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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