Troubleshooting python integrations tasks failing with runtime error: unable to find any timezone configuration

Overview & Summary

After upgrading to Swimlane Platform 10.26, scheduled Python tasks, custom scripts, and plugin integrations (such as the Microsoft Exchange Email plugin) fail during execution with the error:

RuntimeError: Unable to find any timezone configuration

This occurs because dependencies such as pendulum call pendulum.now(), which requires a system-level or environment-level timezone definition. When no timezone configuration is detected in the runtime container environment, the task halts immediately.

Environment & Affected Versions

Product: Swimlane Platform

Affected Versions: 10.26.x

Components Impacted: swimlane-tasks, swimlane-api, Python Tasks, Plugin Integration(e.g., Microsoft Exchange Email)

Symptoms & Error Details

Python tasks or scheduled integrations fail immediately upon execution.

Integrations that rely on the pendulum date/time library fail during initialization or datetime parsing.

Execution logs and tracebacks display on Hangfire:

RuntimeError: Unable to find any timezone configuration (Traceback typically originates from pendulum/tz/local_timezone.py)

Root Cause

The base container environment for swimlane-tasks and swimlane-api does not have a default system timezone configured or the TZ environment variable set. When Python packages like pendulum query the local system timezone via pendulum.now(), the lookup fails and throws a runtime exception.

Workaround & Resolution

Because integration plugins cannot be modified directly, setting the environment variable at the container deployment level provides a global platform-level fix across all tasks and plugins.

Method 1: Container-Level Environment Variable Configuration (Recommended)

Add the TZ environment variable with value UTC to both the swimlane-tasks and swimlane-api Kubernetes deployments.

Step 1: Pause ArgoCD / GitOps Sync (if applicable)

If ArgoCD manages your cluster deployments, pause auto-sync or scale down the application controller temporarily to prevent deployment overrides; otherwise, ignore this step 1:

kubectl scale deployment argocd-application-controller -n argocd --replicas=0

Step 2: Update swimlane-tasks Deployment

Export or edit the deployment: kubectl edit deployment swimlane-tasks -n <swimlane-namespace> 2. Locate the primary container (swimlane-tasks) under spec.template.spec.containers and add the TZ environment variable:

spec:
  template:
    spec:
      containers:
      - env:
        - name: TZ
       value: UTC

3. Save and exit to trigger a rolling update.

Step 3: Update swimlane-api Deployment

Edit the swimlane-api deployment: kubectl edit deployment swimlane-api -n <swimlane-namespace> 2. Locate the swimlane-api container under spec.template.spec.containers and add:

spec:
  template:
    spec:
      containers:
      - env:
        - name: TZ
       value: UTC

3. Save and exit to trigger a rolling update.

Method 2: Custom Python Script Workaround (Optional / Custom Tasks Only)

For standalone custom Python tasks, we can initialize the timezone directly within the script header:

import os

import time

os.environ['TZ'] = 'UTC'

time.tzset()

Note: This method only applies to custom tasks and cannot be used for Plugin integration plugins (e.g., Microsoft Exchange) else need to fork the tasks and add the code at the beginning.

Verification & Testing

Trigger a test run of the affected Python task or integration and confirm successful execution without timezone errors.