NestJS UniswapV2 & Gas Price API

A high-performance NestJS application providing Ethereum gas prices and UniswapV2 swap calculations.

Features

• Ethereum Gas Price API
  • Fast, production-ready endpoint for current gas prices
• UniswapV2 Swap Calculations
  • Get swap rates and output amounts for any token pair
• Redis Caching
  • Fetch the gas price with low latency

Prerequisites

• Node.js 20+
• Redis
• Alchemy API Key

Installation

1. Clone the repository
2. Copy .env.example into .env
3. Provide ALCHEMY_API_KEY
4. Install dependencies:

pnpm install

Run

pnpm start:dev

Running Tests

Run all tests locally:

pnpm test

Or view the latest test results in GitHub Actions.

Testing Endpoints

Gas price

curl -X GET "http://localhost:3000/api/v1/gasPrice" | jq

Uniswap

curl -X GET "http://localhost:3000/api/v1/return/0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48/0xc02aaa39b223fe8d0a0e5c4f27ead9083c756cc2/100" | jq

Performance Optimization Proposal: 5ms Gas Price API

Goal

Transform gas price endpoint to achieve <5ms response times for production-ready, high-frequency applications.

Current vs Proposed Performance

Scenario	Current	Proposed	Improvement
Cache Hit	10-30ms	0.1-2ms	15x faster
Cache Miss	200-500ms	0.1-2ms*	200x faster
P95 Response	50ms	<5ms	10x faster

*After initial warmup

Key Technical Improvements

1. Multi-Layer Caching

Memory Cache (0.1ms) → Redis Cache (2-5ms) → Blockchain RPC (200ms+)

2. Stale-While-Revalidate

• Return cached data instantly
• Refresh in background
• Zero user-facing cache misses

3. Cache Warming

• Background refresh every 10s
• Cache always ready on startup
• Eliminates cold start delays

4. Performance Monitoring

• Track response times per request
• Monitor cache hit ratios
• Alert on performance degradation

Implementation Plan

Phase 1: Enhanced Cache Layer

• Add in-memory caching to existing CacheService
• Implement LRU eviction and stale-while-revalidate

Phase 2: Background Refresh Service

• Create GasPriceCacheService with active warming

Phase 3: Monitoring & Optimization

• Performance middleware and metrics
• Production configuration tuning

Current Architecture Analysis

Strengths

• Clean modular architecture with SoC
• Redis integration for gas price caching with TTL management
• Global exception filter and logging interceptor
• Class-validator integration with transformation
• Containerized with non-root user security
• Unit tests for core services

Architectural Decisions

1. Caching

Current Decision: Simple Redis caching with 30s TTL for gas prices

Why: Reduces blockchain RPC calls and improves response times

Limitation: Basic caching without cache warming or invalidation strategies

2. Blockchain

Current Decision: Single provider (Alchemy) with simple connection

Why: Simple setup and reliable service

Limitation: No failover, rate limiting, or connection pooling

3. Configuration

Current Decision: Environment variables with basic defaults

Why: Standard 12-factor app approach

Limitation: No validation, secrets management, or environment-specific configs

4. Error Handling

Current Decision: Global exception filter with basic logging

Why: Centralized error handling and consistent API responses

Limitation: No structured logging, error tracking, or alerting

Production-Ready Improvements

1. Better configuration

• Environment-specific configuration files
• Secrets management
• Configuration validation on startup
• Rate limiting configuration per environment

2. Resilient Blockchain

• Multiple RPC provider endpoints
• Circuit breaker pattern for failed providers
• Connection pooling/retry mechanisms
• Provider health monitoring

3. Caching Strategy

• Cache warming to prevent cold cache hits
• Multi-level caching (memory + Redis)
• Cache metrics and monitoring

4. Monitoring

• Structured logging with request IDs
• Health checks with dependency status
• APM integration for request tracing
• Error tracking (Sentry)

5. API Security/Rate Limiting

• API rate limiting per endpoint/user
• Request/response validation with validation library
• API key authentication
• Request size limits

6. Data Persistence

• Database for analytics and historical data

7. Testing

• Integration tests
• Load testing with realistic traffic
• End-to-end testing pipeline

8. Infrastructure

• Kubernetes deployment with HPA
• Multi-environment deployment pipeline