Although a lot of us are upset about how this was handled, I'd suggest
testing how much you can optimize first. If that doesn't help, I have a
couple of suggestions below. Here is my own plan:

1. Start with optimizing settings. Things like reducing max idle instances
and lowering the rate on low priority task queues to reduce spikes.

2. Set a minimum instance commitment to take advantage of the lower cost for
committed hours.

3. Optimize the datastore. My biggest cost is in datastore ops (mostly
writes), so I'm looking at adding (indexed=False) to model properties that I
don't query on, and using memcache more often.

4. If the above gets me back to a reasonable cost, then I'm staying. If not,
then I'm looking at AppScale <http://code.google.com/p/appscale/> and
TyphoonAE <http://code.google.com/p/typhoonae/>. Both are open source
solutions that allow me to run GAE apps on other platforms. They're not
battle tested, so I expect to have to pitch in with a few bug fixes, but I
know that they've ran some apps successfully (TyphoonAE says they've ran the
PubSubHubbub server successfully, which happens to be one of the apps I run
as well). In terms of server hosting, I've used RackSpace and Softlayer, and
they're both really good.


I hope this helps. I have a huge amount of code which makes re-writing my
apps almost impossible. If your code base is still small, you might have
other options as well.

Waleed


On Sat, Sep 3, 2011 at 6:06 AM, Raymond C. <windz...@gmail.com> wrote:

> Regarding hosting options, I am looking at rackspace since there are many
> successful businesses outside are using it.  Now looking at if I should
> switch to node.js or keep running python on the new server.
>
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