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ReportPortal is widely used for analyzing automated test results, aggregating logs, classifying failures with ML, and tracking quality trends over time. When used correctly, it significantly improves feedback speed and decision-making.
However, many teams fail to unlock its full potential. The problem is rarely the tool itself – it’s how teams analyze and interpret the data.
Below are the most common mistakes teams make when working with test results in ReportPortal, along with practical advice on how to avoid them.
1. Analyzing reports without a clear goal
A frequent mistake is reviewing reports without a specific purpose. Teams open a dashboard, notice the number of failed tests, and move on.
ReportPortal provides data, not conclusions. Without clear questions, analysis remains superficial. Unhelpful questions:
How many tests failed?"
"Is the build green?"
Better questions:
Which failure types are increasing over time?
Which tests are the flakiest?
Where do we lose the most time during triage?
How to avoid it: Define the goal before analyzing results – release quality, test stability, feedback speed, or technical debt. Build dashboards around that goal.
2. Ignoring custom defect types
Many teams rely only on default defect types (Product Bug, Automation Bug, System Issue, No Defect, To Investigate) and never go further. As a result:
all failures look the same
ML classification becomes less effective
ReportPortal delivers real value only when defect types are used consistently.
Common issue: Everything is marked as "To Investigate", and nothing gets properly categorized.
How to avoid it:
Define a clear set of defect types and keep them up to date with your needs
Analyze each failure and explicitly assign the correct defect type – this creates training data for the Analyzer, so similar issues can be automatically recognized and categorized correctly in future runs
3. Blind trust in ML classification
ReportPortal’s ML features are powerful, but they are not a replacement for process. Some teams either ignore ML entirely or trust it without verification.
Problems occur when:
training data is inconsistent
predictions are not reviewed
test logs are unstable
How to avoid it:
Regularly confirm or correct ML predictions.
Ensure consistent logging for similar failures.
Treat ML as an assistant, not a decision-maker
4. Mixing incompatible test runs in one analysis
Another common mistake is analyzing tests with different purposes together:
UI and API tests
smoke and regression suites
This makes metrics misleading. A failure rate acceptable for nightly runs may be unacceptable for smoke tests.
How to avoid it:
Separate launches by test purpose.
Use attributes or separate projects.
5. Underestimating the importance of log quality
ReportPortal cannot compensate for poor logging. If logs are inconsistent or lack context, analysis becomes manual and slow. Typical issues:
the same error reported differently
missing steps or environment details
no clear failure reason
How to avoid it:
Standardize test logging.
Log causes, not just symptoms.
Ensure similar failures produce similar messages.
6. No clear ownership of test result analysis
A critical organizational mistake is having "shared ownership" of ReportPortal – meaning no ownership at all. When no one is responsible:
dashboards degrade over time
defect classification becomes inconsistent
insights are lost
How to avoid it:
Assign a clear owner (for example, QA Lead).
Continuously improve dashboards and metrics.
Treat ReportPortal as a product, not just a log repository.
ReportPortal is a decision-support tool, not just a reporting system. Most mistakes teams make are process-related, not technical. Teams that define clear analysis goals, invest in defect classification and logging quality, and assign ownership, turn ReportPortal into a powerful driver of quality and efficiency rather than a source of noisy data.