Test Impact Analysis is an approach to obtain a subset of tests that are impacted by the code changes. This approach is mostly applied to unit testing where the link between the code and its associated tests is easy to obtain. On the integration level, however, it is not straightfoward to find such a link programatically, especially when the integration tests are held into separate repositories. We propose an approach for selecting integration tests based on the runtime analysis of code changes to reduce the test execution overhead. We provide a set of tools and framework that can be plugged into existing CI/CD pipelines. We have evaluated the approach on a range of opensource Java programs and found ≈50% reduction in tests on average, and above 80% in a few cases. We have also applied the approach to a large-scaled system currently in production and found similar results.