🗄️ Implement Caching Layer for Gas Queries #67
Description
📌 Overview
Frequent gas queries can overload RPC nodes, leading to higher latency and potential rate-limiting issues. Caching responses improves performance, reduces backend load, and ensures consistent data delivery.
This task introduces a caching layer for gas queries using Redis to optimize GasGuard API responsiveness and reliability.
🎯 Objective
Build a system that:
- Caches gas query results to reduce repeated RPC calls
- Provides configurable cache expiration per endpoint or chain
- Maintains data accuracy while improving response times
- Lowers API latency and backend resource usage
🛠 Scope of Work
1️⃣ Caching Implementation
- Integrate Redis as caching backend
- Cache gas query results:
- Base fee, priority fee, max fee
- Chain-specific metrics
- Volatility or analytics data if frequently requested
- Support configurable TTL (time-to-live) per query type
- Implement cache invalidation for outdated data
2️⃣ API Integration
-
Intercept gas query endpoints to:
- Check cache before making RPC call
- Serve cached data if available
- Update cache when RPC response is retrieved
-
Example pseudo-flow:
Client -> API Endpoint -> Redis Cache? -> Return Cached / Fetch from RPC -> Store in Cache -> Return Response
3️⃣ Metrics & Monitoring
- Track cache hit/miss rates for each endpoint
- Optional integration with Prometheus for cache performance monitoring
- Log cache failures or Redis connection issues for diagnostics
4️⃣ Security & Access
- Redis access secured via authentication
- Cache only non-sensitive public data (gas queries)
- Logging for operational transparency
🧰 Suggested Tech Stack
Core
- TypeScript
- Node.js
- Redis (in-memory caching)
- ioredis or node-redis library
- Express / Fastify / NestJS
Optional Enhancements
- Prometheus metrics for cache efficiency
- Redis cluster for high availability and scalability
- Jest (unit testing)
🧠 Implementation Expectations
- Clear separation between:
- RPC query layer
- Redis caching layer
- API response layer
- Efficient cache lookup and invalidation logic
- Unit tests covering:
- Cache hit/miss behavior
- TTL expiration
- RPC fallback when cache unavailable
- Multi-chain and multi-endpoint queries
📊 Deliverables
- Redis caching layer integrated with gas query endpoints
- Configurable TTL and cache invalidation logic
- Metrics and logging for cache performance
- Documentation explaining:
- Cache usage
- TTL configuration
- Operational monitoring
- Unit tests (minimum 70% coverage)
- Updated README
🏷 Difficulty Level
Intermediate
Ideal for contributors with:
- Backend TypeScript experience
- Knowledge of caching strategies and Redis
- Understanding of multi-chain gas query patterns
- Performance optimization mindset
🕒 Estimated Time
24hrs (part-time contributor)
✅ Acceptance Criteria
- Gas queries return cached data when available
- RPC calls reduced due to effective caching
- Configurable TTL implemented
- Metrics and logging operational
- Documentation updated
- All tests passing
🎯 Expected Outcome
GasGuard achieves lower latency and reduced RPC load, ensuring faster responses and more reliable gas data delivery for clients and dApps.