Guardrail Enforcement Engine for Imported Resource Compliance
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Solution Overview
Problem
Existing computing resource development processes face inefficiencies due to security scans and policy compliance bottlenecks, leading to network and compute bloat, particularly when importing resources that do not adhere to established policies.
Innovation Solution
A policy enforcement service utilizing generative artificial intelligence (AI) tools to enforce guardrails on computing resources, ensuring compliance through blueprint management, owner identification, and resource configuration adjustments, leveraging machine learning models for policy definition and reconciliation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If security scans and policy compliance reviews are performed on imported computing resources, then resource compliance and security are improved, but developer productivity and processing speed deteriorate due to bottlenecks
Solution Approach 1:
The system performs policy compliance checks and security scans during the resource import process itself, rather than as separate post-import steps. The policy enforcement service evaluates resources against defined policies before they are fully integrated into the environment, preventing non-compliant resources from being deployed and eliminating subsequent remediation cycles
Solution Approach 2:
A policy enforcement service acts as an intermediary component between the resource import process and the existing security/scanning infrastructure. This service automatically evaluates imported resources against defined policies, generates compliance reports, and coordinates with vulnerability scanning services, thereby streamlining the overall compliance verification process without requiring manual intervention at each stage
2Reliability
If comprehensive security scans are conducted on imported resources, then security issues are detected, but network and compute bloat increases due to unnecessary communications and processing
Solution Approach 1:
The policy enforcement service performs targeted policy-specific evaluations on imported resources rather than conducting exhaustive security scans on all resources. By focusing only on the specific policy requirements (e.g., authorized geographical locations, PII security configurations), the system achieves sufficient compliance verification without the overhead of comprehensive security scanning on every imported resource
Solution Approach 2:
The system performs preliminary policy compliance checks during import that identify and filter out obviously non-compliant resources before they undergo full security scanning. This preliminary filtering prevents unnecessary security scan communications and processing for resources that will be rejected anyway, reducing overall network and compute bloat
3Reliability
If manual policy compliance reviews are performed by operations teams, then policy adherence is ensured, but processing time and operational complexity increase
Solution Approach 1:
The policy enforcement service enables automated self-service policy compliance verification. The service automatically retrieves resource configurations, evaluates them against defined policies, generates compliance reports, and communicates results to developers without requiring manual review by operations teams. This automation maintains policy adherence while eliminating the time loss associated with manual reviews
Solution Approach 2:
The system implements automated feedback loops where the policy enforcement service continuously monitors imported resources, evaluates compliance status, and provides real-time feedback to developers. This automated feedback mechanism replaces manual review processes, ensuring policy adherence while significantly reducing processing time through continuous automated evaluation rather than batch manual reviews
Data Source
AI summary
A policy enforcement application receives input specifying policy constraints for resources of a given type. The application imports a pre-existing resource into the policy enforcement application, and determines, by the policy enforcement application, that the pre-existing resource is of the given type. Responsive to determining that the pre-existing resource is of the given type, the application determines that the pre-existing resource does not comply with the policy constraints. The application determines an owner of the resource based on metadata associated with the resource, and prompts the owner with a set of recommended configuration changes. Responsive to receiving a selection of a selectable option from the owner, the application reconfigures the resource with the recommended configuration changes.