implementing Memory Leak in Node.js 18 when Using Redis for Caching
I'm having trouble with I'm writing unit tests and I'm currently working with a memory leak scenario in my Node.js 18 application that utilizes Redis for caching frequently accessed data. My application is set up to cache API responses for a short duration, but I've noticed that the memory usage keeps increasing over time, eventually leading to a crash. I'm using the `ioredis` library to connect to my Redis instance and have implemented caching like this: ```javascript const Redis = require('ioredis'); const redis = new Redis(); async function fetchData() { const cacheKey = 'myApiData'; const cachedData = await redis.get(cacheKey); if (cachedData) { return JSON.parse(cachedData); } const freshData = await getDataFromApi(); await redis.set(cacheKey, JSON.stringify(freshData), 'EX', 3600); return freshData; } async function getDataFromApi() { // Simulated API call return new Promise(resolve => setTimeout(() => resolve({ data: 'Some data' }), 1000)); } ``` I've tried using the `--inspect` flag and analyzing the heap snapshots with Chrome DevTools, but I need to pinpoint what might be causing the leak. I suspect it might be related to holding references to objects in memory longer than necessary. I've also tried manually clearing the cache with `redis.del(cacheKey)` in case stale entries are piling up, but the scenario continues. When monitoring the application with `node --inspect`, after several hours of running, I see the resident memory grow from approximately 200MB to over 1GB, which seems excessive for my use case. Does anyone have any insights into optimizing Redis usage in Node.js or strategies for identifying memory leaks in this context? Are there known issues with `ioredis` that could cause this behavior? The project is a service built with Javascript. Is there a simpler solution I'm overlooking? For context: I'm using Javascript on Windows 10.