name: detecting-performance-regressions description: Automatically detect performance regressions in CI/CD pipelines by comparing metrics against baselines. Use when validating builds or analyzing performance trends. Trigger with phrases like "detect performance regression", "compare performance metrics", or "analyze performance degradation". version: 1.0.0 allowed-tools: "Read, Write, Edit, Grep, Glob, Bash(ci:), Bash(metrics:), Bash(testing:*)" license: MIT author: Jeremy Longshore jeremy@intentsolutions.io

Performance Regression Detector

This skill provides automated assistance for performance regression detector tasks.

Overview

This skill automates the detection of performance regressions within a CI/CD pipeline. It utilizes various methods, including baseline comparison, statistical analysis, and threshold violation checks, to identify performance degradation. The skill provides insights into potential performance bottlenecks and helps maintain application performance.

How It Works

1. Analyze Performance Data: The plugin gathers performance metrics from the CI/CD environment.
2. Detect Regressions: It employs methods like baseline comparison, statistical analysis, and threshold checks to detect regressions.
3. Report Findings: The plugin generates a report summarizing the detected performance regressions and their potential impact.

When to Use This Skill

This skill activates when you need to:

• Identify performance regressions in a CI/CD pipeline.
• Analyze performance metrics for potential degradation.
• Compare current performance against historical baselines.

Examples

Example 1: Identifying a Response Time Regression

User request: "Detect performance regressions in the latest build. Specifically, check for increases in response time."

The skill will:

1. Analyze response time metrics from the latest build.
2. Compare the response times against a historical baseline.
3. Report any statistically significant increases in response time that exceed a defined threshold.

Example 2: Detecting Throughput Degradation

User request: "Analyze throughput for performance regressions after the recent code merge."

The skill will:

1. Gather throughput data (requests per second) from the post-merge CI/CD run.
2. Compare the throughput to pre-merge values, looking for statistically significant drops.
3. Generate a report highlighting any throughput degradation, indicating a potential performance regression.

Best Practices

• Define Baselines: Establish clear and representative performance baselines for accurate comparison.
• Set Thresholds: Configure appropriate thresholds for identifying significant performance regressions.
• Monitor Key Metrics: Focus on monitoring critical performance metrics relevant to the application's behavior.

Integration

This skill can be integrated with other CI/CD tools to automatically trigger regression detection upon new builds or code merges. It can also be combined with reporting plugins to generate detailed performance reports.

Prerequisites

• Historical performance baselines in {baseDir}/performance/baselines/
• Access to CI/CD performance metrics
• Statistical analysis tools
• Defined regression thresholds

Instructions

1. Collect performance metrics from current build
2. Load historical baseline data
3. Apply statistical analysis to detect significant changes
4. Check for threshold violations
5. Identify specific regressed metrics
6. Generate regression report with root cause analysis

Output

• Performance regression detection report
• Statistical comparison with baselines
• List of regressed metrics with severity
• Visualization of performance trends
• Recommendations for investigation

Error Handling

If regression detection fails:

• Verify baseline data availability
• Check metrics collection configuration
• Validate statistical analysis parameters
• Ensure threshold definitions are valid
• Review CI/CD integration setup

Resources

• Statistical process control for performance testing
• CI/CD performance testing best practices
• Regression detection algorithms
• Performance monitoring strategies