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https://github.com/kvishalrj/qeats_performance_testing

A food delivery application
https://github.com/kvishalrj/qeats_performance_testing

jmeter postman signoz

Last synced: 29 days ago
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A food delivery application

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README 

        
# QEats Performance Testing



## Overview

**QEats** is a food delivery application, and the purpose of this project is to monitor the performance of the application under high load and ensure it meets expected benchmark metrics.



### Project Highlights:

- Wrote and executed **JMeter** tests to validate the **happy flow** of the application under various load conditions.

- Tested the application under different **load scenarios** to evaluate business metrics and application performance.

- Used **SigNoz** for monitoring the host machine's metrics where the test-bed was set up, ensuring comprehensive visibility of the system’s health during tests.

- Focused on performance validation for critical application functionalities, ensuring they could handle expected user traffic without degradation in performance.

- Provided insights into system behavior under load, identifying areas for performance optimization.



## Tools and Technologies Used:

- **JMeter**

- **SigNoz**

- **Postman**



## Project Structure:

The project is organized into the following modules:



1. **JMeter Test Scripts**:

   - Contains the test scripts that simulate various user activities and actions on the QEats application to test its performance under load.

   - Includes tests for user login, placing orders, browsing menu items, and checking order statuses.



2. **Performance Metrics**:

   - In-depth performance metrics collected from **SigNoz** to track resource utilization and system health during the tests.

   - Host machine metrics (CPU, memory, network) monitored throughout the test runs to provide a full picture of performance.



3. **Test Execution Reports**:

   - Contains the results of each test, providing detailed logs, performance graphs, and insights into how the application performed under various conditions.



4. **Postman Collections**:

   - A collection of **Postman** API tests used for validating backend API performance and response times, providing a comprehensive view of the application's behavior under load.



## Features Implemented:

- **Load Testing**:

  - Simulated different load scenarios with varying numbers of concurrent users to measure response times, throughput, and system stability.

- **Performance Monitoring**:

  - Integrated with **SigNoz** to monitor system health and resource usage during the tests.

- **Business Metrics Testing**:

  - Validated critical business metrics like order placement time, browsing response time, and transaction processing under load.

- **Test Results Reporting**:

  - Detailed test execution reports, including **response times**, **throughput**, and **error rates** under various load conditions.

- **Scalability Validation**:

  - Ensured the system could scale under increasing traffic loads and meet expected service levels.



## How to Run:

1. Clone the repository:

   ```bash

   git clone https://github.com/kvishalrj/QEats_Performance_Testing.git

   ```

2. Ensure **JMeter** and **SigNoz** are installed and configured.

3. Import the JMeter test plan into **JMeter** for executing the load tests.

4. Run the tests and observe performance metrics in **SigNoz**.



### Running Tests:

#### Using JMeter:

- Open the JMeter test plan (`.jmx` file) in **JMeter**.

- Configure the number of threads (virtual users) to simulate various load scenarios.

- Run the tests and analyze the results in the **Summary Report** and **Graphs**.



#### Monitoring Performance with SigNoz:

- Access the **SigNoz** dashboard to monitor host machine metrics in real time while tests are running.

- Review the metrics to identify potential bottlenecks and areas of improvement.



## Reporting:

After the test run, detailed reports are generated:

- **Performance Graphs**: Found in the `reports/` directory, showing metrics like response times, throughput, and errors.

- **Test Logs**: Detailed logs for each test, including timestamps and actions performed.

- **System Metrics**: Collected data on CPU, memory, and network usage during test execution, available through **SigNoz**.



## Future Scope:

- Enhance test coverage to include stress and spike testing scenarios.

- Integrate performance tests with CI/CD pipelines to continuously validate performance with every code change.

- Optimize performance based on identified bottlenecks and resource consumption patterns.