thanks Joshua... has GAE something similar to cloudfront?

I could move the S3 bucket to GAE and use the GAE's cloudfront?

I've no credits for AWS

On Thursday, August 22, 2019 at 7:12:34 PM UTC+2, Joshua Smith wrote:
>
> GAE isn’t going to serve those images any faster than S3 does (unless 
> they’re in glacier storage). 
>
> What you propose won’t be possible because of limits on the size of GAE 
> apps (10K files, max file sizes, etc.) 
>
> If you are reading the images more than once, putting a cloudfront 
> distribution between your app and the S3 bucket might help. 
>
> On Aug 22, 2019, at 8:53 AM, ALT-EMAIL Virilo Tejedor <virilo...@gmail.com 
> <javascript:>> wrote: 
> > 
> > Hi all, 
> > 
> > I'd like to create a static web server to store almost 1 TB of images. 
> > 
> > It is an opensource dataset that I'd like to use to train a Deep 
> Learning model. 
> > 
> > I have free usage of GPUs and Internet conexion in another plattform, 
> but they don't provide me 1 TB storage. 
> > 
> > I've also 600$ credits in Google Cloud, I was wondering if there was an 
> easy way to create something to feed with images the server in the other 
> plattform. 
> > 
> > The datasource is available as an AWS bucket.  I tried to connect the 
> GPU machine directly to the ASW bucket via awscli, but it is too much slow. 
>  Like if the bucket were thought for a complete sync but not for coninuous 
> random access to the files. 
> > 
> > I've though two possible approaches: 
> > 
> >         - Execute a python script in GAE to download the dataset and to 
> create a GAE web server: 
> https://cloud.google.com/appengine/docs/standard/python/getting-started/hosting-a-static-website
>  
> > 
> >         - Execute a python script in GAE to download the dataset and to 
> create a Google Cloud CDN. 
> > 
> > Do you think any of this approaches are valid to feed the model during 
> the training? 
> > 
> > I'm a newbie in GAE and any help, starting point or idea will be very 
> wellcomed. 
> > 
> > Thanks in advance 
> > 
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