CloudQuery Policies
A policy-as-code solution for managing security, governance, and compliance across cloud infrastructures.
| Category | Compliance & Governance |
|---|---|
| Last Commit | 1 year ago |
| This page updated | a month ago |
| Pricing Details | Free and open-source with community support. |
| Target Audience | DevOps teams, security professionals, compliance officers. |
CloudQuery addresses the complex challenge of managing and enforcing security, governance, and compliance policies across diverse cloud infrastructures by introducing a policy-as-code approach. This is achieved through the CloudQuery Policies feature, which allows users to codify, version, and execute rules using SQL.
The technical architecture of CloudQuery Policies leverages a multi-layered approach. Policies can be written in HCL or JSON for the logical layer and SQL for the query layer, enabling users to define and execute specific queries or sub-policies via the CloudQuery CLI. The system supports native GitHub integration, allowing policies to be downloaded and run directly from GitHub repositories. This facilitates version control and collaboration. Additionally, users can create complex SQL views that can be referenced in subsequent queries, enhancing the flexibility and reusability of policy definitions.
Operationally, CloudQuery is designed for high-performance data ingestion and processing, utilizing Go's concurrency model and Apache Arrow for efficient data streaming over gRPC. This architecture ensures low memory footprint and high scalability, making it suitable for large-scale cloud environments. However, this approach also means that the system can be resource-intensive, particularly when handling large volumes of data or complex queries. Users need to consider the scalability and performance implications when deploying CloudQuery across multiple cloud providers and large datasets.
From a technical standpoint, CloudQuery's policy execution is highly customizable, with features like inline policy functions that allow dynamic query definitions and the ability to outsource query definitions to external files. This flexibility is balanced by the need for careful management of policy versions and dependencies, especially when integrating with multiple cloud providers and other data sources. The system's stateless plugins and horizontal scaling capabilities help mitigate some of these operational complexities, but they also require careful planning and monitoring to ensure optimal performance.