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Given the architecture demands and shortcomings noted in the article, it would likely be more efficient to cut out the overhead invoked by Cloud Run and AI Platform and just run everything in Kubernetes Engine (backed by Knative for Cloud Run-esque autoscaling). This would also solve the latency and scale-to-minimum size issues, and likely be cheaper in the long term at the cost of a bit more configuration to get it started.

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Thanks for the tips. Having everything colocated in a k8s cluster will definitely help with latency and probably overall infra cost but it will be at the expense of engineering times spent on running a k8s cluster in prod.

Fingers crossed that we keep growing which would mean that we can justify working on v2 architecture.

It probably would - however we built this out with a team of 1-2 engineers, so paying a bit more and dealing with maybe 20 seconds of extra latency a day is a price we are willing to pay for expedited/easier deployment.

Thanks for the suggestion though! I'm sure we will consider that in the future :)

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