Performance Design Test Report

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Project Name: E-Commerce Platform Performance Evaluation
Test Report Date: October 7, 2050
Prepared By: [Your Name]

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1. Introduction

This report outlines the performance testing conducted on the E-Commerce Platform to evaluate its response time, throughput, resource utilization, and overall scalability. The primary objective of the test was to ensure the application performs optimally under expected and peak load conditions.

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2. Objectives

• To measure response times of critical transactions under various load conditions.

• To assess the system's ability to handle the expected user load.

• To identify any performance bottlenecks or limitations.

• To verify that the application meets the defined performance requirements.

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3. Test Environment

Component	Details
Application	E-Commerce Platform
Test Environment	QA Environment
Servers	4 Application Servers, 2 DB Servers
Network	LAN (1 Gbps)
Database	MySQL
Tools Used	JMeter, Grafana, New Relic

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4. Test Scenarios

Scenario	Description	Load
Scenario 1: Baseline Test	Measure response time under minimal load (10 concurrent users).	10 users
Scenario 2: Load Test	Evaluate performance with expected user load (500 concurrent users).	500 users
Scenario 3: Stress Test	Test the application at maximum load to determine breaking points (1000+ concurrent users).	1000+ users
Scenario 4: Spike Test	Assess application performance during a sudden increase in load (from 100 to 1000 users in seconds).	100 to 1000 users

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5. Test Results

5.1 Scenario 1: Baseline Test

• Average Response Time: 150 ms

• Throughput: 30 requests/second

• Error Rate: 0%

• Observations: The system performed optimally with minimal load.

5.2 Scenario 2: Load Test

• Average Response Time: 500 ms

• Throughput: 300 requests/second

• Error Rate: 1.5%

• Observations: The system handled the expected user load within acceptable response time limits.

5.3 Scenario 3: Stress Test

• Average Response Time: 1200 ms

• Throughput: 800 requests/second

• Error Rate: 5%

• Observations: The application began to show signs of performance degradation, with higher response times and error rates above 800 users.

5.4 Scenario 4: Spike Test

• Average Response Time: 1000 ms during a spike

• Throughput: 700 requests/second

• Error Rate: 4%

• Observations: The system was able to recover after the sudden load spike but with reduced throughput and increased response time.

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6. Performance Bottlenecks Identified

• Database Latency: High response times were observed in complex database queries under stress conditions.

• CPU Utilization: Application servers reached 95% CPU utilization during stress tests, indicating a need for scaling or optimization.

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7. Recommendations

• Optimize database queries to reduce latency during high load.

• Consider horizontal scaling of application servers to improve CPU utilization during peak traffic.

• Implement caching strategies to improve throughput.

• Re-test after optimization to ensure performance improvements.

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8. Conclusion

The performance tests on the E-Commerce Platform revealed that the system performs well under the expected user load. However, performance issues were identified during stress and spike tests, particularly in database latency and CPU utilization. With optimization, the system can handle peak traffic more efficiently.

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