While using the Flexible Environment or a dedicated Compute Engine instance 
would probably be the simplest solution, you may also consider (if 
committed to using the Standard Environment of App Engine) breaking up the 
file into several pieces are storing these in Memcache, maintaining their 
freshness as necessary (changes to the underlying model, a given file part 
being evicted from the cache).

Cheers,

Nick
Cloud Platform Community Support 

On Monday, April 24, 2017 at 5:16:18 PM UTC-4, Shachar Grembek wrote:
>
> Thanks for the suggestion, but as you mentioned, it would be too extreme 
> to redesign the architecture, just because of that
>
> On Monday, April 24, 2017 at 6:53:24 PM UTC+3, Justin Beckwith wrote:
>>
>> While I'm sure there are other options you should explore first, one idea 
>> is to look at using App Engine Flexible.  The instances in flex tend to 
>> last longer [o(days)], and the data could be cached on the instance.  
>>
>> Depending on the APIs and services you're using, a change like this could 
>> be pretty extreme, so you may want to read up on the differences here:
>> https://cloud.google.com/appengine/docs/the-appengine-environments
>>
>>
>>
>> On Mon, Apr 24, 2017 at 8:25 AM, Shachar Grembek <[email protected]> 
>> wrote:
>>
>>> Hi,
>>>
>>> I have a resource file that its size is 1.6 Mega (A Machine learning 
>>> model). The data is required and needs to be loaded for every API call I 
>>> receive, but loading the file to memory takes around 8 seconds. So I would 
>>> like to find a way to have the data available in a more efficient manner. I 
>>> considered to store the data in Memcache, but Memcache objects are limited 
>>> to 1M. I would really appreciate, if someone can help me find a way to 
>>> store it in a manner so it can be loaded it in 1 second or less.
>>>
>>> Thanks!
>>>
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>>
>>
>>
>> -- 
>>
>> Justin Beckwith | Google Cloud Platform | @justinbeckwith 
>> <http://twitter.com/JustinBeckwith> | http://jbeckwith.com
>>
>

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