Jay Ma

@mabdinur @taegyunkim any updates on this?

``` ENV DD_LOGS_ENABLED=true ENV DD_LOGS_INJECTION=true ENV DD_TRACE_ENABLED=true ENV DD_PROFILING_ENABLED=true # https://docs.datadoghq.com/tracing/trace_collection/custom_instrumentation/python/otel/ ENV DD_TRACE_OTEL_ENABLED=true # https://docs.datadoghq.com/profiler/connect_traces_and_profiles/#identify-code-hotspots-in-slow-traces # only available for ver 2.10.5+ ENV DD_PROFILING_TIMELINE_ENABLED=true # https://docs.datadoghq.com/dynamic_instrumentation/enabling/python/?tab=environmentvariables ENV DD_DYNAMIC_INSTRUMENTATION_ENABLED=true # https://docs.datadoghq.com/tracing/metrics/runtime_metrics/python/ ENV...

So i guess for short term solution would be we turn off `DD_PROFILING_TIMELINE_ENABLED`? @taegyunkim

@taegyunkim hey its still taking significant chunk of CPU cycle and memory -   dd version 2.14.4 dd flags: ``` ENV DD_LOGS_ENABLED=true ENV DD_LOGS_INJECTION=true ENV DD_TRACE_ENABLED=true ENV DD_PROFILING_ENABLED=true #...

@taegyunkim any updates?

> Could you check again your DD_* environment variables and flamegraph Im sure i didnt turn on `DD_PROFILING_TIMELINE_ENABLED` or any of them. @taegyunkim

I will try enable `DD_PROFILING_STACK_V2_ENABLED`. Whats the expected behavior? @taegyunkim > will soon work on a fix for this, < 2 weeks. When do we expect the fix is in...

> And do you mind sharing what Python version you're using? From our testing, Python 3.12 doesn't have the issue ensure_binary_or_empty() allocating a lot of memory. @taegyunkim Im using python...