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.
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.
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.
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.