Implement GDPR requirements directly in your cloud infrastructure.
RuleMesh connects GDPR IT Requirements to real cloud architecture. Each requirement includes implementation guidance for AWS, Azure, and Google Cloud so engineering teams can move directly from regulatory obligations to system configuration.
rule StorageLimitation { # Article 5(1)(e) scope: "PII_DATA", retention: 2_YEARS, on_expiry: PERMANENT_DELETE, mapping AWS::S3::Bucket { LifecycleConfiguration: { Rules: [{ ExpirationInDays: 730 }] } } }
The RuleMesh approach
Each GDPR IT Requirement is mapped to a Cloud Foundations Control that describes the technical pattern required to implement it. Provider-specific guidance then explains how to implement the control in AWS, Azure, and Google Cloud.
Structured Requirements
Each IT Requirement includes a ComplianceDSL rule, cloud control mappings, and evidence checklists — structured for both engineers and AI agents.
Provider-Specific Guidance
Cloud Foundations Controls define the architecture pattern. Provider mappings show how to implement it in AWS, Azure, or Google Cloud.
Consistent Across Platforms
Requirements remain consistent across cloud platforms while still providing provider-specific implementation guidance.
Technical Implementation Highlights
rule PrivacyByDesign { # Data Protection by Design and Default enforce: MINIMAL_PRIVILEGE, default_state: ENCRYPTED, mapping Azure::Storage::Account { properties: { supportsHttpsTrafficOnly: true, encryption: { keySource: "Microsoft.Storage" } } } }
rule SecurityOfProcessing { # Technical and organizational measures technique: PSEUDONYMIZATION, encryption_at_rest: AES_256, mapping GCP::BigQuery::Dataset { default_encryption: { kms_key_name: "projects/rulemesh/keys/primary" } } }
Example mappings
Configure retention policies to automatically delete personal data after the defined retention period expires.
S3 Lifecycle Policies, CloudWatch Logs Retention, DynamoDB TTL
Implement appropriate technical measures designed to implement data-protection principles such as data minimisation effectively and integrate safeguards into processing.
AWS Config Rules, S3 Default Encryption, RDS Encryption at Rest, Macie for data classification
Implement pseudonymisation and encryption of personal data as appropriate measures to ensure a level of security appropriate to the risk.
KMS Key Management, S3 SSE, RDS Encryption, EBS Encryption, ACM Certificate Manager
Cloud control architecture
RuleMesh organizes cloud implementation guidance in three layers: IT Requirements define what must be implemented, Cloud Foundations Controls define the architecture pattern, and Provider Mappings show how to implement it.
AWS Infrastructure
Implementation guidance for S3, RDS, IAM, Lambda, and more. Cloud control mappings cover encryption, access management, data retention, and logging across AWS services.
- check_circleS3 Bucket Policy Enforcement
- check_circleRDS Encryption-at-Rest Mandates
- check_circleVPC Flow Log Compliance
Azure Ecosystem
Native integration with Azure Policy and Blueprints for unified governance.
Google Cloud
Organization-level constraints and VPC Service Controls.
Unified Data Map
Cross-Cloud sync
Requirement Generation
RuleMesh generates structured IT Requirements from its GDPR model, each mapped to cloud controls and evidence checklists.
Implementation
Engineers or AI agents implement the controls in your cloud infrastructure using the provider-specific guidance.
Governance & Evidence
Governance checklists verify implementation. Evidence artifacts are attached to Jira tickets for audit readiness.
Implementation and governance
Once requirements are generated in Jira, engineers or AI agents implement the controls. Governance checklists verify implementation and evidence artifacts demonstrate compliance. Cloud mappings ensure the implementation step is clear and technically correct.
Ready to implement GDPR in your cloud?
Get structured GDPR requirements with cloud control mappings for AWS, Azure, and Google Cloud.