Optimizing a Slow ML Inference API: Lessons Learned
When I started working with Inference, I quickly realized there was a gap between theory and what actually happens in practice. This post is about how i optimised a slow ml inference api. I'll walk you through what I learned, what tripped me up, and the lessons that stuck with me. No fluff — just honest notes from someone who went through it. Introduction to Optimizing a Slow ML Inference API I still recall the frustration of dealing with a slow ML inference API. The latency was unbearable, and it seemed like no matter what I did, I just couldn't get the performance I needed. But after weeks of trial and error, I finally managed to optimize the API and achieve significant improvements. In this article, I'll share my experience, the mistakes I made, and the lessons I learned along the way. The Initial Challenges When I first started working on the ML inference API, I was excited to see it in action. However, my enthusiasm was short-lived. The API was slow, and the laten...