Have you tried installing appstats?

On Tue, May 22, 2012 at 4:27 PM, Waleed Abdulla <[email protected]> wrote:

> I meant that the extra delays might not be just memcache, but an API delay
> in general because I'm noticing it with the logging service and the
> urlfetch service as well, as shown by the errors I listed. It's really hard
> to pinpoint these things because different apps have different use patterns
> so they might notice the problem in different ways.
>
>
>
>
> On Tue, May 22, 2012 at 1:59 PM, Rishi Arora <[email protected]>wrote:
>
>> Perhaps they're related, but Google generally doesn't do anything about
>> datastore deadline exceeded errors.  They claim that you should either be
>> using HRD or make your app tolerant of M/S data-store spikes by making
>> asynchronous calls.  In my case, I studied appstat output thoroughly over a
>> large sample, and the problem is specifically for memcache API calls.
>>
>> FYI, here's a production issue I just logged, which you should consider
>> starring, so that it gets attention:
>>
>> code.google.com/p/googleappengine/issues/detail?id=7554
>>
>>
>>
>> On Tue, May 22, 2012 at 3:27 PM, Waleed Abdulla <[email protected]> wrote:
>>
>>> I'm noticing excessive datastore delays today (M/S), and generally a lot
>>> of API calls timing out. Might be related. Errors like:
>>>
>>> *DeadlineExceededError: The API call logservice.Flush() took too long
>>> to respond and was cancelled.*
>>>
>>> Also:
>>>
>>> *<class
>>> 'google.appengine.runtime.apiproxy_errors.DeadlineExceededError'>: The API
>>> call urlfetch.Fetch() took too long to respond and was cancelled.*
>>>
>>>
>>>
>>>
>>> On Tue, May 22, 2012 at 12:04 PM, Gayle Laakmann <[email protected]>wrote:
>>>
>>>> I think I'm having the same issue.
>>>>
>>>> How did you get that look at memcache latency specifically?
>>>>
>>>> On May 22, 9:41 am, Rishi Arora <[email protected]> wrote:
>>>> > Ah, I was mistaken.  The restriction is the other way round.  Py2.7
>>>> > requires HRD.
>>>> >
>>>> > On Tue, May 22, 2012 at 11:24 AM, Joshua Smith <
>>>> [email protected]>wrote:
>>>> >
>>>> >
>>>> >
>>>> >
>>>> >
>>>> >
>>>> >
>>>> > > HRD does not require Py2.7
>>>> >
>>>> > > On May 22, 2012, at 12:01 PM, Rishi Arora wrote:
>>>> >
>>>> > > Also, I imagine going to HRD would indirectly help my situation
>>>> because
>>>> > > I'll be forced to upgrade to python2.7.  So, while my instance is
>>>> waiting
>>>> > > forever for memcache to return some data, it would be available to
>>>> service
>>>> > > other requests, and keep the number of active instances low.  Am I
>>>> correct
>>>> > > in this reasoning?
>>>> >
>>>> > > On Tue, May 22, 2012 at 10:59 AM, Rishi Arora <
>>>> [email protected]>wrote:
>>>> >
>>>> > >> My app usually consumes ~30 instance hours every day, and
>>>> occasionally
>>>> > >> spikes to ~35 when Master-Slave datastore latencies go up.  We
>>>> will be
>>>> > >> transitioning to HRD soon, but today large latency spikes have
>>>> caused my
>>>> > >> instance hours to reach ~50 already, in the first 9 hours of the
>>>> day.  I
>>>> > >> peeked at the appstats output to see where this spike is coming
>>>> from, and
>>>> > >> it appears to be memcache (see attached pic).  This seems absurd
>>>> and not
>>>> > >> something app operators should be expected to pay for.  Anybody
>>>> else seen
>>>> > >> this?
>>>> >
>>>> > >> Thanks in advance
>>>> > >> - Rishi
>>>> >
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