Develop a comprehensive audit logging API system that tracks and manages user actions across different applications. This system should be designed to handle high-volume logging, provide search and filtering capabilities, and ensure data integrity and security.
- Log Entry Creation: API endpoints to create audit log entries with metadata
- Structured Data: Each log entry should include:
- User ID and session information
- Action performed (CREATE, UPDATE, DELETE, VIEW, etc.)
- Resource type and ID (e.g., "user", "order", "product")
- Timestamp with timezone
- IP address and user agent
- Before/after state changes (for modifications)
- Custom metadata fields
- Severity level (INFO, WARNING, ERROR, CRITICAL)
- Tenant ID: Multi-tenant support for multiple applications/organizations
- Advanced Search: Filter logs by date range, user, action type, resource type, severity, tenant ID
- Full-text Search: Search through log messages and metadata
- Pagination: Handle large result sets efficiently
- Export Functionality: Export logs in JSON, CSV formats
- Real-time Log Streaming: WebSocket endpoint for real-time log monitoring
- Tenant Isolation: Ensure complete data isolation between tenants
- Data Retention: Configurable retention policies (e.g., keep logs for 90 days)
- Data Archival: Move old logs to cold storage
- Data Compression: Efficient storage for large log volumes
- Backup and Recovery: Automated backup procedures
- API Gateway: Choose between AWS API Gateway or Application Load Balancer based on requirements
- RESTful API following OpenAPI 3.0 specification
- Authentication: JWT-based authentication
- Authorization: Role-based access (Admin, Auditor, User) with tenant-based access control
- Rate Limiting: Prevent API abuse
- Request Validation: Input sanitization and validation
- Error Handling: Proper HTTP status codes and error messages
- Search Integration: OpenSearch for advanced search capabilities
- Multi-tenancy: Support for multiple tenants with complete data isolation
- Database Choice: Select one of the three options based on your preference and requirements:
- PostgreSQL + TimescaleDB: Optimized for time-series data with efficient partitioning
- MongoDB: Document-based storage with flexible schema for audit logs
- DynamoDB: Serverless NoSQL with automatic scaling and built-in encryption
- Multi-tenant Schema: Design schema to support multiple tenants with proper isolation
- Optimized Schema: Design for high-volume writes and complex queries based on your chosen database
- Indexing Strategy: Efficient indexes for search operations (database-specific) including tenant-based indexes
- Data Partitioning: Consider time-based and tenant-based partitioning for large datasets
- Connection Pooling: Handle concurrent requests efficiently
- High Throughput: Handle 1000+ log entries per second
- Low Latency: Sub-100ms response times for search queries
- Message Queue: AWS SQS for background task processing and data archival
- Async Processing: Background tasks for data archival and cleanup using SQS
- Data Encryption: Encrypt sensitive log data at rest
- Access Control: Fine-grained permissions for log access with tenant isolation
- Audit Trail: Log access to the audit logs themselves
- Data Masking: Mask sensitive information in logs (PII, passwords)
- Tenant Isolation: Complete data isolation between tenants at all levels
- Cross-tenant Protection: Prevent data leakage between tenants
- Framework: Django or FastAPI
- API Gateway: Choose one of:
- AWS API Gateway (for serverless, managed API management)
- Application Load Balancer (ALB) (for traditional load balancing)
- Database: Choose one of:
- PostgreSQL with TimescaleDB extension (for time-series data)
- MongoDB (for document-based storage)
- DynamoDB (for serverless, scalable NoSQL)
- Message Queue: AWS SQS for background task processing
- Search: OpenSearch (optional, for advanced search capabilities)
POST /api/v1/logs # Create log entry (with tenant ID)
GET /api/v1/logs # Search/filter logs (tenant-scoped)
GET /api/v1/logs/{id} # Get specific log entry (tenant-scoped)
GET /api/v1/logs/export # Export logs (tenant-scoped)
GET /api/v1/logs/stats # Get log statistics (tenant-scoped)
POST /api/v1/logs/bulk # Bulk log creation (with tenant ID)
DELETE /api/v1/logs/cleanup # Cleanup old logs (tenant-scoped)
WS /api/v1/logs/stream # Real-time log streaming (tenant-scoped)
GET /api/v1/tenants # List accessible tenants (admin only)
POST /api/v1/tenants # Create new tenant (admin only)
graph TB
subgraph "Client Applications"
App1[Application 1<br/>Tenant A]
App2[Application 2<br/>Tenant B]
App3[Application 3<br/>Tenant C]
end
subgraph "API Gateway Layer"
APIGateway[AWS API Gateway]
ALB[Application Load Balancer]
end
subgraph "Audit Log API"
Auth[Authentication]
TenantAuth[Tenant Authorization]
RateLimit[Rate Limiting]
end
subgraph "Core Services"
LogService[Log Service<br/>Multi-tenant]
SearchService[Search Service<br/>Tenant-scoped]
ExportService[Export Service<br/>Tenant-scoped]
StreamService[Stream Service<br/>Tenant-scoped]
end
subgraph "Data Layer"
PostgreSQL[(PostgreSQL + TimescaleDB<br/>Tenant-partitioned)]
MongoDB[(MongoDB<br/>Tenant-collections)]
DynamoDB[(DynamoDB<br/>Tenant-partitioned)]
OpenSearch[(OpenSearch<br/>Tenant-indices)]
end
subgraph "Message Queue"
SQS[AWS SQS<br/>Tenant-queues]
end
subgraph "Background Services"
Workers[SQS Workers<br/>Tenant-aware]
Cleanup[Data Cleanup<br/>Tenant-scoped]
Archive[Data Archival<br/>Tenant-scoped]
end
App1 --> APIGateway
App1 --> ALB
App2 --> APIGateway
App2 --> ALB
App3 --> APIGateway
App3 --> ALB
APIGateway --> Auth
ALB --> Auth
Auth --> TenantAuth
TenantAuth --> RateLimit
RateLimit --> LogService
RateLimit --> SearchService
RateLimit --> ExportService
RateLimit --> StreamService
LogService --> PostgreSQL
LogService --> MongoDB
LogService --> DynamoDB
SearchService --> OpenSearch
ExportService --> PostgreSQL
ExportService --> MongoDB
ExportService --> DynamoDB
LogService --> SQS
Workers --> SQS
Cleanup --> SQS
Archive --> SQS
sequenceDiagram
participant Client as Client App<br/>(Tenant A)
participant Gateway as API Gateway/ALB
participant Auth as Auth Service
participant TenantAuth as Tenant Auth
participant Log as Log Service
participant DB as Database (Tenant A)
participant SQS as AWS SQS
participant Search as OpenSearch
participant Worker as SQS Worker
Client->>Gateway: POST /api/v1/logs<br/>(tenant_id: A)
Gateway->>Auth: Validate JWT Token
Auth-->>Gateway: Token Valid
Gateway->>TenantAuth: Validate Tenant Access
TenantAuth-->>Gateway: Tenant Access Granted
Gateway->>Log: Create Log Entry (Tenant A)
Log->>DB: Store Log Entry (Tenant A)
Log->>SQS: Queue Background Tasks (Tenant A)
Log-->>Gateway: Log Created
Gateway-->>Client: 201 Created
Note over SQS,Worker: Background Processing (Tenant A)
SQS->>Worker: Process Background Tasks
Worker->>Search: Index for Search (Tenant A)
Worker->>DB: Data Cleanup/Archival (Tenant A)
Note over Client,Search: Real-time Streaming (Tenant A)
Client->>Gateway: WS /api/v1/logs/stream<br/>(tenant_id: A)
Gateway->>Log: Subscribe to Stream (Tenant A)
Log->>Client: Real-time Log Updates (Tenant A)
- Unit Tests: >85% code coverage
- Integration Tests: API endpoint testing
- Performance Tests: Load testing with realistic data volumes
- Security Tests: Authentication and authorization testing
- API Documentation: OpenAPI/Swagger documentation
- Setup Instructions: Clear deployment and configuration guide
- Architecture Diagram: System design and data flow
- Code Documentation: Inline comments and docstrings
- Alert System: Configure alerts for specific log patterns
- Dashboard: Simple web interface for log visualization
- Log Analytics: Basic analytics and reporting
- Log Correlation: Group related log entries by request ID
- Git Repository: Clean, well-structured code
- README: Comprehensive setup and usage instructions
- API Documentation: Complete endpoint documentation
- Postman Collection: Test the API endpoints
- Architecture Diagram: System design overview
- Live Demo: Deployed application (optional)
- Code Structure: Clean, maintainable, and well-structured code
- API Design: RESTful principles, proper error handling, validation
- Database Design: Efficient schema design and query optimization with multi-tenant support
- Multi-tenancy: Proper implementation of tenant isolation and access control
- Technical Decisions: Justification of technology choices and architecture
- High Throughput: Ability to handle 1000+ log entries per second
- Low Latency: Sub-100ms response times for search queries
- Message Queue: Effective use of AWS SQS for background processing
- Database Optimization: Efficient design and query performance for chosen database
- Authentication: Proper JWT-based authentication implementation
- Authorization: Role-based access control and fine-grained permissions with tenant isolation
- Data Protection: Encryption at rest and in transit
- Input Validation: Proper sanitization and validation of all inputs
- Tenant Isolation: Complete data isolation between tenants
- Test Coverage: >85% code coverage with comprehensive testing
- API Documentation: Complete OpenAPI/Swagger documentation
- Setup Instructions: Clear deployment and configuration guide
- Code Documentation: Inline comments and comprehensive docstrings
- Complex Requirements: Ability to handle complex requirements efficiently
- Creative Solutions: Innovative approaches to technical challenges
- Database Choice: Justification and implementation of chosen database technology
- API Gateway Choice: Selection and implementation of API Gateway or ALB
- SQS Integration: Effective use of AWS SQS for background processing
- OpenSearch Integration: Implementation of advanced search capabilities
- Multi-tenancy: Effective implementation of tenant isolation and access control
- Bonus Features: Implementation of optional advanced features
- Performance Optimization: Creative solutions for performance challenges
This challenge is designed to be completed in 3-5 business days:
- Set up project structure and technology stack
- Choose and configure database (PostgreSQL/MongoDB/DynamoDB)
- Set up API Gateway or ALB
- Implement core audit log management features
- Design and implement database schema
- Create basic API endpoints
- Set up AWS SQS for background processing
- Configure OpenSearch for search capabilities
- Implement search, filtering, and export functionality
- Add real-time streaming capabilities
- Implement security and authentication
- Create comprehensive test suite
- Complete API documentation
- Create architecture diagrams
- Final testing and optimization
- Prepare submission materials
Focus on delivering a working MVP with core features rather than implementing all bonus features.
- Core audit log creation and retrieval API endpoints
- Database setup and configuration (PostgreSQL/MongoDB/DynamoDB)
- API Gateway or ALB setup and configuration
- Basic search and filtering functionality
- Database schema design and implementation with multi-tenant support
- Authentication and authorization system with tenant isolation
- Basic security controls and data validation
- AWS SQS setup for background processing
- OpenSearch setup for search capabilities
- Multi-tenant implementation and tenant management
- Advanced search with full-text capabilities using OpenSearch
- Real-time log streaming via WebSocket
- Data retention and archival policies using SQS
- Performance optimization and database-specific tuning
- Comprehensive test coverage
- SQS worker implementation for background tasks
- API Gateway/ALB advanced features (rate limiting, caching)
- Export functionality (JSON, CSV)
- Dashboard and visualization interface
- Advanced analytics and reporting
- Alert system for log patterns
Any questions you may have, please contact us by e-mail.
Good luck! 🚀