No "hacks".  We didn't plan to run NLTK forever.

We have peaks and valleys and no 4 boxes would not handle the amount of
crawling we do. 

We wouldn't have stuck with the platform if we thought it was slowing down
development.  It saved us an Infrastructure guy which was huge for a
startup. Over 2 years that buys a LOT of hosting.

Also with AppEngine we haven't had to worry much about downtime. The outages
we have had were reasonably short, and I don't have to get out of bed to
deal with.

 

 

From: [email protected]
[mailto:[email protected]] On Behalf Of Rafael
Sent: Friday, February 28, 2014 3:47 PM
To: google-appengine
Subject: Re: [google-appengine] Show and Tell: Plexi Voice a Windows Phone 8
App with AppEngine backend.

 

It sounds like a lot of hacks to make it "fit" in appengine. 

 

Can you tell me if you would have developed and maintained this in half of
the time if you had just 4 boxes running with 64gb of ram? 

 

On Fri, Feb 28, 2014 at 2:19 PM, Brandon Wirtz <[email protected]
<mailto:[email protected]> > wrote:

We just put out our Open Beta of Plexi Voice. A GoogleNow/Siri like
Conversational Search product. Yes it is for Windows Phone. Yes, it uses
Google AppEngine for all of its backend.

http://www.windowsphone.com/en-us/store/app/plexivoice/9c09f697-657d-4613-ae
67-7e787121d0a4

 

The code is ours, full stack, written in Python. We aren't entirely
converted to modules, but pretty close. We do some cross app calls, but try
to do as much as possible as Modules.

We'd move to doing everything in Modules but the cost of migrating data from
one App to the other would be like $10k and it isn't worth it at this point.

 

Several people in the past have asked about using Python's Natural Language
Tool Kit on AppEngine. 2 years ago we did make a version that "fit" in an F4
instance, but we don't use that anymore, we have our own NLP Engine, that
will run in an F1.

 

For the most part all of our code runs in an F2. Some of our bigger things
related to large dictionaries doesn't fit, so we run F2's instead of F1s.  

We average about 2000 instance hours a day.

We have 2 Terabytes of DataStore.

For our search engine we crawl about 2 Million pages a day of the Internet.

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