This document outlines the specifications for implementing Rate Limiting and Caching within an API that serves both REST and GraphQL endpoints. The core functionality is built upon GraphQL, which ensures flexibility for clients while maintaining a consistent data retrieval interface.
Rate Limiting
As an API provider, I want to ensure fair usage and protect the system from abuse by implementing rate limiting so that the users can experience stable and reliable service.
Acceptance Criteria
[ ] The API enforces rate limiting based on the number of requests per user per time interval.
[ ] Overstepping the rate limit results in an HTTP 429 response code.
[ ] Rate limits are configurable and can differ between different levels of user or subscription.
[ ] Users can query their current rate limit status via response headers.
[ ] Rate limiting can be bypassed or modified for specific whitelisted consumers or endpoints.
sequenceDiagram
participant User
participant API
User->>API: Sends API Request
API-->>User: Checks Rate Limit
alt Rate Limit Exceeded
API->>User: Return HTTP 429 Too Many Requests
else Rate Limit OK
API->>User: Process Request
end
Caching
To improve performance and reduce load on the system, caching mechanisms should be implemented for regularly accessed data.
Acceptance Criteria
[ ] The system caches common queries and their responses.
[ ] Cached data has a configurable time-to-live (TTL).
[ ] Cache invalidation occurs when underlying data changes.
[ ] The system supports both server-side and client-side caching strategies.
[ ] The API provides cache-related headers in responses to facilitate client-side caching.
sequenceDiagram
participant Client
participant Cache
participant API
Client->>Cache: Request Data
alt Cache Hit
Cache-->>Client: Return Cached Data
else Cache Miss
Cache->>API: Fetch Data
API-->>Cache: Store New Data
Cache-->>Client: Return New Data
end
This document outlines the specifications for implementing Rate Limiting and Caching within an API that serves both REST and GraphQL endpoints. The core functionality is built upon GraphQL, which ensures flexibility for clients while maintaining a consistent data retrieval interface.
Rate Limiting
As an API provider, I want to ensure fair usage and protect the system from abuse by implementing rate limiting so that the users can experience stable and reliable service.
Acceptance Criteria
Caching
To improve performance and reduce load on the system, caching mechanisms should be implemented for regularly accessed data.
Acceptance Criteria