are logically interconnected and where metadata semantic is consistent across domains.
With this, consumers such as our AI agents and your external systems have access to a trustable and real-time view of all the data assets, enabling strong analytics and AI-driven use-cases.
Multi-vendor and multi-layer topology
One central, unified model
The Topology Data Fabric aggregates elements, dependencies, metadata, selective metrics and events in a unified, real-time data model.
Connectors and parsers covering popular monitoring tools and multi-vendor devices, from network, storage, virtualization, 5G and clouds.
No data replication
Unryo builds the topology model without costly replication and adapts to the data source characteristics (endpoint, streaming, ...)
Open and Extensible Model
Using topology dependencies awareness, Unryo informs when a critical issue impacts other devices, important services or customers.
Rest API Access
Enable access to your systems or anyone in the company.
Enhance AI Agents
Combined with Agentic AI capabilities, this enables true end-to-end correlation, improved visibility and faster issue resolution.
Key Features
