Repetir o processo é fácil. Saber o que te disseram, não. 

If you run an Appium tests, you can already retry a failed test. Frameworks like TestNG has a retry analyzer. JUnit teams add an extension or a build plugin setting. An engineer can wire one up in an afternoon. So it’s fair to ask what else a team needs. 

The retry itself isn’t the hard part. The hard part is everything around it: where the retry logic lives, how the rest of the run is configured, and whether anyone can see what happened afterward. 

Three problems around a retry 

1. The retry logic lives in the test code. In TestNG, retries are wired in through an analyzer or listener. In JUnit, through an extension or build configuration. Each team picks its own approach, and changing a retry count means changing code and rebuilding.
2. The rest of the run is configured somewhere else. Which cloud to connect to, which app build, which devices, which tests to run. These tend to end up spread across capabilities, CI scripts, and annotations. When a run behaves differently than expected, the first task is figuring out where each setting came from.
3. Retries leave little trail. A test that fails once and passes on attempt two often looks like a pass. The failed attempt may exist in local build output, but it isn’t sitting in your test report next to the rest of the run. The team can’t easily tell a clean pass from a pass that needed help, which is the information that points to a flaky test or an unstable environment.

None of these is dramatic on its own. Together they explain why a team that has “already handled retries” still spends release week rerunning tests by hand to work out what’s real. 

Why this gets more expensive as suites grow 

An estimated 40–50% of enterprise code is now AI-generated (Digital.ai). More code means more surfaces for failures, and test suites grow along with it. 

Flaky tests are a known tax at scale: Atlassian attributes roughly 15% of its Jira backend repository failures to flaky tests, with the resulting reruns wasting over 150,000 developer hours a year (Atlassian, 2025). 

If you’re still tuning locators and waits, start with Tentativas repetidas não corrigem um localizador defeituoso.. What follows is about the failures that remain after that. 

Test Orchestrator: a middle layer for how tests run 

Test Orchestrator in Digital.ai Testing sits between your Appium tests and the Digital.ai Testing platform. It manages how tests run and automatically retries failures, without changing the tests themselves or manually restarting a build. It’s a Java-based agent distributed as a JAR file. You add it to your existing test project and use it when the tests run. 

One YAML file for the run. Cloud connection, app, device selection, which tests to run, and how many times to retry a failure all live in a centralized, YAML-based configuration. A retry count becomes a configuration value, not a code change, and every setting for a run is in one place. 

Retries you can see. When a failed test is retried, each attempt and its outcome is visible in Test Reporter. The team can tell which failures repeated, which passed on retry, and whether a critical test stopped the run. A pass on attempt two is no longer indistinguishable from a clean pass. 

Your tests stay as they are. You add Test Orchestrator as the layer in the middle. Existing test methods don’t change. It works with JUnit and TestNG, fits into CI/CD pipelines as a quality gate, and is available for both SaaS and on-premises customers. 

What changes day to day 

• Engenheiros de controle de qualidade spend less time manually rerunning failed tests to find out whether a failure repeats. When something fails, the attempts in Test Reporter give them a clearer starting point. 

• QA managers know what needs attention before release sign-off. Repeated failures get investigated first, passed-on-retry tests get tracked, and a critical test that stopped the run is easy to spot, so the team doesn’t treat every failed run the same way. 

When a framework retry is enough 

If your suite is small, one team owns it, and a pass or fail in the console is all you need, a retry analyzer may be all you need. Test Orchestrator is aimed at teams with enough automated tests that investigating failures and rerunning individual tests takes real time each release. 

It also doesn’t remove the cause of a flaky test. A test that passes on its second attempt is still telling you something, whether it’s an unstable environment or a locator that’s starting to drift. The point is that the signal stays visible, so you can act on it. 

From “did it pass eventually” to “what happened on each attempt” 

Adding a retry takes an afternoon. Knowing what the retries told you, and managing how every run is set up, is the part that gets harder as suites grow. Test Orchestrator puts both in one place and leaves your tests alone. 

Saiba mais no Test Orchestrator documentation.