Designing Automated Smoke Tests for Post-Deployment Validation of IVR Flow Changes

How-To-Articles
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Designing Automated Smoke Tests for Post-Deployment Validation of IVR Flow Changes

What This Guide Covers

You are designing a suite of automated “smoke tests” to validate that your Genesys Cloud Architect flow deployments are functional and have not introduced regression errors. Smoke tests are high-level, automated checks that run immediately after a new flow version is published. They simulate actual customer calls or messages to verify that critical paths-such as emergency routing, Data Action lookups, and queue transfers-are working correctly. When complete, you will have a reliable “Go/No-Go” signal for every production release, significantly reducing the risk of a “silent failure” where a published flow appears healthy but disconnects callers or fails to route correctly.

Prerequisites, Roles & Licensing

  • Genesys Cloud: CX 1, 2, or 3.
  • Permissions:
    • Architect > Flow > View
    • Conversations > Call > Create (for telephony testing)
  • Tooling:
    • Cyara or Hammer (Commercial) OR Playwright/Puppeteer (Custom) for Digital.
    • Python/Requests for API-driven logic testing.

The Implementation Deep-Dive

1. Defining “Critical Paths”

A smoke test should not test every edge case. Focus on the “Happy Path” and the “Safety Net”:

  1. The Entry Point: Does the DID correctly route to the new flow version?
  2. The Logic Gate: Does the Data Action return a valid response?
  3. The Destination: Does the call successfully enter the intended ACD queue?
  4. The Safety Net: Does the error-handler branch work if a Data Action fails?

2. Digital Smoke Testing (Web Messaging)

Using Playwright to simulate a customer interaction is the most effective way to test Digital flows.

// tests/smoke/ivr-smoke-test.spec.js
const { test, expect } = require('@playwright/test');

test('Messenger Flow Smoke Test', async ({ page }) => {
  await page.goto('https://your-test-site.com');
  
  // Open Messenger
  await page.click('#genesys-messenger-launcher');
  
  // Send a message that triggers a specific routing task
  await page.fill('input[type="text"]', 'Check my balance');
  await page.keyboard.press('Enter');
  
  // Assert that the bot responds with the expected menu or data
  await expect(page.locator('.message-bubble')).toContainText('Your current balance is');
});

3. Voice Smoke Testing (API-Driven)

For voice, you can use the Genesys Cloud Conversations API to initiate a test call and then inspect the conversation details to see which Architect segments were hit.

import requests
import time

def run_voice_smoke_test(token, test_number, target_flow_id):
    # 1. Place an outbound call to your IVR entry point
    headers = {"Authorization": f"Bearer {token}"}
    payload = {
        "phoneNumber": test_number,
        "callFromId": "test-agent-id"
    }
    resp = requests.post("https://api.mypurecloud.com/api/v2/conversations/calls", headers=headers, json=payload)
    conversation_id = resp.json()['id']
    
    # 2. Wait for the IVR to process
    time.sleep(10)
    
    # 3. Inspect the conversation timeline
    detail_resp = requests.get(f"https://api.mypurecloud.com/api/v2/analytics/conversations/{conversation_id}/details", headers=headers)
    
    # Verify the flow ID and version in the participants/segments
    segments = [s for p in detail_resp.json()['participants'] for s in p['sessions'][0]['segments']]
    flow_segment = next((s for s in segments if s.get('segmentType') == 'ivr'), None)
    
    assert flow_segment['id'] == target_flow_id
    print("✓ Flow reached successfully")

4. Mocking Data Actions for Pure Logic Tests

If you want to test the logic of the flow without depending on external CRM uptime, use a Mock Data Action.

  • Create a Data Action that points to a controlled “Mock Server” (e.g., a simple AWS Lambda).
  • During the smoke test, configure the Mock Server to return specific values (Success, Timeout, 404).
  • Verify the Architect flow branches correctly for each scenario.

5. Post-Deployment CI/CD Integration

Trigger these tests automatically as part of your deployment pipeline.

# GitLab CI Example
deploy_flow:
  script:
    - archy publish --file main_flow.yaml
    - python scripts/run_smoke_tests.py --env prod
  rules:
    - if: $CI_COMMIT_BRANCH == "main"

Validation, Edge Cases & Troubleshooting

Edge Case 1: Testing “After Hours” Logic

If you deploy at 10:00 AM, how do you smoke-test the “Closed” branch of your flow?
Solution: Build a “Test Bypass” into your Architect flow. If the ANI matches a specific internal test number, allow the flow to be “forced” into the After-Hours branch using a participant data flag.

Edge Case 2: Toll Charges for Voice Testing

Repeatedly calling production DIDs for smoke testing can incur significant carrier costs and tie up trunks.
Solution: Use internal SIP trunks or Genesys Cloud WebRTC testing where possible to avoid PSTN costs.

Edge Case 3: Flaky Web Elements in Digital Testing

The Messenger widget may take a few seconds to load, causing tests to fail randomly.
Solution: Use “Wait for Selector” with a generous timeout (e.g., 30 seconds) and ensure your test environment has stable network connectivity.

Official References