[munns]

The issue of the application artifact size is definitely real and it blocks some NLP/ML workloads for sure. Consider that a today problem that isn't hard in Lambda.

But we've 100% got customers doing near realtime streaming analytics in complicated pipelines feeding off of things like Kinesis Data Streams. This FINRA example is one datapoint: https://aws.amazon.com/solutions/case-studies/finra-data-val... and this Thompson Reuters one: https://aws.amazon.com/solutions/case-studies/thomson-reuter...

These are nontrivial and business critical workloads.

Thanks, - Chris Munns - AWS - Serverless - https://twitter.com/chrismunns

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Missosoup i see you making changes to your comment and it greatly changes the tone/context. i won't adjust my own reply in suit but leave it as it was for your original comments on this.

[missosoup]

I'm not going to make any elaborations on my comment now. Please feel free to edit yours or post another to answer anything I raised. Your original reply containing some generic sales brochures isn't what I expected from someone representing aws stepping into this discussion.