Monitoring & Regression Testing
Detect performance regressions, track historical trends, and identify scalability limits across repeated test executions.
StresStimulus compares past results from protocol and browser test cases to reveal performance and quality deterioration, evaluate changes against established baselines, and identify trends that individual test review may miss.
Monitor Application Quality Across Test Executions
Identify quality and performance changes that individual test results might not show.
Application performance and quality can change gradually or unexpectedly as software, configurations, infrastructure, user populations, and usage patterns evolve. Historical monitoring helps reveal these changes, detect emerging problems, and keep application performance and quality within acceptable limits over time.
StresStimulus maintains Test Run History for cross-execution comparison and analysis. Use comprehensive regression analysis to compare individual runs against established baselines and Trend Reports to identify gradual changes across multiple executions.
Detect Regressions Against Historical Baselines
Identify performance and quality deterioration automatically, even when individual tests pass.
| Metric | Baseline | Current | Difference | Status |
|---|---|---|---|---|
| P95 response | 800 ms | 1,040 ms | +30% | Fail |
| Throughput | 200/s | 184/s | -8% | Warn |
| Error rate | 0.5% | 0.5% | 0% | Pass |
Regression analysis works independently of standard Pass/Fail Rules, revealing deterioration relative to previous results even when established acceptance criteria are satisfied.
StresStimulus compares completed test executions against configurable baselines, including a selected previous run or statistical values calculated from recent compatible runs. Define warning and failure thresholds to detect deterioration in response times, throughput, errors, and other supported performance and quality measurements.
Test Run History provides access to previous executions and regression classifications. Select any execution to compare its measurements against the baseline, review absolute and percentage differences, and identify changes in individual transactions.
Pinpoint Regressions Across Thousands of Measurements
Find critical performance and quality changes in minutes, without manually comparing extensive test reports.
A single test execution can produce thousands of measurements across test cases, transactions, and metrics. StresStimulus automatically compares these measurements with configurable historical baselines, and highlights changes with color-coded severity levels.
Focus on what matters. Filter comparison results by regression severity, including errors, warnings, or improvements, and search by transaction or metric name. Quickly narrow thousands of measurements to specific results requiring investigation, with baseline values, current values, and differences displayed side by side.
Compare multiple executions. Open separate regression grids for different test runs and comparison conditions, then switch between tabs to investigate changes across releases or configurations without repeatedly rebuilding comparisons.
Track Historical Performance Trends
Discover gradual performance deterioration across repeated executions.
Generate Trend Reports using compatible historical runs, selected runs, or configured analysis windows. Examine response times, throughput, errors, and timeouts to identify patterns of improvement, deterioration, or stability.
Automatically generated Key Findings highlight significant changes, including increasing P95 response times, declining throughput, and consecutive degrading runs. Trend analysis can reveal gradual deterioration that has not yet triggered an individual regression warning or failure.
Identify Scalability Limits
See how application performance changes as concurrent load increases.
Compare compatible test executions performed at different virtual-user load levels. Examine response times, throughput, errors, and timeouts to identify performance deterioration, throughput plateaus, and other scalability constraints.
Scalability Analysis identifies observed degradation boundaries between tested load levels and highlights the measurements and transactions contributing to the deterioration.
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Detect Performance Problems Before They Reach Production
Monitor tests, compare historical results, and make performance changes easier to identify.