---
title: "Comment by Алексей Спинов on \"Lessons Learned from Running Serverless Applications in Production on AWS\" | Hashnode"
description: "Great breakdown. One thing I learned running serverless scraping pipelines: cold starts compound when you chain multiple API calls. I found that keeping a warm"
url: "https://hashnode.com/posts/lessons-learned-from-running-serverless-applications-in-production-on-aws/67fe329f647f06e151034e8b/comment/69de6f65e72a4c8f1a624fe4"
---

[Discussion](https://hashnode.com/posts/lessons-learned-from-running-serverless-applications-in-production-on-aws/67fe329f647f06e151034e8b)

Comment [Lessons Learned from Running Serverless Applications in Production on AWS](https://hashnode.com/posts/lessons-learned-from-running-serverless-applications-in-production-on-aws/67fe329f647f06e151034e8b)

[Алексей Спинов](https://hashnode.com/@spinov001)

[Apr 14](https://hashnode.com/posts/lessons-learned-from-running-serverless-applications-in-production-on-aws/67fe329f647f06e151034e8b/comment/69de6f65e72a4c8f1a624fe4)

Great breakdown. One thing I learned running serverless scraping pipelines: cold starts compound when you chain multiple API calls. I found that keeping a warm pool of 2-3 functions and using connection pooling (especially for DB writes) cut our P95 latency by 60%. For anyone doing data-intensive serverless work, batching API responses before writing to storage also helps avoid those timeout surprises.