damagecontrolR

DamagecontrolR is an open-source toolkit for the R programming language that provides a framework for modeling, simulating, and implementing damage control strategies in data-driven environments. It is designed to help teams assess incidents quickly, specify containment and mitigation policies, and plan recovery actions in a repeatable and auditable way.

The core engine supports a policy-based approach to decision making. Users can define containment, rollback, and mitigation policies using simple rules or stateful models. The package includes modules for event detection (thresholds, statistical tests, and machine learning signals), policy evaluation, action execution (API hooks to external systems and messaging), and reporting.

DamagecontrolR employs a modular architecture with a core engine, a policy layer, data adapters, and visualization helpers. The data model covers incidents, events, containment actions, and outcomes. The design emphasizes extensibility through plug-ins and adapters for databases, queues, and monitoring dashboards.

Typical workflows involve data ingestion, anomaly detection, policy evaluation, action execution, and post-incident review. The package supports reproducible experiments via R scripts or R Markdown and can be integrated into CI/CD pipelines for testing containment policies and recovery procedures.

Development is community-driven and released under an open-source license. Versioning follows semantic conventions, and documentation provides tutorials, API references, and example use cases. The project maintains a public repository and issue tracker for contributions and governance.

Example usage can include loading data, defining a simple containment policy, running a simulated incident, and generating a report of outcomes.