Cartography is a Python tool that pulls infrastructure assets and their relationships into a Neo4j graph database.
Cartography solves the problem of understanding infrastructure sprawl across cloud and on-premises environments by aggregating asset data from multiple sources into a unified graph representation. It connects to cloud providers, container platforms, and other infrastructure systems to extract resources and their relationships, then stores this information in Neo4j where it can be queried and analyzed. This graph-based approach makes it possible to discover connections between assets that would be difficult to identify in siloed systems and to answer complex questions about infrastructure topology and dependencies.
The tool is suited for organizations managing infrastructure across multiple cloud providers or hybrid environments who need visibility into asset relationships and dependencies. It works well for teams building internal tools around infrastructure discovery, compliance checking, and security analysis. Cartography is particularly valuable when you need to correlate data across different infrastructure layers—for instance, understanding which cloud resources are connected to which Kubernetes clusters, or tracing relationships between network components and applications. The Neo4j backend enables flexible querying without requiring predefined schemas, allowing teams to explore their infrastructure in ways that match their specific operational needs.
The project shows consistent development activity with regular updates to support new infrastructure sources and maintain compatibility with evolving cloud platforms. The codebase demonstrates a modular architecture where new data sources can be added as plugins, indicating an established pattern for extending functionality. Documentation is maintained alongside the code, suggesting attention to usability for new adopters. The project maintains active engagement with its user base through issue tracking and appears responsive to requests for additional infrastructure integrations.
