Quick Example Deploying ML REST API with FastAPI, Docker, and ECS

Опубликовано: 16 Декабрь 2022
на канале: Gus Cavanaugh
2,830
27

I've been scared of docker in the past. Even during the height of the k8s kraze, I rarely ran individual containers. Instead I would create an unnecessary cluster to run my image.

In the context of CI/CD for ML, I'm developing a new appreciation. In this example, I have a simple API for my model using FastAPI (I used to use Flask but I'm trying to get with the times - FastAPI seems sweet).

I then wrote a simple Dockerfile for my app, uploaded the image to dockerhub, and deployed the API with ECS. "Hey ECS, run this docker image" - works pretty well. GCP, Azure, and all the other clouds all have great ways to deploy containers.

This isn't to make a case for VMs, K8s, or anything else, but in the context of "how do I repeatedly and reliably build a web service for my ML project" using one of these services as part of a CD pipeline is super handy. My previous fears were unfounded.

Connect with me on LI:   / gustafrcavanaugh  


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