Python Troubleshooting¶

Attach a python debugger to a running pod. No need to modify the application's code or restart it.

Steps:

1. Install Robusta

2. Manually trigger this action using the Robusta CLI and the pod's name:

robusta playbooks trigger python_debugger name=podname namespace=default

2. Follow the instructions you receive and run kubectl port-forward

3. In Visual Studio Code do a Remote Attach as per the instructions

Now you can use break points and log points in VSCode.

This action has been deprecated. To enable it add the following to your generated_values.yaml

Add this to your Robusta configuration (Helm values.yaml):

customPlaybooks:
- actions:
  - python_debugger: {}
  triggers:
  - on_pod_all_changes: {}

The above is an example. Try customizing the trigger and parameters.

custom_annotations (str dict)

custom annotations to be used for the running pod/job

process_substring (str)

process name (or substring).

pid (int)

pid

interactive (bool) = True

if more than one process matches, interactively ask which process to choose.

port (int) = 5678

debugging port.

• on_container_oom_killed

• on_image_pull_backoff

• on_pod_all_changes

• on_pod_crash_loop

• on_pod_create

• on_pod_delete

• on_pod_evicted

• on_pod_oom_killed

• on_pod_update

• on_prometheus_alert

This action can be manually triggered using the Robusta CLI:

robusta playbooks trigger python_debugger name=POD_NAME namespace=POD_NAMESPACE 

Attach a python profiler to a running pod, and run a profiling session for the specified duration.

No need to change the profiled application code, or to restart it.

This is powered by PySpy

This action has been deprecated. To enable it add the following to your generated_values.yaml

Manually trigger with:

robusta playbooks trigger python_profiler name=podname namespace=default process_name=your-process seconds=5

Add this to your Robusta configuration (Helm values.yaml):

customPlaybooks:
- actions:
  - python_profiler: {}
  triggers:
  - on_pod_all_changes: {}

The above is an example. Try customizing the trigger and parameters.

custom_annotations (str dict)

custom annotations to be used for the running pod/job

seconds (int) = 2

Profiling duration.

process_name (str)

Profiled process name prefix.

include_idle (bool)

Include idle threads

• on_container_oom_killed

• on_image_pull_backoff

• on_pod_all_changes

• on_pod_crash_loop

• on_pod_create

• on_pod_delete

• on_pod_evicted

• on_pod_oom_killed

• on_pod_update

• on_prometheus_alert

This action can be manually triggered using the Robusta CLI:

robusta playbooks trigger python_profiler name=POD_NAME namespace=POD_NAMESPACE 

Monitor a Python process for X seconds and show memory that was allocated and not freed.

Use this to track memory leaks in your Python application on Kubernetes.

This action has been deprecated. To enable it add the following to your generated_values.yaml

Manually trigger with:

robusta playbooks trigger python_memory name=podname namespace=default

Add this to your Robusta configuration (Helm values.yaml):

customPlaybooks:
- actions:
  - python_memory: {}
  triggers:
  - on_pod_all_changes: {}

The above is an example. Try customizing the trigger and parameters.

custom_annotations (str dict)

custom annotations to be used for the running pod/job

process_substring (str)

process name (or substring).

pid (int)

pid

interactive (bool) = True

if more than one process matches, interactively ask which process to choose.

seconds (int) = 60

Memory allocations analysis duration.

• on_container_oom_killed

• on_image_pull_backoff

• on_pod_all_changes

• on_pod_crash_loop

• on_pod_create

• on_pod_delete

• on_pod_evicted

• on_pod_oom_killed

• on_pod_update

• on_prometheus_alert

This action can be manually triggered using the Robusta CLI:

robusta playbooks trigger python_memory name=POD_NAME namespace=POD_NAMESPACE