AWS Architecture Blog·April 8, 2026Multi-Tenant Configuration Service with Tagged Storage Pattern on AWS
This article demonstrates how to build a scalable, multi-tenant configuration service using the "tagged storage pattern" on AWS. It addresses challenges like managing rapidly changing tenant metadata and scaling configuration services by using an event-driven architecture, a strategy pattern for storage, and strict tenant isolation through JWTs.
Read original on AWS Architecture BlogManaging configurations in a multi-tenant microservices architecture presents significant challenges, particularly around data isolation, cache consistency, and scaling the configuration service itself. Traditional approaches often force trade-offs between stale data and performance overhead. This article introduces the tagged storage pattern to tackle these issues, enabling flexible routing to optimized storage backends and real-time updates.
Key Architectural Components and Patterns
- Multi-Backend Storage Strategy: Utilizes Amazon DynamoDB for high-frequency, tenant-specific configurations (e.g., feature flags, payment preferences) and AWS Systems Manager Parameter Store for shared, more static parameters (e.g., API endpoints, database connection strings). This optimizes for diverse access patterns and reduces costs.
- Strategy Pattern for Storage Selection: A NestJS-based gRPC microservice implements a Strategy Pattern to dynamically select the appropriate storage backend based on configuration key prefixes. This simplifies the addition of new storage types without modifying core logic.
- Tenant Isolation: Achieved through JWT claims where the `custom:tenantId` is extracted from validated tokens, ensuring requests cannot access other tenants' data. The service never accepts tenantId from request parameters.
- Event-Driven Refresh Layer: Addresses the cache staleness problem without polling or service restarts. Amazon EventBridge monitors Parameter Store for changes, triggering AWS Lambda to update service caches, enabling near real-time configuration updates.
Data Model for Multi-Tenancy and Efficiency
The data model is crucial for both tenant isolation and query efficiency. For DynamoDB, a composite key structure using `TENANT#{tenantId}` as the partition key and `CONFIG#{configType}` as the sort key ensures tenant data co-location and efficient tenant-scoped queries. Parameter Store uses a hierarchical path structure like `/config-service/{tenantId}/{service}/{parameter}` for bulk retrieval and clear access control.
Addressing Cache Staleness and Downtime
The event-driven refresh layer is a critical design choice. Instead of costly polling or disruptive service restarts, it uses EventBridge and Lambda to notify services of configuration changes, allowing them to invalidate and refresh their local caches within seconds, achieving zero-downtime updates and improved responsiveness.
Key Technology Choices
- gRPC: Used for high-performance, type-safe service-to-service communication, reducing network bandwidth and improving response times.
- AWS Fargate & ECS: For running microservices, abstracting away underlying infrastructure management.
- Amazon Cognito: For user authentication and embedding tenant context into JWTs.
- AWS Cloud Map: For service discovery within the microservices environment.
This architectural approach provides a robust solution for multi-tenant configuration management, balancing performance, scalability, security, and operational simplicity. It highlights practical strategies for managing diverse configuration types and ensuring real-time consistency in dynamic cloud environments.