Solving QA Environment Availability Issues with Partial Pass-Through JMS IBM MQ Mocks

Testing teams often face common QA environment challenges:

• Environment downtime
• Intermittent errors from backend systems
• Test data setup takes weeks
• Teams conflict over shared test data
• Limited test scenarios

While the long-term solution involves stabilizing shared environments and implementing testing pyramids, here's a quick fix using Traffic Parrot's partial pass-through mocking capabilities.

We implemented this solution for a mobile onboarding application connecting to IBM MQ middleware. By creating mock queues alongside production queues, we enabled:

• Simultaneous mocked and real responses based on test data
• Automated test data setup and reset
• Extended test coverage for previously unavailable scenarios
• Reduced environment dependencies

 Key Implementation Steps:

• Create additional mock queues
• Reconfigure client to use mock queues
• Set up pass-through mocks in Traffic Parrot

The beauty of this approach? You maintain real system integration while having the flexibility to mock specific scenarios. For example, we successfully mocked unsupported mobile service types while passing through all other requests to the actual backend.

Want to try it yourself? Check out Traffic Parrot's demo applications on GitHub, which have step-by-step implementation guides.