Performance testing: An integral part of modern projects

Performance testing is now an essential component of any large-scale project where high system throughput or handling of large data volumes (big data) is required. The goal is to evaluate how the system behaves under different levels of load and to identify its limits. Learn more in our blog: Automated test suite as a service: Ensuring stability for business-critical systems.

Key phases of performance testing

1. Defining system requirements

In this phase, it is crucial to clearly define the parameters that will be evaluated during testing. Key factors include:

• Response time of a portal or REST API
• Maximum number of concurrently connected users
• Maximum volume of processed data (number of records, file sizes, number of files, etc.)

The objective of this phase is to determine the system’s maximum load capacity (worst-case scenario) and establish acceptable response time thresholds under such conditions.

2. Preparing test scenarios

Based on the defined requirements, test scenarios are created to simulate different levels of load, such as:

• Low load – normal system operation
• Medium load – increased number of requests
• High load – maximum expected operation

Each scenario should include a load distribution strategy, such as gradually increasing the number of requests (ramp-up) until the maximum load is reached and maintained for a certain period.

Another important part of this phase is defining the system’s initial state—such as preloading the database or specific configuration settings.

3. Test execution

Tests should be performed in a well-prepared environment and in accordance with the test scenario. To avoid skewed results caused by external factors, it is recommended to repeat the tests multiple times.

The output of each test scenario should be a test report containing:

• Minimum, maximum, and average system response time
• Number of successful and failed requests
• Other relevant metrics depending on the tested application

4. Performance testing tools

There is a wide range of tools available for simulating user or system load. Some of the most well-known include:

• K6 – a modern performance testing tool with JavaScript support
• Apache JMeter – a robust open-source tool suitable for API and web application testing
• Locust – a Python-based framework allowing easy test scripting

The choice of the right tool depends on the specific use case, project requirements, and preferred technology stack.

Conclusion

Performance testing plays a crucial role in ensuring software stability and reliability. Properly conducted testing helps uncover system bottlenecks before deployment, preventing potential outages and issues under high load conditions.

If your project involves high throughput or large data volumes, you should definitely pay close attention to performance testing. At CodeArt, we are happy to assist you with that.