dosubot[bot] commented on issue #8427:
URL: 
https://github.com/apache/incubator-devlake/issues/8427#issuecomment-2854427237

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   <!-- Answer -->
   The error you're encountering might be related to compatibility issues 
between the Gin framework and the base image version used in your Kubernetes 
deployment. Since you mentioned upgrading some base image versions in the 
Dockerfile, it's possible that these changes are affecting the runtime 
environment in a way that leads to the "unknown caller pc" error.
   
   Here are a few steps you can take to troubleshoot and potentially resolve 
the issue:
   
   1. **Check Base Image Versions**: Ensure that the base image versions in 
your Dockerfile are compatible with the Gin framework version (`v1.9.1`) used 
in the project 
<sup>[[1]](https://github.com/apache/incubator-devlake/blob/main/backend/go.mod)</sup>.
 You can compare the versions used locally versus those in the cloud deployment.
   
   2. **Review Dockerfile Dependencies**: Verify the dependencies and their 
versions listed in the Dockerfile. The current versions are:
      - Golang: `golang:1.20.5-bookworm`
      - libgit2: `v1.3.2`
      - Mockery: `github.com/vektra/mockery/v2@v2.20.0`
      - Swag: `github.com/swaggo/swag/cmd/swag@v1.16.1`
      - Python: `python:3.9-slim-bookworm` 
<sup>[[2]](https://github.com/apache/incubator-devlake/blob/main/backend/Dockerfile)</sup>.
   
   3. **Kubernetes-Specific Issues**: Since the error only appears in 
Kubernetes cloud deployment, consider checking for any Kubernetes-specific 
configurations or limitations that might affect the Gin framework. There is a 
known issue related to Kubernetes deployment in the project, specifically a "Go 
Panic in OpenShift Kubernetes" caused by the Dynatrace agent 
<sup>[[3]](https://github.com/apache/incubator-devlake-website/blob/main/docs/Troubleshooting/Installation.md)</sup><sup>[[4]](https://github.com/apache/incubator-devlake-website/blob/main/versioned_docs/version-v0.21/Troubleshooting/Installation.md)</sup>.
 Although this might not be directly related, reviewing similar issues could 
provide insights.
   
   4. **Environment Differences**: Investigate any differences between your 
local and cloud environments, such as network configurations, resource limits, 
or security settings that might impact the application's behavior.
   
   5. **Logs and Monitoring**: Enable detailed logging and monitoring in your 
Kubernetes deployment to capture more information about the error and its 
context. This might help identify the root cause.
   
   If these steps don't resolve the issue, consider isolating the problem by 
deploying a minimal version of your application with only the Gin framework and 
its dependencies to see if the error persists.
   
   
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