0 votes
1 view
in Azure by (5.8k points)

I have made an Azure Machine Learning Experiment which takes a small dataset (12x3 array) and some parameters and does some calculations using a few Python modules (a linear regression calculation and some more). This all works fine.

I have deployed the experiment and now want to throw data at it from the front-end of my application. The API-call goes in and comes back with correct results, but it takes up to 30 seconds to calculate a simple linear regression. Sometimes it is 20 seconds, sometimes only 1 second. I even got it down to 100 ms one time (which is what I'd like), but 90% of the time the request takes more than 20 seconds to complete, which is unacceptable.

I guess it has something to do with it still being an experiment, or it is still in a development slot, but I can't find the settings to get it to run on a faster machine.

Is there a way to speed up my execution?

1 Answer

0 votes
by (9.5k points)

You need to give some time for instances to execute otherwise your container will warm up inside and cause delays. 

Follow these steps to adjust the number of calls:

1. Go to manage.windowsazure.com/

2. Navigate to Azure ML section on the left-side

3. Select your workspace

4. Go to web services 

5. Select your web service

6. Now, adjust the number of calls

 

Welcome to Intellipaat Community. Get your technical queries answered by top developers !


Categories

...