What is a Monthly Active Principal (MAP) and how does it affect pricing?
A Monthly Active Principal (MAP) refers to any unique user or service (human or non-human identity) that requests authorization decisions within a calendar month. Cerbos pricing is primarily based on the number of these MAPs, with different tiers offering varying allowances.
Can Cerbos Hub be self-hosted?
Yes, the Enterprise plan for Cerbos Hub offers an option for self-hosted deployment, providing greater control and customization for organizations with specific infrastructure requirements.
How does Cerbos ensure compliance with regulations like GDPR and HIPAA?
Cerbos generates detailed, audit-ready logs for every access decision, capturing requests, actions, resources, and the exact policy version used. This centralized and structured logging provides complete visibility into identity access actions, simplifying audits and ensuring compliance with regulations such as GDPR, SOC 2, HIPAA, PCI DSS, and ISO 27001.
What is the difference between Cerbos PDP and Cerbos Hub?
Cerbos PDP is the open-source authorization engine that evaluates and applies fine-grained access control policies. Cerbos Hub is the central control plane that provides complete authorization management, including policy creation, testing, deployment, and compliance visibility, working in conjunction with the PDPs deployed in your environment.
Can I integrate Cerbos with my existing Git provider and CI/CD pipeline?
Yes, Cerbos supports flexible policy delivery, allowing you to manage and deploy policies from your existing Git provider, any CI/CD pipeline, the Cerbos Hub API, or directly through the Cerbos Hub interface. It also includes automated policy validation within its CI pipeline.
Does Cerbos support authorization for AI agents and RAG systems?
Yes, Cerbos provides specific authorization capabilities for AI systems, including dynamically controlling access for AI agents to MCP server tools and maintaining data security and compliance with fine-grained authorization for RAG (Retrieval Augmented Generation) and LLMs.