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Helicopter Racing League case study for Google certified cloud professional architect exam.

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Helicopter Racing League case study for Google certified cloud professional architect exam.
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27 авг 2024

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Комментарии : 28

@dantheputzer 3 года назад

Great breakdown of the case study! One thing that came to my mind is, that using Apigee for exposing the models is unnecessary. If I recall correctly AI Platform (or Vertex AI as it seems to be called now) has endpoints for exposing models built in.

@infolanes 3 года назад

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@infolanes 3 года назад

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@ashokkumarsivasankaran5428 3 года назад

Thanks Nitin! You explained it in detail!

@infolanes 3 года назад

Glad it was helpful!

@infolanes 3 года назад

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@vantrungnguyen6098 3 года назад

Thank you very much for this amazing video. It will be much greater if you do another one with the new TerramEarth and Mountkirk game case study :D

@infolanes 3 года назад

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@infolanes 3 года назад

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@heikoonnebrink5210 3 года назад

Hi for the transcoding pipeline you suggested to use cloud functions. They timeout after 1 min execution time by default and can be extended just to a max of 8 minutes. This will be too short for lots of video content. Assume App Engine or Cloud Run might be a petter choice as the also could be triggered by an GCS upload event..

@heikoonnebrink5210 3 года назад

small fix.. max execution time is 9 minutes ;-)

@infolanes 3 года назад

Yes, correct but my assumption here is that file will be small because it is coming via live stream. So 9 mins is sufficient for small files.

@infolanes 3 года назад

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@rashmitrathod6873 3 года назад

I too feel and completely agreed that cloud run would be a better choice considering no time constraint, serverless, event/triggered driven, and can scale to zero when no work needed.