Table of Contents
What Does Test Analytics Mean?
Test analytics refers to the collection, visualization, and interpretation of data generated from automated test executions. These analytics help teams understand test health, identify failure patterns, measure stability over time, and optimize testing strategies by turning raw test data into actionable insights.
Why Test Analytics Matters
Modern software teams rely on continuous feedback to maintain quality at speed. Without analytics, test results exist in isolation, making it difficult to spot recurring issues or performance regressions.
Test analytics centralizes these insights, helping teams:
- Detect flaky or unstable tests before they affect releases.
- Track test coverage, duration, and success rates across environments.
- Identify patterns tied to specific frameworks, clusters, or configurations.
- Make data-driven decisions to improve testing efficiency and reliability.
How Test Analytics Works with Testkube
- Centralized Visibility: Testkube aggregates test results across multiple clusters, frameworks, and environments.
- Trend Analysis: Track pass/fail trends, execution times, and failure rates over time to evaluate stability.
- Flakiness Detection: Identify tests with inconsistent outcomes and investigate root causes using historical logs.
- Performance Metrics: Visualize resource usage, latency, and response times for performance-oriented test runs.
- Cross-Environment Comparison: Compare how the same tests behave across staging, production, or regional clusters.