S3 gateway & Data sovereignty
Data sovereignty, deterministic bucket names, and policy-driven replication for any S3-compatible backend.
For platform teams, MSPs, and organizations migrating across S3 providers or enforcing data-residency rules.
Problem
Organizations use multiple S3-compatible storage services (AWS S3, Cloudflare R2, Backblaze B2, MinIO, Ceph), but management is fragmented. Data residency rules (GDPR, data sovereignty) require certain data to remain in specific geographic locations. Vendor lock-in prevents flexibility and pricing power stays with providers. Bucket name conflicts and manual replication increase errors and workload.
Solution
We implement a unified S3 gateway interface that routes requests to the correct backends based on policies. The gateway hashes bucket names deterministically, enabling tenant isolation and avoiding name conflicts. The metadata layer stores object location, replication status, and ETag data. Automatic cross-provider replication ensures backups and disaster recovery. SigV4 authentication ensures only authorized users can access data.
How S3 gateway helps
S3 gateway removes vendor lock-in risk and ensures data residency requirements are met automatically. When data is scattered across providers and management is manual, costs increase and compliance risks grow — the gateway provides unified management and policy-driven routing.
The system enables flexibility in provider choices and automatic replication for disaster recovery purposes. Metadata management improves auditing and tenant isolation ensures security in multi-tenant environments.
Key Benefits
The organization gains full control over data and can move data between providers without vendor lock-in. Data residency requirements are met automatically based on policies. Costs are optimized by using cheaper tier providers for non-critical data. Replication and disaster recovery happen automatically. Metadata management improves auditing and compliance reporting. Tenant isolation and hashing reduce security risks.
Implementation Timeline
Implementation typically takes 4-8 weeks. The first week is spent on requirements mapping and provider configuration. The second and third weeks focus on gateway installation, metadata layer setup, and policy definition. The fourth week includes pilot testing with sample data and replication tool verification. The fifth and sixth weeks are spent integrating with existing applications and monitoring. Production usage begins gradually starting with critical data.
Technical Architecture
The gateway is built as a FastAPI application that listens for S3 API requests. The metadata layer uses a database (PostgreSQL or equivalent) to store bucket mappings, object locations, and replication status. Bucket names are hashed based on tenant ID using a deterministic algorithm. The replication worker (background worker) reads replication jobs and performs copying between providers using the boto3 library. SigV4 authentication is validated with every request. The system is container-based (Docker) and scales horizontally.
Features
S3 gateway provides a unified interface for multiple S3-compatible storage providers. Manage data across providers without vendor lock-in and ensure compliance requirements.
Key outcomes
Process
Discovery
Pilot
Integrations
Rollout
Optimization
Data & integrations
- CRM and support systems
- Documents and knowledge bases
- APIs and data sources
Security & compliance
- Processing designed for agreed privacy requirements
- Audit trail and logging
- Clear boundaries and access control
Use cases
Deterministic bucket naming
Policy-driven replication
Keys stay in the browser
FAQ
What S3-compatible providers are supported?
The gateway supports all S3-compatible providers: AWS S3, Cloudflare R2, Backblaze B2, Wasabi, MinIO, Ceph, DigitalOcean Spaces, and others. If a service supports the S3 API and boto3 library, it works with the gateway. We can also add support for new providers as needed.
How are data residency policies defined?
Policies are defined at the metadata level: e.g., "EU customer data to Frankfurt (AWS eu-central-1) or Warsaw (Cloudflare R2)". The gateway checks the tenant ID and object metadata, and routes requests to the correct provider automatically. You can define policies by country, region, or compliance requirement.
Can the gateway automate replication for backup?
Yes. The gateway can automatically replicate objects to another provider (e.g., primary AWS S3, backup Backblaze B2). The replication worker reads from metadata which objects need replication and performs copying asynchronously. You can define replica count (e.g., 2x, 3x) and target providers based on policies.
How are bucket names hashed and why is it important?
The gateway hashes bucket names deterministically using tenant ID and logical bucket name (e.g., SHA256(tenant_id + logical_name)). This ensures the same tenant always gets the same bucket name, but different tenants can't collide. Hashing also obscures bucket name structure, improving security. The metadata layer stores the mapping logical <-> hashed.
Can we migrate data from one provider to another without downtime?
Yes. The gateway enables gradual migration: new data goes to the new provider, old data is replicated in the background. The metadata layer knows where objects are located, so read requests work during migration. Once replication is complete, you can switch the primary provider without downtime. This removes vendor lock-in risk.
How does the gateway scale to large data volumes?
The gateway is stateless and can scale horizontally: add more instances as needed. The metadata layer uses a database (PostgreSQL, MySQL) that can be clustered. The replication worker can be split across multiple workers with job sharding logic. Large objects can be handled with multipart upload/download methods, reducing memory usage.
How are authentication and tenant isolation handled?
The gateway uses SigV4 authentication (AWS Signature Version 4). Each tenant receives their own access/secret key pairs, stored encrypted in the metadata layer. Requests are validated with SigV4 signature, and tenant ID drives bucket hashing and policies. Tenants are fully isolated: one cannot see another's data.
What is the cost structure?
Costs consist of: 1) Gateway development and configuration (one-time), 2) Metadata database hosting (monthly), 3) Gateway instance hosting (monthly), 4) Provider costs (data storage and transfer). The gateway itself is lightweight and consumes few resources. Savings come from being able to choose cheaper providers (e.g., R2, B2) instead of expensive ones.
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