Part 8: Results Analysis & Reporting (Performance Testing Revision Cheat Sheet)

 

📌 Purpose

Results analysis interprets the raw performance data to identify bottlenecks, verify SLA compliance, and provide actionable insights. Reporting communicates findings to stakeholders.

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🎯 Key Analysis Steps

1. Data Validation

   • Ensure test ran successfully with no script or environment errors.

   • Confirm monitoring metrics are complete and consistent.

2. Analyze Metrics

   • Response Time: Average, 90th percentile, maximum.

   • Throughput: Transactions/sec, data processed/sec.

   • Error Rates: HTTP errors, failed transactions.

   • Resource Utilization: CPU, memory, disk I/O, network usage.

3. Identify Bottlenecks

   • Correlate high response times with high CPU, memory, DB, or network usage.

   • Check for thread pool exhaustion, GC pauses, DB locks.

   • Compare baseline vs peak load performance.

4. Trend & Pattern Analysis

   • Analyze load vs response time graphs for degradation points.

   • Detect memory leaks via endurance tests.

   • Spot throughput saturation points.

5. Root Cause Hypothesis

   • Document potential causes for performance issues.

   • Use logs, APM traces, and database profiling to validate.

6. SLA Compliance Check

   • Compare results with agreed-upon SLAs/KPIs.

   • Highlight areas where system failed to meet requirements.

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📝 Reporting Best Practices

• Use visuals: graphs, heatmaps, dashboards.

• Include test configuration: scripts, user load, ramp-up/down.

• Document bottlenecks & recommendations.

• Keep report concise for stakeholders but detailed for engineering teams.

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🛠️ Deliverables

• Performance Test Report (PDF or dashboard).

• Graphs showing response time, throughput, and errors.

• List of bottlenecks with probable causes.

• Recommendations for optimization and retest plan.