Deploying ML/Deep Learning on AWS Lambda for Long-Running Training, not just Inference

Question

Deploying ML/Deep Learning on AWS Lambda for Long-Running Training, not just Inference

Cybernetic

2021年2月3日 15:20

Serverless technology can be used to deploy ML models to production, since the deployment package sizes can be compressed if too large (or built from source with unneeded dependencies stripped).

But there is also the use case of deploying ML for training, not just inference. For example, if a company wanted to allow power users to retrain a model from the front-end.

Is this feasible for Lambda given the long training times?

Whereas latency wouldn't be issue (cold start delay is fine) the runtime could be fairly long (hours).

Topic aws-lambda deep-learning machine-learning

Category Data Science

David Masip · Accepted Answer · 2021年2月3日 15:20

1

David Masip answered at 2021年2月3日 15:20

I've used ECS (Fargate) to train models, the retraining trigger could be the start of an ECS service. While ECS has a little latency, it handles well long runtimes.

You can then serve the model via a lambda.

Deploying ML/Deep Learning on AWS Lambda for Long-Running Training, not just Inference

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