[BUG]: Getting "Unable to create shared memory" warning on updating datadog-lambda to v8.123.0 and dd-trace-py v4.5.1

[sgkghoshal]

Tracer Version(s)

4.5.1

Python Version(s)

Python 3.12

Pip Version(s)

26.0.1

Bug Report

Hello,

We have recently updated datadog-lambda-python to v8.123.0 from v8.122.0 and found out that we are getting the below WARNING logs in Datadog for our lambdas:

[WARNING] 2026-03-09T11:59:18.537Z Unable to create shared memory. Features relying on remote configuration will not work as expected.

Looks like the datadog-lambda-python latest version has the below constraint:
For Python >= 3.10: dd-trace-py version is v4.5.0
https://github.com/DataDog/datadog-lambda-python/releases

and it is dd-trace-py v4.5.1 which is generating this warning: 

dd-trace-py/ddtrace/internal/remoteconfig/_connectors.py

Line 50 in ab820c4

"Unable to create shared memory. Features relying on remote configuration will not work as expected."

We run our lambda python code inside a container based on:

• public.ecr.aws/lambda/python:3.12.2026.02.27.23@sha256:70739d82cddc070a22f74c6591bb805153ce7a074a2202557a4b6f7cb1e823ff as the base image
• public.ecr.aws/datadog/lambda-extension:93 for lambda extention

When we run our lambda using a container in AWS, these warning logs are showing up in Datadog.

Is there any way to fix this or change warning to info if that's expected?

Reproduction Code

No response

Error Logs

No response

Libraries in Use

No response

Operating System

No response

[sgkghoshal]

Hi Team, any update on this? As we are not able to update datadog-lambda-python to v8.123.0 for this.

[rally25rs]

I've seen the same on aws Lambda using:

Python = 3.13 (arm64)
datadog-lambda = 8.124.0
ddtrace = 4.7.1

I think specifically we might be using this docker image:

public.ecr.aws/lambda/python:3.13-arm64

[lars-smeby-adsk]

Correct me if I'm wrong, but I think this is solved by #17550, which will be released with 4.8.

[sgkghoshal]

After updating datadog-lambda to the v8.125.0 with ddtrace pinned to v4.8.3, this seems to be resolved.