Does adding runtime.GoSched() calls make any difference?
On Mon, Jul 1, 2019 at 5:37 PM 'Yunchi Luo' via golang-nuts <
golang-nuts@googlegroups.com> wrote:
> Following that logic, a leak of TCP connections should manifest as a file
> descriptor leak. We have the process_open_fds metric from Prometheus, that
> is the number of open file descriptors as found in /proc/<pid>/fd. The
> number of descriptors overtime correlates well with the amount of traffic,
> pretty cyclic. There doesn't appear to be a leak.
>
> We don't do our own memory management and the binary is compiled with
> CGO_ENABLED=0.
>
> I still think the issue I'm seeing should be GC (or heap) related, given
> the explosion in mark & sweep time, HeapSys, HeapIdle, and HeapReleased
> just before the process dies. But I'm lacking ideas on how to track down
> the cause of the increase.
>
> On Mon, Jul 1, 2019 at 5:39 PM Robert Engels <reng...@ix.netcom.com>
> wrote:
>
>> I think don't think you are going to find it in the 'heap', rather it
>> would be in native memory.
>>
>> I would use the monitor the /proc/[pid] for the process, and pay
>> attention to the 'fd','net' and 'statm' - if my theory is correct you will
>> see growth here long before the process is killed. Since you are running
>> under k8s and cgroups, you will need to do this along side the Go process
>> (unless you have root access to the server).
>>
>> I 'think' depending on kernel version, that kernel memory used goes
>> against the process for OOM purposes, so this is a likely candidate if
>> pprof is showing nothing.
>>
>> Do you by chance do any of your own memory management (via malloc/CGO)?
>> If so, this is not going to show in pprof either.
>>
>> -----Original Message-----
>> From: 'Yunchi Luo' via golang-nuts
>> Sent: Jul 1, 2019 4:26 PM
>> To: Robert Engels
>> Cc: golang-nuts@googlegroups.com, Alec Thomas
>> Subject: Re: [go-nuts] OOM occurring with a small heap
>>
>> I actually have a heap profile (pasted at the bottom) from about 1 second
>> before the service died (the goroutine that is logging "[Memory]" triggers
>> heap profiles once RSS > 100MB). I don't see TCP connections there. Maybe
>> it's too few to be sampled. How would I verify your theory? That the
>> service dies within 2 seconds after several hours makes it very hard to
>> debug.
>>
>> The top thing in the heap profile is from the reflect package. I
>> initially found that suspect, but it turns out this comes from a use of
>> httptrace.ClientTrace I had for counting new connections to DynamoDB.
>>
>> tracer := &httptrace.ClientTrace{
>> ConnectStart: func(_, _ string) {
>> newConns.Inc()
>> },
>> }
>>
>> `newConns` is just a prometheus counter. The `tracer` object itself is
>> created once and re-used with every client request context. On request,
>> `httptrace.WithClientTrace(ctx, tracer)` uses reflection to compose the
>> trace functions under-the-hood and uses reflection to invoke it, hence the
>> reflect.funcLayout and reflect.Value.call. Objects in `reflect` account for
>> about 50% of heap in terms of size, and does seem to grow as the service is
>> running out of memory, but that's only 12MB so I thought it was a red
>> herring.
>>
>> Heap profile:
>> Type: inuse_space
>> Time: Jun 30, 2019 at 4:46am (EDT)
>> Entering interactive mode (type "help" for commands, "o" for options)
>> (pprof) inuse_objects
>> (pprof) top
>> Showing nodes accounting for 414485, 100% of 414485 total
>> Showing top 10 nodes out of 81
>> flat flat% sum% cum cum%
>> 344074 83.01% 83.01% 344074 83.01% reflect.funcLayout.func1
>> 32768 7.91% 90.92% 376842 90.92% reflect.callReflect
>> 16384 3.95% 94.87% 16384 3.95%
>> github.com/json-iterator/go.processTags
>> 10923 2.64% 97.51% 10923 2.64% context.WithValue
>> 8192 1.98% 99.48% 8192 1.98% crypto/hmac.New
>> 1260 0.3% 99.79% 1260 0.3%
>> github.com/aws/aws-sdk-go/aws/signer/v4.(*signingCtx).buildCanonicalHeaders
>> 820 0.2% 100% 820 0.2%
>> github.com/stripe/veneur/tdigest.NewMerging
>> 64 0.015% 100% 64 0.015% reflect.addReflectOff
>> 0 0% 100% 820 0.2%
>> git.sqcorp.co/cash/digester/lib/pkg/histogram.(*SlidingWindowDigest).Observe
>> 0 0% 100% 820 0.2%
>> git.sqcorp.co/cash/digester/lib/pkg/histogram.(*SlidingWindowDigest).openDigests
>> (pprof) cum
>> (pprof) top
>> Showing nodes accounting for 376842, 90.92% of 414485 total
>> Showing top 10 nodes out of 81
>> flat flat% sum% cum cum%
>> 0 0% 0% 376842 90.92%
>> net/http/httptrace.(*ClientTrace).compose.func1
>> 0 0% 0% 376842 90.92% reflect.Value.Call
>> 0 0% 0% 376842 90.92% reflect.Value.call
>> 32768 7.91% 7.91% 376842 90.92% reflect.callReflect
>> 0 0% 7.91% 376842 90.92% reflect.makeFuncStub
>> 344074 83.01% 90.92% 344074 83.01% reflect.funcLayout.func1
>> 0 0% 90.92% 344074 83.01% sync.(*Pool).Get
>> 0 0% 90.92% 16448 3.97%
>> github.com/json-iterator/go._createDecoderOfType
>> 0 0% 90.92% 16448 3.97%
>> github.com/json-iterator/go.createDecoderOfType
>> 0 0% 90.92% 16448 3.97%
>> github.com/json-iterator/go.decoderOfStruct
>>
>>
>> On Mon, Jul 1, 2019 at 4:32 PM Robert Engels <reng...@ix.netcom.com>
>> wrote:
>>
>>>
>>> A leak of the TCP connections (maybe not properly closed)? Each TCP
>>> connection will use kernel memory and process memory (local buffers), that
>>> won't be on the heap (the reference to the TCP connection will be in the Go
>>> heap, but is probably much smaller than the buffer allocation).
>>>
>>> That would be my guess - but just a guess.
>>>
>>> -----Original Message-----
>>> From: 'Yunchi Luo' via golang-nuts
>>> Sent: Jul 1, 2019 2:14 PM
>>> To: golang-nuts@googlegroups.com
>>> Cc: Alec Thomas
>>> Subject: [go-nuts] OOM occurring with a small heap
>>>
>>> Hello, I'd like to solicit some help with a weird GC issue we are seeing.
>>>
>>> I'm trying to debug OOM on a service we are running in k8s. The service
>>> is just a CRUD server hitting a database (DynamoDB). Each replica serves
>>> about 300 qps of traffic. There are no memory leaks. On occasion (seemingly
>>> correlated to small latency spikes on the backend), the service would OOM.
>>> This is surprising because it has a circuit breaker that drops requests
>>> after 200 concurrent connections that has never trips, and goroutine
>>> profiles confirm that there are nowhere 200 active goroutines.
>>>
>>> GC logs are pasted below. It's interlaced with dumps of runtime.Memstats
>>> (the RSS number is coming from /proc/<pid>/stats). Go version is 1.12.5,
>>> running an Alpine 3.10 container in an Amazon kernel
>>> 4.14.123-111.109.amzn2.x86_64.
>>>
>>> The service happily serves requests using ~50MB of RSS for hours, until
>>> the last 2 seconds, where GC mark&sweep time starts to 2-4X per cycle
>>> (43+489/158/0.60+0.021
>>> ms cpu => 43+489/158/0.60+0.021 ms cpu), and RSS and Sys blow up. It’s
>>> also interesting that in the last log line: `Sys=995MB RSS=861MB
>>> HeapSys=199MB`. If I’m reading this correctly, there’s at least `662MB` of
>>> memory in RSS that is not assigned to the heap. Though this might be due to
>>> the change in 1.125 to use MADV_FREE, so the pages are freeable not yet
>>> reclaimed by the kernel.
>>>
>>> I don’t understand how heap can be so small across gc cycles
>>> (28->42->30MB on the last line means heap doesn't grow past 42MB?), yet RSS
>>> keeps growing. I'm assuming the increased RSS is causing the kernel to OOM
>>> the service, but that should only happen if the RSS is not freeable as
>>> marked by MADV_FREE. There doesn't seem to be any indication of that from
>>> the GC logs. I guess this all comes down to me not having a good
>>> understanding of how the GC algorithm works and how to read these logs. I'd
>>> really appreciate it if anyone can explain what's happening and why.
>>>
>>> gc 41833 @19135.227s 0%: 0.019+2.3+0.005 ms clock,
>>> 0.079+0.29/2.2/5.6+0.020 ms cpu, 11->11->5 MB, 12 MB goal, 4 P
>>> INFO 2019-06-30T08:46:04.886 [Memory]: Alloc=7MB TotalAlloc=230172MB
>>> Sys=69MB RSS=51MB HeapSys=62MB HeapIdle=51MB HeapInUse=11MB HeapReleased=5MB
>>> gc 41834 @19135.869s 0%: 0.005+2.9+0.003 ms clock,
>>> 0.023+0.32/2.5/6.6+0.012 ms cpu, 11->11->5 MB, 12 MB goal, 4 P
>>> INFO 2019-06-30T08:46:05.886 [Memory]: Alloc=9MB TotalAlloc=230179MB
>>> Sys=69MB RSS=51MB HeapSys=62MB HeapIdle=50MB HeapInUse=12MB HeapReleased=5MB
>>> gc 41835 @19136.704s 0%: 0.038+2.1+0.004 ms clock,
>>> 0.15+0.35/2.1/5.3+0.016 ms cpu, 11->11->5 MB, 12 MB goal, 4 P
>>> INFO 2019-06-30T08:46:06.886 [Memory]: Alloc=9MB TotalAlloc=230184MB
>>> Sys=69MB RSS=51MB HeapSys=62MB HeapIdle=50MB HeapInUse=12MB HeapReleased=5MB
>>> gc 41836 @19137.611s 0%: 0.009+2.1+0.003 ms clock,
>>> 0.036+0.39/2.0/5.7+0.015 ms cpu, 11->11->5 MB, 12 MB goal, 4 P
>>> INFO 2019-06-30T08:46:07.887 [Memory]: Alloc=10MB TotalAlloc=230190MB
>>> Sys=69MB RSS=51MB HeapSys=62MB HeapIdle=49MB HeapInUse=12MB HeapReleased=5MB
>>> gc 41837 @19138.444s 0%: 0.008+2.1+0.004 ms clock,
>>> 0.035+0.51/2.1/5.7+0.017 ms cpu, 11->11->5 MB, 12 MB goal, 4 P
>>> INFO 2019-06-30T08:46:08.887 [Memory]: Alloc=10MB TotalAlloc=230195MB
>>> Sys=69MB RSS=51MB HeapSys=62MB HeapIdle=49MB HeapInUse=12MB HeapReleased=5MB
>>> gc 41838 @19139.474s 0%: 0.005+2.6+0.003 ms clock,
>>> 0.023+0.37/2.5/4.3+0.014 ms cpu, 11->11->5 MB, 12 MB goal, 4 P
>>> gc 41839 @19140.173s 0%: 0.011+2.4+0.003 ms clock,
>>> 0.046+0.20/2.3/5.8+0.015 ms cpu, 11->11->5 MB, 12 MB goal, 4 P
>>> INFO 2019-06-30T08:46:09.887 [Memory]: Alloc=7MB TotalAlloc=230202MB
>>> Sys=69MB RSS=51MB HeapSys=62MB HeapIdle=50MB HeapInUse=11MB HeapReleased=5MB
>>> gc 41840 @19140.831s 0%: 0.082+2.1+0.003 ms clock,
>>> 0.32+0.64/2.1/5.3+0.014 ms cpu, 11->11->5 MB, 12 MB goal, 4 P
>>> INFO 2019-06-30T08:46:10.887 [Memory]: Alloc=9MB TotalAlloc=230209MB
>>> Sys=69MB RSS=51MB HeapSys=62MB HeapIdle=50MB HeapInUse=12MB HeapReleased=5MB
>>> gc 41841 @19141.655s 0%: 0.014+2.1+0.003 ms clock,
>>> 0.056+0.28/2.0/5.7+0.013 ms cpu, 11->11->5 MB, 12 MB goal, 4 P
>>> gc 41842 @19142.316s 0%: 0.006+2.7+0.003 ms clock,
>>> 0.027+0.29/2.6/6.2+0.014 ms cpu, 11->11->5 MB, 12 MB goal, 4 P
>>> INFO 2019-06-30T08:46:11.888 [Memory]: Alloc=6MB TotalAlloc=230216MB
>>> Sys=69MB RSS=51MB HeapSys=62MB HeapIdle=51MB HeapInUse=11MB HeapReleased=5MB
>>> gc 41843 @19142.942s 0%: 0.010+2.1+0.005 ms clock,
>>> 0.040+0.29/2.0/5.7+0.023 ms cpu, 11->11->5 MB, 12 MB goal, 4 P
>>> INFO 2019-06-30T08:46:12.888 [Memory]: Alloc=9MB TotalAlloc=230223MB
>>> Sys=69MB RSS=51MB HeapSys=62MB HeapIdle=50MB HeapInUse=11MB HeapReleased=5MB
>>> gc 41844 @19143.724s 0%: 0.008+2.4+0.004 ms clock,
>>> 0.035+0.38/2.0/5.7+0.017 ms cpu, 11->11->5 MB, 12 MB goal, 4 P
>>> gc 41845 @19144.380s 0%: 10+9.3+0.044 ms clock, 43+6.1/9.2/4.4+0.17 ms
>>> cpu, 11->11->6 MB, 12 MB goal, 4 P
>>> INFO 2019-06-30T08:46:13.901 [Memory]: Alloc=6MB TotalAlloc=230230MB
>>> Sys=136MB RSS=98MB HeapSys=94MB HeapIdle=83MB HeapInUse=11MB
>>> HeapReleased=35MB
>>> gc 41846 @19144.447s 0%: 0.008+26+0.005 ms clock,
>>> 0.033+0.46/7.8/26+0.020 ms cpu, 11->12->9 MB, 12 MB goal, 4 P
>>> gc 41847 @19144.672s 0%: 0.013+76+0.006 ms clock,
>>> 0.053+0.20/6.4/80+0.024 ms cpu, 17->18->8 MB, 18 MB goal, 4 P
>>> gc 41848 @19145.014s 0%: 0.008+172+0.005 ms clock,
>>> 0.035+0.13/8.5/177+0.022 ms cpu, 15->17->10 MB, 16 MB goal, 4 P
>>> gc 41849 @19145.298s 0%: 0.007+285+0.006 ms clock,
>>> 0.030+10/285/7.6+0.024 ms cpu, 19->23->15 MB, 20 MB goal, 4 P
>>> INFO 2019-06-30T08:46:15.052 [Memory]: Alloc=22MB TotalAlloc=230264MB
>>> Sys=598MB RSS=531MB HeapSys=265MB HeapIdle=240MB HeapInUse=25MB
>>> HeapReleased=164MB
>>> gc 41850 @19145.665s 0%: 10+419+0.005 ms clock, 43+489/158/0.60+0.021 ms
>>> cpu, 26->30->17 MB, 30 MB goal, 4 P
>>> gc 41851 @19146.325s 0%: 21+798+0.036 ms clock, 86+990/401/0+0.14 ms
>>> cpu, 28->42->30 MB, 34 MB goal, 4 P
>>> INFO 2019-06-30T08:46:16.613 [Memory]: Alloc=41MB TotalAlloc=230303MB
>>> Sys=995MB RSS=861MB HeapSys=199MB HeapIdle=155MB HeapInUse=44MB
>>> HeapReleased=54MB
>>>
>>> I also captured the OOM log from dmesg here
>>> https://gist.github.com/mightyguava/7ecc6fc55f5cd925062d6beede3783b3.
>>>
>>> --
>>> Yunchi
>>>
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>>>
>>>
>>>
>>
>> --
>> Yunchi
>>
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>
> --
> Yunchi
>
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--
*Michael T. jonesmichael.jo...@gmail.com <michael.jo...@gmail.com>*
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