If it is a software / configuration issue in your setup then it is not down
time.

If you have errors on M/S you are on your own.

Instances die early if you hit the soft memory limit. Likely if you have
load time issues you have memory usage issues as well.


-----Original Message-----
From: google-appengine@googlegroups.com
[mailto:google-appengine@googlegroups.com] On Behalf Of Cezary Wagner
Sent: Monday, January 16, 2012 2:37 PM
To: Google App Engine
Subject: [google-appengine] Re: Why are several production issues related to
DeadlineExceededErrors being ignored?

Brandom,

I think that problem of DeadlinesExceeds is different:
1st of GAE availability is not measure considering DeadlinesExceeds - it
will be rather not 100%. If it not monitored it has not impact on quality.
Am I wrong?
This is data for the last week:
Day     Total checks    Outages Failed checks   Avg. response time
Uptime
2012.01.14      26      1       1       3.152   96.154 %
2012.01.15      47      1       1       4.937   97.872 %
2012.01.16      47      4       5       3.657   89.362 %

2nd My code without changes through months becomes slower/not faster - I
have optimized code and it works not faster - on SDK it executes 5s-1s
(excluding load time) see above results from production. It could be
suffered with imports but why it once loads and once not loads it random -
it should not load every time or it problem with balance/resource - why IT
IS RANDOM?

3rd Instance DIES just after load not survive 15min period - instance was
load for 1 min than it dies - that is some problem or lack of
balance/resource?

4rd Maybe master/slave has impact?

5th The application not works in my case under low traffic EARLY DIES of
INSTANCES and DeadlinesExceeds kills 3%-10% of customer traffic(stats above)
- I am imagine that GAE works some for higher traffic with exception that
number of errors will be lower - maybe - but how achieve high traffic if it
not works on lower?

Please answer to question or propose other solution - GAE concept is good
but the current my customers experience is not excellent.

On 16 Sty, 18:58, "Brandon Wirtz" <drak...@digerat.com> wrote:
> I agree multiple imports is not supposed to be a problem, but I have
> seen it cause issues, or seen issues be resolved by not doing it.
>
> Remember that the Google Implementation of Python has its own
"Specialness"
> and what is true in traditional python is not always quite the same in
> GAE land.
>
> From: google-appengine@googlegroups.com
> [mailto:google-appengine@googlegroups.com] On Behalf Of Karl Rosaen
> Sent: Monday, January 16, 2012 7:32 AM
> To: google-appengine@googlegroups.com
> Subject: Re: [google-appengine] Re: Why are several production issues
> related to DeadlineExceededErrors being ignored?
>
> Brandon, thanks so much for taking the time to put together the video,
> very helpful.
>
> The key insight seem to be: time spent in the queue waiting for a
> frontend counts towards the limit for a DeadlineExceedError.  This
> seems silly - seems to me user visible latency, and framework level
> timeout enforcement should be decoupled in this case.  But good
> insight and glad to better understand this behavior.  This also makes
> me wonder what the benefit of having 'auto' for max pending latency
> would ever be - I'm going to slide mine down to ~1s.
>
> One quibble about your advice for 'avoid importing code more than once':
> this shouldn't be a major issue in python unless you are importing a
> module from within a function that is called several times:
>
> Although Python's interpreter is optimized to not import the same
> module multiple times, repeatedly executing an import statement can
> seriously affect performance in some circumstances.
>
> http://wiki.python.org/moin/PythonSpeed/PerformanceTips#Import_Statem...
> rhead
>
> Just wanted to clarify that one needn't fret about the same utility
> module being imported from two modules or anything like that.
>
> Karl
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