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Raphael/agent http request errors#173

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raphaelgavache merged 40 commits into
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raphael/agent_http_request_errors
Mar 29, 2017
Merged

Raphael/agent http request errors#173
raphaelgavache merged 40 commits into
masterfrom
raphael/agent_http_request_errors

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@raphaelgavache

@raphaelgavache raphaelgavache commented Feb 13, 2017

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Summary

Log whenever an http error happens when dd-trace-py sends traces to the agent.
Every 60 seconds logs have the ERROR level,
Under 60 seconds between two http error the logs have DEBUG level

Testing

Added a test in py-integration in the TestWorker: test_worker_http_error_logging

Comment thread ddtrace/api.py Outdated

# client error code
if 400 <= status_code <= 499:
log.error("Client error: #{}".format(response.msg))

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we need some form of rate limiting here ... otherwise we could spam the log a lot.

Raphael Gavache and others added 12 commits February 13, 2017 23:11
periodically (every 1s)
changing how the the timer works
.stop() already used in python3 threading, changing name
Using AsyncWorker _target thread function to write the http log requests
log on the Writer
bad indent fix
Comment thread ddtrace/writer.py Outdated

time.sleep(1) # replace with a blocking pop.

# Logging the http errors

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how can this work? what assigns to result_traces?

@raphaelgavache raphaelgavache Feb 14, 2017

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api uses the httplib python library to send the data

The request comes from the lib with the 3 attributes status, reason, msg
https://github.com/python-git/python/blob/master/Lib/httplib.py#L943

It is then transmitted here
https://github.com/DataDog/dd-trace-py/blob/raphael/agent_http_request_errors/ddtrace/api.py#L79

And then here
https://github.com/DataDog/dd-trace-py/blob/raphael/agent_http_request_errors/ddtrace/api.py#L56

Actually no errors are raised in case of 400-599 http errors

Comment thread ddtrace/writer.py Outdated

# Logging the http errors
if result_traces and result_traces.status >= 400:
current_time = time.time()

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nitpick: now = time.time()

Comment thread ddtrace/writer.py Outdated
log.error("traces to Agent: HTTP error status {}, reason {}, message {}".format(
result_traces.status, result_traces.reason, result_traces.msg))
last_error_ts = current_time
else:

@clutchski clutchski Feb 14, 2017

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i'd change this to:

log_level = log.debug
if now > last_error_ts + LOG_ERR_INTERVAL:
    log_level = log.error
    last_error_ts = now
log_level("traces ...")

it's a bit cleaner and easier to read

Comment thread ddtrace/writer.py
else:
log.debug("services to Agent: HTTP error status {}, reason {}, message {}".format(
result_services.status, result_services.reason, result_services.msg))

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can we add a test for this whole thing?

Comment thread ddtrace/writer.py Outdated
# Logging the http errors
if result_traces and result_traces.status >= 400:
current_time = time.time()
if current_time > last_error_ts + 10:

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i think that the default interval should be 60 or 120

Comment thread tests/test_integration.py Outdated
'test to try the http log errors, to trigger it change'
+ 'https://github.com/DataDog/dd-trace-py/blob/master/ddtrace/api.py#L78'
+ 'to "conn.request("HEAD", endpoint, data, self._headers)"'
+ 'skip TestAPITransport and TestAPIDowngrade as they will fail if you change PUT to HEAD')

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i think more important than testing the log capture itself is testing that the timestamps you are using for tracking errors are correctly updated. this means forcing an error in the api, and ensuring that last_error_ts is updated to a reasonable value.

Comment thread ddtrace/writer.py Outdated
time.sleep(0.05)

def _target(self):
last_error_ts = 0

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think about moving this to an attribute on AgentWriter so it's easier to test against self.last_error_ts

Comment thread ddtrace/writer.py Outdated
if now > last_error_ts + LOG_ERR_INTERVAL:
log_level = log.error
last_error_ts = now
log_level("traces to Agent: HTTP error status {}, reason {}, message {}".format(

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failed to send traces to Agent...

@palazzem palazzem left a comment

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minor changes that you can double check! overall the approach is fine!

Comment thread ddtrace/ext/aws.py Outdated
@@ -0,0 +1,11 @@
BLACKLIST_ENDPOINT = [

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think this is the result of a conflict; don't think we need it

Comment thread ddtrace/writer.py
getattr(result_services, "msg", None))
result_services = None

time.sleep(1) # replace with a blocking pop.

@palazzem palazzem Mar 16, 2017

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it's better to avoid any kind of sleep() in application code... why do we need that?

Comment thread ddtrace/writer.py Outdated

time.sleep(1) # replace with a blocking pop.
log_level = log.debug
if result_traces and getattr(result_traces, "status", None) >= 400:

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this code is the same as the block below... you can merge the two blocks or use a separated function like _log_error_status(...)

Comment thread tests/test_integration.py Outdated

logged_errors = log_handler.messages['error']
eq_(len(logged_errors), 1)
if PY2:

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instead of using a switch, you can just:

ok_('failed_to_send traces to Agent: HTTP error status 400, reason Bad Request' in logged_errors[0])

or whatever is the string you want to check.

Comment thread tests/test_integration.py Outdated
self.tracer.writer.api = FlawedAPI(Tracer.DEFAULT_HOSTNAME, Tracer.DEFAULT_PORT)
tracer.trace('client.testing').finish()
tracer.trace('client.testing').finish()
eq_(tracer.writer._worker._last_error_ts, 0)

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this check could be flaky because you're relying that this thread is faster than the API worker

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@palazzem palazzem modified the milestone: 0.8.0 Mar 29, 2017
@raphaelgavache raphaelgavache merged commit 3ab3525 into master Mar 29, 2017
@palazzem palazzem deleted the raphael/agent_http_request_errors branch March 30, 2017 13:19
@palazzem palazzem modified the milestones: 0.8.0, 0.7.1 Apr 3, 2017
@palazzem palazzem modified the milestones: 0.7.1, 0.8.0 Apr 10, 2017
gh-worker-dd-mergequeue-cf854d Bot pushed a commit that referenced this pull request Apr 23, 2026
…llocator (#17664)

## Description

This PR fixes a segmentation fault in the memory allocation profiler that occurs when a hook call races with `memalloc` start/stop operations. The issue arises from concurrent access to the saved allocator struct, which could be partially written while being read, resulting in`NULL` function pointers being dereferenced.  The key indicator in that case is that `#1 0x0000000000000000` frame -- we are trying to execute a null function pointer.

````
Error UnixSignal: Process terminated with SEGV_MAPERR (SIGSEGV)
#0   0x00007ff3c303a8d4  
#1   0x0000000000000000 memalloc_alloc (/go/src/github.com/DataDog/apm-reliability/dd-trace-py/ddtrace/profiling/collector/_memalloc.cpp:68)
#2   0x00007ff39dcb3b20 memalloc_alloc (/go/src/github.com/DataDog/apm-reliability/dd-trace-py/ddtrace/profiling/collector/_memalloc.cpp:68)
#3   0x00007ff39dcb3b20 memalloc_malloc(void*, unsigned long) (/go/src/github.com/DataDog/apm-reliability/dd-trace-py/ddtrace/profiling/collector/_memalloc.cpp:80)
#4   0x00007ff3c3087e1b PyUnicode_New 
#5   0x00007ff3c30889f4  
#6   0x00007ff3c3170c84  
#7   0x00007ff3c316b931  
#8   0x00007ff3c31aaac8  
#9   0x00007ff3c31033ac  
#10  0x00007ff3c310e2a6 PyObject_CallMethodObjArgs 
#11  0x00007ff3c310e46d  
#12  0x00007ff3c31a96c2  
#13  0x00007ff3c3102fd7 PyObject_Vectorcall 
#14  0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#15  0x00007ff3c323c094  
#16  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#17  0x00007ff3c323c094  
#18  0x00007ff3c30e997d PyObject_CallOneArg 
#19  0x00007ff3c306a480 _PyObject_GenericGetAttrWithDict 
#20  0x00007ff3c30c620d PyObject_GetAttr 
#21  0x00007ff3c32309e7 _PyEval_EvalFrameDefault 
#22  0x00007ff3c323c094  
#23  0x00007ff3c312880e  
#24  0x00007ff3c30e917c _PyObject_MakeTpCall 
#25  0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#26  0x00007ff3c323c094  
#27  0x00007ff3c312880e  
#28  0x00007ff3c30e917c _PyObject_MakeTpCall 
#29  0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#30  0x00007ff3c323c094  
#31  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#32  0x00007ff3c323c094  
#33  0x00007ff3c317d0fd  
#34  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#35  0x00007ff3c323c094  
#36  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#37  0x00007ff3c323c094  
#38  0x00007ff3c317d1b5  
#39  0x00007ff3c3102fd7 PyObject_Vectorcall 
#40  0x00007ff3c3232f4a _PyEval_EvalFrameDefault 
#41  0x00007ff3c3240da5  
#42  0x00007ff3c324112d  
#43  0x00007ff3c3233be1 _PyEval_EvalFrameDefault 
#44  0x00007ff3c323c094  
#45  0x00007ff3c317d1b5  
#46  0x00007ff3c3102fd7 PyObject_Vectorcall 
#47  0x00007ff3c3232f4a _PyEval_EvalFrameDefault 
#48  0x00007ff3c323c094  
#49  0x00007ff3c31033ac  
#50  0x00007ff3c310358d PyObject_CallFunctionObjArgs 
#51  0x00007ff3bf7eb91d WraptBoundFunctionWrapper_call (/project/src/wrapt/_wrappers.c:3750)
#52  0x00007ff3c3104055 _PyObject_Call 
#53  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#54  0x00007ff3c323c094  
#55  0x00007ff3c317d23c  
#56  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#57  0x00007ff3c323c094  
#58  0x00007ff3c310416f _PyObject_Call 
#59  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#60  0x00007ff3c3240da5  
#61  0x00007ff3c324112d  
#62  0x00007ff3c3233be1 _PyEval_EvalFrameDefault 
#63  0x00007ff3c323c094  
#64  0x00007ff3c317d1b5  
#65  0x00007ff3c3102fd7 PyObject_Vectorcall 
#66  0x00007ff3c3232f4a _PyEval_EvalFrameDefault 
#67  0x00007ff3c323c094  
#68  0x00007ff3c317d1b5  
#69  0x00007ff3c310416f _PyObject_Call 
#70  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#71  0x00007ff3c323c094  
#72  0x00007ff3c317d1b5  
#73  0x00007ff3c310416f _PyObject_Call 
#74  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#75  0x00007ff3c323c094  
#76  0x00007ff3c31033ac  
#77  0x00007ff3c310358d PyObject_CallFunctionObjArgs 
#78  0x00007ff3bf7eb91d WraptBoundFunctionWrapper_call (/project/src/wrapt/_wrappers.c:3750)
#79  0x00007ff3c30e917c _PyObject_MakeTpCall 
#80  0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#81  0x00007ff3c323c094  
#82  0x00007ff3c317d518  
#83  0x00007ff3c3155963  
#84  0x00007ff3c315393d  
#85  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#86  0x00007ff3c323c094  
#87  0x00007ff3c317d0fd  
#88  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#89  0x00007ff3c323c094  
#90  0x00007ff3c317d0fd  
#91  0x00007ff3c317d518  
#92  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#93  0x00007ff3c323c094  
#94  0x00007ff3c30e9371 _PyObject_FastCallDictTstate 
#95  0x00007ff3c30e958d _PyObject_Call_Prepend 
#96  0x00007ff3c3109150  
#97  0x00007ff3c3104055 _PyObject_Call 
#98  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#99  0x00007ff3c323c094  
#100 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#101 0x00007ff3c30e958d _PyObject_Call_Prepend 
#102 0x00007ff3c3109150  
#103 0x00007ff3c30e917c _PyObject_MakeTpCall 
#104 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#105 0x00007ff3c323c094  
#106 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#107 0x00007ff3c30e958d _PyObject_Call_Prepend 
#108 0x00007ff3c3109150  
#109 0x00007ff3c30e917c _PyObject_MakeTpCall 
#110 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#111 0x00007ff3c323c094  
#112 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#113 0x00007ff3c30e958d _PyObject_Call_Prepend 
#114 0x00007ff3c3109150  
#115 0x00007ff3c30e917c _PyObject_MakeTpCall 
#116 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#117 0x00007ff3c323c094  
#118 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#119 0x00007ff3c30e958d _PyObject_Call_Prepend 
#120 0x00007ff3c3109150  
#121 0x00007ff3c30e917c _PyObject_MakeTpCall 
#122 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#123 0x00007ff3c323c094  
#124 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#125 0x00007ff3c30e958d _PyObject_Call_Prepend 
#126 0x00007ff3c3109150  
#127 0x00007ff3c30e917c _PyObject_MakeTpCall 
#128 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#129 0x00007ff3c323c094  
#130 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#131 0x00007ff3c30e958d _PyObject_Call_Prepend 
#132 0x00007ff3c3109150  
#133 0x00007ff3c30e917c _PyObject_MakeTpCall 
#134 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#135 0x00007ff3c323c094  
#136 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#137 0x00007ff3c30e958d _PyObject_Call_Prepend 
#138 0x00007ff3c3109150  
#139 0x00007ff3c30e917c _PyObject_MakeTpCall 
#140 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#141 0x00007ff3c323c094  
#142 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#143 0x00007ff3c30e958d _PyObject_Call_Prepend 
#144 0x00007ff3c3109150  
#145 0x00007ff3c30e917c _PyObject_MakeTpCall 
#146 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#147 0x00007ff3c323c094  
#148 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#149 0x00007ff3c30e958d _PyObject_Call_Prepend 
#150 0x00007ff3c3109150  
#151 0x00007ff3c30e917c _PyObject_MakeTpCall 
#152 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#153 0x00007ff3c323c094  
#154 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#155 0x00007ff3c30e958d _PyObject_Call_Prepend 
#156 0x00007ff3c3109150  
#157 0x00007ff3c30e917c _PyObject_MakeTpCall 
#158 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#159 0x00007ff3c323c094  
#160 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#161 0x00007ff3c30e958d _PyObject_Call_Prepend 
#162 0x00007ff3c3109150  
#163 0x00007ff3c30e917c _PyObject_MakeTpCall 
#164 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#165 0x00007ff3c323c094  
#166 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#167 0x00007ff3c30e958d _PyObject_Call_Prepend 
#168 0x00007ff3c3109150  
#169 0x00007ff3c30e917c _PyObject_MakeTpCall 
#170 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#171 0x00007ff3c323c094  
#172 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#173 0x00007ff3c30e958d _PyObject_Call_Prepend 
#174 0x00007ff3c3109150  
#175 0x00007ff3c30e917c _PyObject_MakeTpCall 
#176 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#177 0x00007ff3c323c094  
#178 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#179 0x00007ff3c30e958d _PyObject_Call_Prepend 
#180 0x00007ff3c3109150  
#181 0x00007ff3c30e917c _PyObject_MakeTpCall 
#182 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#183 0x00007ff3c323c094  
#184 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#185 0x00007ff3c30e958d _PyObject_Call_Prepend 
#186 0x00007ff3c3109150  
#187 0x00007ff3c30e917c _PyObject_MakeTpCall 
#188 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#189 0x00007ff3c323c094  
#190 0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#191 0x00007ff3c323c094  
#192 0x00007ff3c30e92f1 _PyObject_FastCallDictTstate 
#193 0x00007ff3c30e958d _PyObject_Call_Prepend 
#194 0x00007ff3c3109150  
#195 0x00007ff3c30e917c _PyObject_MakeTpCall 
#196 0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#197 0x00007ff3c323c094  
#198 0x00007ff3c317d0fd  
#199 0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#200 0x00007ff3c323c094  
#201 0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#202 0x00007ff3c323c094  
#203 0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#204 0x00007ff3c323c094  
#205 0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#206 0x00007ff3c323c094  
#207 0x00007ff3c317d23c  
#208 0x00007ff3c31a7ec5  
#209 0x00007ff3c301ac77  
#210 0x00007ff3c357c573  
````

The fix implements two key changes.

1. **Hook functions (`memalloc_alloc`, `memalloc_realloc`)**: Snapshot the allocator struct locally before use and guard indirect function calls with `NULL` checks. This prevents crashes if a partially-written struct is observed during a start/stop race.

2. **Start/stop operations (`memalloc_start`, `memalloc_stop`)**: Use local variables and single assignments when publishing the allocator struct to `global_memalloc_ctx.pymem_allocator_obj`. This ensures concurrent hook calls observe either the old or new struct, never a partially-written intermediate state.

The real root cause is that `PyMem_GetAllocator` is not documented as atomic, and the struct could be read field-by-field while being written to concurrently.  By using local copies and single assignments, we ensure atomicity at the C level and prevent observation of inconsistent state.

Co-authored-by: thomas.kowalski <thomas.kowalski@datadoghq.com>
emmettbutler pushed a commit that referenced this pull request Apr 24, 2026
…llocator (#17664)

## Description

This PR fixes a segmentation fault in the memory allocation profiler that occurs when a hook call races with `memalloc` start/stop operations. The issue arises from concurrent access to the saved allocator struct, which could be partially written while being read, resulting in`NULL` function pointers being dereferenced.  The key indicator in that case is that `#1 0x0000000000000000` frame -- we are trying to execute a null function pointer.

````
Error UnixSignal: Process terminated with SEGV_MAPERR (SIGSEGV)
#0   0x00007ff3c303a8d4  
#1   0x0000000000000000 memalloc_alloc (/go/src/github.com/DataDog/apm-reliability/dd-trace-py/ddtrace/profiling/collector/_memalloc.cpp:68)
#2   0x00007ff39dcb3b20 memalloc_alloc (/go/src/github.com/DataDog/apm-reliability/dd-trace-py/ddtrace/profiling/collector/_memalloc.cpp:68)
#3   0x00007ff39dcb3b20 memalloc_malloc(void*, unsigned long) (/go/src/github.com/DataDog/apm-reliability/dd-trace-py/ddtrace/profiling/collector/_memalloc.cpp:80)
#4   0x00007ff3c3087e1b PyUnicode_New 
#5   0x00007ff3c30889f4  
#6   0x00007ff3c3170c84  
#7   0x00007ff3c316b931  
#8   0x00007ff3c31aaac8  
#9   0x00007ff3c31033ac  
#10  0x00007ff3c310e2a6 PyObject_CallMethodObjArgs 
#11  0x00007ff3c310e46d  
#12  0x00007ff3c31a96c2  
#13  0x00007ff3c3102fd7 PyObject_Vectorcall 
#14  0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#15  0x00007ff3c323c094  
#16  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#17  0x00007ff3c323c094  
#18  0x00007ff3c30e997d PyObject_CallOneArg 
#19  0x00007ff3c306a480 _PyObject_GenericGetAttrWithDict 
#20  0x00007ff3c30c620d PyObject_GetAttr 
#21  0x00007ff3c32309e7 _PyEval_EvalFrameDefault 
#22  0x00007ff3c323c094  
#23  0x00007ff3c312880e  
#24  0x00007ff3c30e917c _PyObject_MakeTpCall 
#25  0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#26  0x00007ff3c323c094  
#27  0x00007ff3c312880e  
#28  0x00007ff3c30e917c _PyObject_MakeTpCall 
#29  0x00007ff3c32335a2 _PyEval_EvalFrameDefault 
#30  0x00007ff3c323c094  
#31  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#32  0x00007ff3c323c094  
#33  0x00007ff3c317d0fd  
#34  0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
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#37  0x00007ff3c323c094  
#38  0x00007ff3c317d1b5  
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#41  0x00007ff3c3240da5  
#42  0x00007ff3c324112d  
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#50  0x00007ff3c310358d PyObject_CallFunctionObjArgs 
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#64  0x00007ff3c317d1b5  
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#68  0x00007ff3c317d1b5  
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#76  0x00007ff3c31033ac  
#77  0x00007ff3c310358d PyObject_CallFunctionObjArgs 
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#210 0x00007ff3c357c573  
````

The fix implements two key changes.

1. **Hook functions (`memalloc_alloc`, `memalloc_realloc`)**: Snapshot the allocator struct locally before use and guard indirect function calls with `NULL` checks. This prevents crashes if a partially-written struct is observed during a start/stop race.

2. **Start/stop operations (`memalloc_start`, `memalloc_stop`)**: Use local variables and single assignments when publishing the allocator struct to `global_memalloc_ctx.pymem_allocator_obj`. This ensures concurrent hook calls observe either the old or new struct, never a partially-written intermediate state.

The real root cause is that `PyMem_GetAllocator` is not documented as atomic, and the struct could be read field-by-field while being written to concurrently.  By using local copies and single assignments, we ensure atomicity at the C level and prevent observation of inconsistent state.

Co-authored-by: thomas.kowalski <thomas.kowalski@datadoghq.com>
emmettbutler pushed a commit that referenced this pull request May 6, 2026
…llocator (#17664)

## Description

This PR fixes a segmentation fault in the memory allocation profiler that occurs when a hook call races with `memalloc` start/stop operations. The issue arises from concurrent access to the saved allocator struct, which could be partially written while being read, resulting in`NULL` function pointers being dereferenced.  The key indicator in that case is that `#1 0x0000000000000000` frame -- we are trying to execute a null function pointer.

````
Error UnixSignal: Process terminated with SEGV_MAPERR (SIGSEGV)
#0   0x00007ff3c303a8d4  
#1   0x0000000000000000 memalloc_alloc (/go/src/github.com/DataDog/apm-reliability/dd-trace-py/ddtrace/profiling/collector/_memalloc.cpp:68)
#2   0x00007ff39dcb3b20 memalloc_alloc (/go/src/github.com/DataDog/apm-reliability/dd-trace-py/ddtrace/profiling/collector/_memalloc.cpp:68)
#3   0x00007ff39dcb3b20 memalloc_malloc(void*, unsigned long) (/go/src/github.com/DataDog/apm-reliability/dd-trace-py/ddtrace/profiling/collector/_memalloc.cpp:80)
#4   0x00007ff3c3087e1b PyUnicode_New 
#5   0x00007ff3c30889f4  
#6   0x00007ff3c3170c84  
#7   0x00007ff3c316b931  
#8   0x00007ff3c31aaac8  
#9   0x00007ff3c31033ac  
#10  0x00007ff3c310e2a6 PyObject_CallMethodObjArgs 
#11  0x00007ff3c310e46d  
#12  0x00007ff3c31a96c2  
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#202 0x00007ff3c323c094  
#203 0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#204 0x00007ff3c323c094  
#205 0x00007ff3c3233dd3 _PyEval_EvalFrameDefault 
#206 0x00007ff3c323c094  
#207 0x00007ff3c317d23c  
#208 0x00007ff3c31a7ec5  
#209 0x00007ff3c301ac77  
#210 0x00007ff3c357c573  
````

The fix implements two key changes.

1. **Hook functions (`memalloc_alloc`, `memalloc_realloc`)**: Snapshot the allocator struct locally before use and guard indirect function calls with `NULL` checks. This prevents crashes if a partially-written struct is observed during a start/stop race.

2. **Start/stop operations (`memalloc_start`, `memalloc_stop`)**: Use local variables and single assignments when publishing the allocator struct to `global_memalloc_ctx.pymem_allocator_obj`. This ensures concurrent hook calls observe either the old or new struct, never a partially-written intermediate state.

The real root cause is that `PyMem_GetAllocator` is not documented as atomic, and the struct could be read field-by-field while being written to concurrently.  By using local copies and single assignments, we ensure atomicity at the C level and prevent observation of inconsistent state.

Co-authored-by: thomas.kowalski <thomas.kowalski@datadoghq.com>
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