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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