What Is Performance Testing: Definition, Types and Metrics

Sona Hakobyan

Performance testing is the backbone of delivering seamless software experiences. In a world where slow applications drive away 53% of users, ensuring your system can handle real-world demands is non-negotiable. 

This guide dives into the fundamentals of performance testing, explores its critical types and metrics, and reveals how it uncovers bottlenecks before they impact users. 

Whether you’re a developer, QA specialist, or business leader, you’ll learn actionable strategies to validate scalability, optimize resources, and build customer trust. 

Let’s begin.

What Is Performance Testing?

Performance testing is a method for evaluating how a software system performs under certain workloads, network conditions, and usage patterns. The main objective is to identify bottlenecks and confirm that the application meets predetermined performance testing objectives, such as responsiveness and stability.

When asking “what is a performance test?” or “why performance testing is important,” consider that these examinations measure crucial factors like response times, throughput, and resource usage. They help you decide whether your application can handle real-world demands, such as large numbers of simultaneous users or frequent data requests, without slowing down or crashing.

In a broader sense, performance testing means understanding how your software behaves under stress. By pinpointing areas that cause slowdowns or resource drains, organizations can ensure that end users get consistent service—even when the workload spikes. This proactive approach reduces the risk of system failures after deployment and improves overall customer satisfaction.

Purpose:

• Ensure applications meet speed and stability requirements.
• Validate scalability for future user growth.
• Prevent crashes during peak traffic (e.g., holiday sales).
• Optimize infrastructure costs by right-sizing resources.

For example, an e-commerce site uses performance testing to confirm it can handle 10,000 simultaneous users during a Black Friday sale without lagging.

Types of Performance Testing

Performance testing generally encompasses several approaches, each designed to uncover specific insights about system behavior. While load testing forms a broad category, its subtypes, stress testing, soak testing, spike testing, data volume testing, and resource testing, all focus on unique aspects of how a system handles varying workloads. 

Below are the major types of performance tests, broken down into individual categories to explain how they work and what they aim to accomplish.

Load Testing

Load testing checks the system’s performance under expected, regular user load. It involves simulating a typical number of simultaneous requests or users and observing metrics such as throughput, response times, and resource usage. 

By performing load testing, development teams can confirm that the software meets performance testing requirements and determine if any problems emerge under everyday usage.

Key points:

• Assesses the system under normal or slightly above-normal conditions.
• Helps pinpoint if the system can manage usual levels of workload without degradation.
• Often serves as a baseline for other, more specific tests.

For instance, testing a banking app with 5,000 concurrent users to ensure transaction speeds remain under 2 seconds.

In its turn, load testing consists of several types of testing. Let’s discover the main types of load testing now:

Stress Testing

Stress testing pushes the system beyond its normal operational capacity. The goal is to see how the application behaves when user load or data requests reach peak levels, sometimes exceeding planned usage. 

By identifying the breakpoints, teams gain knowledge about system stability and can plan for graceful failure or resource allocation during extreme events.

Key points:

• Determines the system’s breaking point.
• Useful in planning how the software handles unexpected spikes.
• Reveals potential vulnerabilities, such as memory leaks or unhandled exceptions.

A streaming platform might test how many users it can handle before video buffering increases by 300%.

Soak Testing

Soak testing, sometimes called endurance testing, involves running the system at a typical or higher-than-usual load for a prolonged period. This approach can help identify issues like gradual memory leaks, resource exhaustion, or other problems that appear over time.

Key points:

• Examines long-term reliability rather than short bursts of activity.
• Helps detect stability problems that develop slowly.
• Aids in ensuring the software remains robust during extended usage.

For instance, a streaming service runs a soak test by simulating thousands of viewers over an entire weekend. During this extended test, the team tracks memory usage, CPU load, and error rates. This approach can reveal slow-building issues (like memory leaks) that wouldn’t appear in shorter tests.

Spike Testing

Spike testing focuses on the system’s reaction to sudden, dramatic spikes in user activity or data volume. For instance, you might simulate a scenario where a marketing campaign or unexpected event floods the application with new visitors.

Key points:

• Evaluates how the application copes with sudden bursts in workload.
• Shows whether the system can recover after traffic surges back down.
• Helps refine scalability strategies and system elasticity.

Imagine a news website’s response to a 500% traffic spike during a major event.

Scalability Testing

Scalability testing checks whether the system can scale vertically (by adding more power to existing servers) or horizontally (by adding more servers) without performance drops. This method is critical for applications that anticipate growth or seasonal surges.

Key points:

• Verifies the system’s ability to expand under increased workload.
• Helps plan infrastructure for future demand.
• Ensures consistent user experience as the application scales.

A cloud service provider might test how adding servers affects response times during load spikes.

Capacity Testing

Capacity testing determines the maximum amount of work a system can handle while still meeting its defined performance benchmarks. Unlike stress testing—which seeks a breaking point—capacity testing aims to define an optimal throughput threshold.

Key points:

• Establishes the upper operational limit under acceptable performance criteria.
• Informs resource planning and budgeting.
• Reduces risk of under-provisioning or over-provisioning system resources.

A social media app could use this to plan server requirements for viral content scenarios.

Data Volume Testing

Data volume testing zeroes in on how the system manages large sets of information. When databases grow in size—often due to heavy usage over time—queries can slow down, and resource usage can spike. By conducting data volume testing, teams can gauge whether the application remains responsive and stable even when databases expand significantly.

Key points:

• Measures software’s efficiency under vast data conditions.
• Detects issues with database queries, indexes, or storage.
• Reveals the capacity of the system to support large data-driven workloads.

For example, a hospital management platform imports massive patient records into its database. Testers then measure how swiftly the system processes queries. If response times spike under heavy data, indexing or storage optimization might be necessary.

Resource Testing

Resource testing inspects how well the software uses specific resources like CPU, memory, and disk I/O under varying workloads. It zooms in on whether these assets can handle peak usage without causing bottlenecks or crashes.

Key points:

• Tracks usage across different resources (CPU, memory, disk).
• Identifies inefficiencies, such as memory leaks or CPU spikes.
• Informs decisions about resource provisioning and optimization.

For instance, an e-commerce site simulates heavy traffic while tracking CPU, memory, and disk usage. If memory spikes too high or the CPU becomes overloaded, developers know to optimize resources before the real holiday rush.

Performance Testing Metrics

When organizations conduct performance tests, they track several metrics that highlight system health and responsiveness.

Why Use Performance Testing?

Organizations from startups to global enterprises rely on performance testing to confirm their software delivers consistent service—even when usage spikes or systems come under stress. Here are some notable advantages:

Performance Testing Challenges

Although performance testing is vital, teams often encounter obstacles that make the process more complex than anticipated. Some of the most common include:

How to Conduct Performance Testing

If you are wondering “how to do performance testing” or “why do we need performance testing,” the steps below should offer a clear roadmap for your performance testing process. Follow them in order, but remain adaptable as project requirements may shift.

By following this sequence, you establish a disciplined performance testing process that clarifies the system’s limits, stability, and growth potential.

Top Performance Testing Tools

How PFLB Can Help with Performance Testing

PFLB is a leading provider of performance testing services, delivering solutions that ensure reliability, scalability, and strong user experiences. Our team has spent years refining methods and tools for performance tests, making us adept at solving challenging demands in various industries.

✅ Cloud-Native Testing at Scale

PFLB leverages cloud infrastructure to simulate 1M+ virtual users globally. Test from AWS, Azure, or Google Cloud regions to mirror real-world traffic patterns—without upfront hardware costs.

✅ Real-Time Monitoring 

Our platform offers live dashboards tracking 50+ metrics (response times, error rates, CPU spikes). AI pinpoints bottlenecks (e.g., slow SQL queries) in minutes, not days.

✅ Compliance-Ready Reporting

Generate audit-ready reports for industries like healthcare (HIPAA) or finance (PCI DSS). Prove compliance with granular performance logs.

✅ Expert-Led Strategy

Our certified engineers design tests tailored to your goals—whether it’s Black Friday readiness or IoT scalability. No more “copy-paste” test scripts.

Our Case Study

NOV enhances real-time drilling data with PFLB load testing

NOV, a global leader in oil and gas solutions, faced performance issues with its CTES Max Completions brand under heavy user loads. To resolve this, NOV partnered with PFLB for customized load testing.

Challenge identified

Bottleneck in SQL Server interactions causing delays.

Solution:

PFLB engineers collaborated closely with NOV to design a tailored load testing strategy. Using PFLB’s in-house platform, they conducted rigorous load and stress tests. These tests uncovered a critical bottleneck in the SQL Server database’s interaction with the application server, triggered by multiple Async Network IO wait events under heavy load. This analysis enabled NOV to pinpoint and address the issue effectively, ensuring the tool’s scalability for real-time data delivery.

Knowledge transfer

NOV gained the ability to perform future tests independently.

Read full case

How Load Testing Helped Texans Survive Power Outages During a Storm

Pedernales Electric Cooperative (PEC), the largest electric distribution cooperative in Texas, faced a critical need to ensure the reliability of its Storm Center and Outage Reporting & Status (OR&S) systems.

Challenge Identified

PEC needed to test both systems under a load of 10,000 virtual users within a week. Complex dependencies on external contractors like KUBRA, who provided the infrastructure, added to the challenge.

Solution:

PFLB collaborated with PEC and KUBRA to conduct real-time load testing. They developed user scenarios to simulate outages, configured load scenarios, and managed IP whitelisting to avoid throttling. Testing uncovered performance issues, including spikes in response time under peak loads, providing PEC with actionable insights to enhance system reliability.

Result:

PEC received a comprehensive performance report and vital insights, enabling them to deploy optimized systems. PEC is now equipped to independently manage future performance testing, ensuring preparedness for heavy user loads during storms.

Read full case

Check out all our portfolio and success stories to see how we’ve delivered tangible results for clients across multiple sectors. We address resource shortfalls, tune software configurations, and help refine your performance testing process so that everything runs smoothly.

Conclusion

Performance testing is more than a technical procedure; it’s a strategic investment in your software’s future. By evaluating how your application handles typical and extreme workloads, you avoid launching unprepared solutions into production. Tests that measure response times, resource usage, and system behavior under peak conditions can reveal hidden problems and ensure user satisfaction.

Whether you are exploring types of performance testing for the first time or optimizing a well-known system, understanding why we need performance testing can help you create a robust plan that supports both current operations and future growth. 

When you’re ready to elevate your performance testing to the next level, consider partnering with PFLB. Our specialized services can help you craft a sustainable, resilient application that meets the evolving demands of your business.