Baseline Testing & Comparison

Set a baseline test result and compare future tests to track performance changes over time. This helps identify regressions and improvements.

Setting a Baseline #

After running a test, click ‘Set as Baseline’ to save that test result as your reference point. Each URL can have its own baseline.

Steps:

1. Run a test with your desired configuration

2. Review the results

3. Click ‘Set as Baseline’ button

4. The baseline is now saved for that URL

Automatic Comparison #

When you run a new test for a URL that has a baseline, the app automatically shows a comparison section highlighting differences.

Steps:

1. Run a test for a URL with an existing baseline

2. Comparison appears automatically after test completes

3. See side-by-side metrics: Baseline vs Current

4. Color-coded indicators show improvements (green) and regressions (red)

Understanding Comparison Metrics #

The comparison shows percentage changes for key metrics, helping you quickly identify performance changes.

Metrics:

• Response Time: Lower is better (green = faster, red = slower)
• Success Rate: Higher is better (green = improved, red = decreased)
• Requests per Second: Higher is better (green = more throughput)
• Total Requests: Reference metric showing test scale

Managing Baselines #

You can update or clear baselines as needed. Baselines are stored per URL, so different websites can have different baselines.

Actions:

• Update Baseline: Click ‘Update Baseline’ to replace existing baseline
• Clear Baseline: Click ‘Clear Baseline’ to remove it
• Set from History: Open History and set any past test as baseline
• Baseline Indicator: Form view shows when a URL has a baseline set

Baseline Use Cases #

• Performance Monitoring: Track performance over time and catch regressions before they impact users
• Regression Detection: Automatically identify when performance degrades compared to your baseline
• Improvement Validation: Verify that optimizations and improvements actually improve performance
• A/B Testing: Compare performance of different server configurations or deployments