I do not have much experience dealing with Argon2ID. However, the scaling 
behavior of your App Engine instance depends on how you set it up as well 
as which environment of App Engine it is running in. Since you mentioned 
you are running on standard, you will notice that scaling of the 
application will be rapid. I believe it would be worth to check the 
following documentation here 
<https://cloud.google.com/appengine/docs/standard/python/how-instances-are-managed>
 
out as it pertains to how instances are managed on standard. You will see 
that you can set a array of attributes to allow the app to scale the way 
you prefer by either Manual , Automatic, Basic scaling. 
<https://cloud.google.com/appengine/docs/standard/python/how-instances-are-managed#instance_scaling>
 As 
you mentioned that Argon2Id  "is both memory and CPU intensive"as well as 
automatic scaling, you can set certain parameters of automatic scaling such 
as:  Target CPU Utilization 
<https://cloud.google.com/appengine/docs/standard/python/config/appref#automatic_scaling_target_cpu_utilization>
, Target Throughput Utilization 
<https://cloud.google.com/appengine/docs/standard/python/config/appref#automatic_scaling_target_throughput_utilization>
, Max Concurrent Requests 
<https://cloud.google.com/appengine/docs/standard/python/config/appref#max_concurrent_requests>
. 

Lastly, you may set the the app.yaml 
<https://cloud.google.com/appengine/docs/standard/python/how-instances-are-managed#instance_scaling>
 
file to specify the *scaling type* and* instance class* of the version you 
deploy on App Engine. *Scaling type* controls how instances are created 
while the *instance class* determines the compute resources such as memory 
size and CPU speed. You may feel free to explore more information about 
this here 
<https://cloud.google.com/appengine/docs/standard/python/how-instances-are-managed#instance_scaling>
. 

I hope I was able to help with the scaling part of your question!


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