Kafka and End-to-End Testing: Navigating a Complex Landscape

Apache Kafka powers many event-driven architectures but introduces unique challenges for end-to-end testing. This post seeks to offer solutions for effectively testing in such environments.

Domain Testing: A Closer Look

This strategy focuses on testing individual domains within a larger Kafka-based ecosystem. It allows for quicker validation of features, even when services are owned by different teams

First, let’s describe a simple Kafka-based microservice environment

In the whole setup, there are three main services. DEV TEAM 1 owns Service A and Service B, while DEV TEAM 2 is in charge of Service C. Each of these services has its own database and offers an API to fetch event data.

TEAM A recently added a new feature in Service A to send events directly to Service C. The obvious way to test this would be for Service A to publish an event, then use Service C's API to retrieve and verify the data. However, this approach comes with its own set of challenges:

1. TEAM 2 hasn't yet built a feature in Service C to handle this specific event.

2. Any bug in Service C could cause TEAM 1's automation tests to fail.

The Solution

To validate their new feature quickly and before full end-to-end testing, TEAM 1 should introduce an additional testing layer known as 'domain testing.' In this new test setup, the process will look something like this:

1. Service A publishes an event.

2. Verify that Service B successfully sends an event to Topic C.

To make this assertion, our tests need to consume events from Topic C. To prevent missing events due to race conditions between the test and Service C, the event consumer should belong to a different group-id.

So what are our options for managing group-ids?

1. Creating a new group-id for each test case would result in an unmanageable number of group-ids.

2. Assigning a unique group-id for each automation project could still lead to race conditions during parallel testing.

The best approach is to establish a single, dedicated automation service with one group-id and offer an API to fetch the test data. This allows for both efficient management and reduced risk of race conditions.

Conclusion

In Kafka-based architectures, advanced testing strategies are essential. Domain testing and specialized tools can help navigate these complexities.