title: Azure ML batch execution latency
body: <p>After reading this post here: <a href="https://stackoverflow.com/questions/34990561/azure-machine-learning-request-response-latency/35020997#35020997?newreg=18fbd305056d4e6ba239783ebefb9629">Azure Machine Learning Request Response latency</a>
  and the article mentioned in the comments I was wondering if this behavior is also true when a published webservice is called in batch mode. 
  Especially since I have read somewhere (sorry, can't find the link at the moment) that the batch calls are not influenced by the "concurrent calls" config...</p>
  
  <p>In our scenario we have a custom R module uploaded to our workspace which includes some libraries that are not available on aML by default. The module takes a dataset, trains a binary tree, creates some plots and encodes them in base64 before returning those as a dataset. Locally that does not take more than 5s. But in the aML webservice it takes approx. 90s and it seems that the runtime in batchmode does not improve when calling the service multiple times.</p>
  
  <p>Additionally it would be nice to know for how long the containers, mentioned in the linked post, will stay warm.</p>