Traffic Parrot, an application virtualization tool, step-by-step Review Tutorial:
Traffic Parrot minimizes software testing expenses and assists testers in expediting product delivery by utilizing application virtualization, alternatively known as imitation or simulation of APIs.
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Imitation and simulation are vital methods that can aid in isolating application testing.
Isolating testing implies shifting away from intricate test scenarios and incorporating multiple applications to scenarios that exclusively concentrate on the application in question.
The phrases Imitation and Simulation essentially denote substituting a genuine service with a feigned one, permitting direct control over its behavior.
In this Traffic Parrot review, we will explore the usage of Traffic Parrot, an application virtualization tool that introduces new possibilities for JMS teams interested in imitation or simulation.
What You Will Learn:
Reasons for Adopting Service virtualization
- Creating automation suites as early as possible
- Succinctly simulating experiment conditions to decrease dependencies and costs
- Implementing shift left testing and running parallel with the development team
- Working within an authentic Agile environment
The following techniques enable you to:
- Test your application when its dependencies are unavailable.
- Test scenarios that are usually difficult to reproduce.
- Reduce time spent on setting up test data.
Traffic Parrot streamlines JMS testing by enabling you to establish JMS test scenarios that would otherwise necessitate complex test data configurations across numerous systems.
It supports IBM® WebSphere MQ as well as Apache ActiveMQ, further enriching the JMS testing toolkit.
The Issue Traffic Parrot Resolves
First, let’s explore the various circumstances under which we would like to imitate and simulate JMS messages.
A standard communication pattern requires an IBM® WebSphere MQ broker with a request queue and a response queue:
- System A initiates a request message to the request queue.
- The request message is then consumed by System B.
- After performing internal processing, System B responds by sending a response message to the response queue.
- Subsequently, System A consumes the response message.
In this scenario, the testing of System B can encounter various difficulties such as:
- An API or the entire system may not yet exist.
- Another tester may already be utilizing it.
- The test environment may be experiencing technical difficulties.
- Setting up test data may be challenging or impossible.
- Simulating error responses may be impossible.
In such situations, we can utilize Traffic Parrot to imitate System B, allowing isolated testing of System A. Traffic Parrot prototypes System B by consuming request messages and producing response messages accordingly.
Using Traffic Parrot to Dispatch JMS Response Messages
Now, let us examine a standard workflow involving Traffic Parrot in imitating and simulating the behavior of a system that receives and sends JMS messages.
As a tester of System A, I desire for Traffic Parrot to feign to be System B by sending response messages to System A. To achieve this, we need to configure Traffic Parrot to respond with a particular message on a particular queue. This configuration is done using Traffic Parrot’s browser-based user interface.
Next, we activate Traffic Parrot’s replay mode to give instructions for responding to the request messages.
And that’s it! It’s as simple as that – we now possess a fully operational JMS imitation. System A can now be tested, and we can modify Traffic Parrot’s response (impersonating System B) to cater to our test scenario.
This includes both typical response messages and error responses that may be challenging to reproduce using actual data (e.g. an item being out of stock).
Traffic Parrot offers numerous advanced features that enable simulation of complex behavior with minimal effort.
Let us now explore some of these.
It is common for response messages to contain information from the request message.
For instance, perhaps System B is responding to a list of requested items and we must mention each item in the response. We can use dynamic responses in Traffic Parrot to accomplish this. The example below illustrates how this can be done for an XML message. Similar outcomes are possible for JSON messages and raw text messages as well.
(Note: Click on the image for an enlarged view)
The templating approach is very powerful. For example, we can:
- Utilize request data in the response.
- Incorporate the current date/time in the response.
- Generate random numbers in the response.
- Loop over parts of the request in the response.
Testing Established Systems with Traffic Parrot
When testing an existing system that was previously solely subjected to end-to-end testing with all its dependencies present, there are typically many message types that need configuration when leveraging service virtualization for isolated testing.
Traffic Parrot provides recording and replay functionality that assists in capturing existing messages, which can later be edited to fit our testing needs. Traffic Parrot accomplishes this by intercepting request and response messages, pairing them, creating mappings, and subsequently forwarding them to their intended destinations.
This is an effective technique for rapidly conducting tests on an existing system without having to spend significant time upfront manually defining mappings on a one-by-one basis. Instead, we can record traffic in a test environment and adjust the captured mappings to fulfill our testing requirements.
To gain further insight into this process, check out this JMS IBM MQ record and replay demo.
Traffic Parrot allows us to test an application without requiring developer assistance.
We can configure JMS behavior through a user-friendly browser-based UI, facilitating quick and easy testing of our system in numerous scenarios.
We also explored how Traffic Parrot can be utilized to record and replay traffic from/to existing systems, providing a head start in configuring initial JMS response messages for testing. This is particularly helpful when dealing with legacy systems that were not designed with testability in mind.
If you have any queries regarding this tool, feel free to reach out to us.