policyEngines

PolicyEngines are software components that evaluate declarative rules against contextual data to produce automated decisions, such as permitting or denying an action. They separate policy specification from application logic, enabling centralized governance, compliance traceability, and dynamic policy updates without redeploying services.

In typical deployments, a policy decision point (PDP) evaluates requests against a policy set and data attributes provided by a policy information point (PIP). A policy enforcement point (PEP) enforces the PDP's decision at the point of access, API gateway, service mesh, or application. Policies may reference attributes from users, resources, environment, or runtime context and may include obligations to be executed alongside the decision.

Policy models include attribute-based access control (ABAC), role-based access control (RBAC), and more expressive forms. Policy languages include Rego (used by the Open Policy Agent) and XACML for standardized engines. Many engines support policy versioning, testing, and policy composition.

Common use cases include cloud and API authorization, Kubernetes admission control, data governance and privacy enforcement, and runtime security controls in microservices. Policy engines can integrate with identity providers, service meshes, and cloud IAM services to provide centralized decision making.

Key design considerations include performance and scalability of evaluation, determinism and auditability of decisions, cache strategies, and change management to avoid policy drift. Security of the policy store and separation of duties are also important.