What we do is to periodically turn on profiling for X seconds, collect some
data and turn it off again. We do it at every once a while periodically. We
target a single or a group of instances in a large group.

On Mon, Jul 24, 2017 at 6:11 PM, Dave Cheney <d...@cheney.net> wrote:

> Another option is to profile a % of requests. In the past I've done that
> by enabling profiling on a set % of application servers then extrapolating
> from there.
>
>
> On Tuesday, 25 July 2017 10:55:42 UTC+10, Jaana Burcu Dogan wrote:
>>
>> It would be very speculative to provide reference numbers without
>> actually seeing the specific program. You can benchmark the
>> latency/throughput with the CPU profiler on to see a realistic estimate.
>> FWIW, memory profiling, goroutine, thread create profiles are always on. At
>> Google, we continuously profile Go production services and it is safe to do
>> so.
>>
>>
>> On Monday, July 24, 2017 at 5:44:10 PM UTC-7, nat...@honeycomb.io wrote:
>>>
>>> Hello,
>>>
>>> I am curious what the performance impact of running pprof to collect
>>> information about CPU or memory usage is. Is it like strace where there
>>> could be a massive slowdown (up to 100x) or is it lower overhead, i.e.,
>>> safe to use in production? The article here -
>>> http://artem.krylysov.com/blog/2017/03/13/profiling-and-op
>>> timizing-go-web-applications/ - suggests that "one of the biggest pprof
>>> advantages is that it has low overhead and can be used in a production
>>> environment on a live traffic without any noticeable performance
>>> penalties". Is that accurate?
>>>
>>> Thanks!
>>>
>>> Nathan
>>>
>> --
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