Modern-day software applications aim to cover a wide range of users’ needs in a flexible and scalable way. Between fierce business competition and high customer expectations, most businesses simply can’t afford to have a low-quality app in the market. To ensure that users get the best version of your product, thorough testing of both functional and non-functional aspects of a software application are an essential step in the development process.

The software testing landscape has evolved drastically over the years, yielding many different types of tests such as unit testing, integration testing, and performance testing. A well-oiled software development process incorporates multiple types of tests so that engineering teams can detect and address issues quickly — ideally during the development phase, before they reach customers and impact business goals.

What is volume testing?

Volume testing — also known as flood testing — examines the stability and response time of a system by transferring huge volumes of data, and evaluates a variety of different system components like databases, software, etc.

This type of software testing is a critical part of avoiding issues under load, such as slowdowns or crashes.

Difference between volume testing, load testing, and stress testing

There are several different subtypes of tests under the performance testing umbrella, including:

• Load testing
• Stress testing
• Soak testing or endurance testing
• Spike testing
• Volume testing

Some of these concepts are often used interchangeably, but they are quite different in their objectives and use cases.

Comparison table

Benefits of volume testing

Data quantity plays a vital role in any system. Volume testing checks risks like data loss and slow response times that might lead to system failures or create a bad user experience. These risks might occur when your system deals with — or is expected to deal with — a large volume of data.

Verifying the load capacity of your application is critical before you release your product, or when you need to scale it up in real time, which is exactly what volume testing helps with. Although volume testing tools are typically time-consuming and complex to work with, the benefits tend to outweigh the challenges. Implementing concepts like traffic replay can reduce such challenges.

In essence, volume testing allows you to:

Determine your system’s capacity

With volume testing, you can estimate the amount of high volume data your system can handle before it crashes. Being aware of your system’s capacity helps you create scalability plans with accuracy, as you’re now able to make informed decisions rather than educated guesses.

Simulating large volumes of data and processing demands provides much more realistic insight into your system’s performance.

Identify weak spots in your system

Volume testing tests your system’s components, pushing them to their limits, and helps identify potential bottlenecks and vulnerabilities in your system. These vulnerabilities can range from hardware constraints, to inadequate memory management or poor database design.

Regardless, volume testing helps pinpoint weak spots during development, so you can address issues before they affect end-users.

Test your system’s response time

Volume tests help you maintain a high performance level by keeping your system’s response time within an acceptable limit, despite a possible increase in data volume.

Numerous studies have shown that users faced with a slow website or app are inclined to click away after just a few seconds, highlighting the importance of maintaining quick response times.

Prevent data loss

Volume testing is an efficient way of assessing the risk of data loss during high-volume scenarios. Data loss can have significant consequences, ranging from bad user experience and lost revenue, to regulatory issues.

By revealing areas where resiliency can be improved, or areas where existing plans need optimization – such as your data backups–volume testing can prevent the pitfalls of a data loss situation.

Develop scalability plans

Information from volume tests can help determine the most suitable scalability plan for your system. For example, is scaling up the way to go, or is scaling out a more appropriate strategy for your needs?

Being able to scale quickly and efficiently is important not just for the user experience, but also for the health, growth, and security of the business.

Identify load issues

Understanding how your system behaves under increased workloads will help mitigate system failures and response time issues before they reach production. To manage data loads more effectively, organizations can increase data storage or scale the database to avoid reaching the set limit.

Once load issues have been identified, it’s much easier to resolve them through optimizations like resource allocations or a system redesign.

LIke most other performance tests, volume testing can be implemented in a continuous manner, ensuring these benefits are leveraged throughout your software development process.

What to monitor in a testing plan?

Your volume testing checklist must be created in detail, and should represent the live environment conditions as closely as possible. To achieve this, your test cases should cover all the use scenarios and data needed to accurately simulate production conditions, including the real-life data your application will handle.

Here are some of the key metrics you should monitor when conducting volume testing:

Data loss

One of the most important aspects of volume testing is checking for data loss. When data has been damaged or lost, it may be unavailable when you request it. Volume testing can verify that your system and database won’t experience any loss when faced with an increased amount of data. Volume tests can also confirm that your data is appropriately stored in the database. Plus, they can detect cases where data is overwritten without prior notice, which helps with choosing your database size.

Response time

Volume testing will provide insights into your system’s performance. No matter how much pressure an application is under, it must maintain a high response time. Exceeding a certain threshold should trigger a reevaluation of your system design.

Processing time

Huge data volume will consume system bandwidth and impact processing time for other users–leading to a poor user experience.

Warning signs and risks

Analyzing how your system responds to large volumes of data is one of the core goals of volume testing. The point is to proactively detect signs that may indicate possible downtimes and system failures, such as lagging. Identifying these areas early will give you the opportunity to address any weak spots before they become larger issues.

Volume testing with production traffic replication / Volume testing in the real world

Accurate test data is extremely important for a good volume test. Unfortunately, creating test data can also be the most difficult part of a volume test. Production traffic replication, or traffic replay, is the easiest way to create accurate test data. Traffic replay records data from production that can be replayed (and multiplied) in any test environment. Rather than using a test data generator or scripting, traffic replay allows your real prod data to be your test data. This removes the entire step of “creating” test data, saving your testing team lots of time.

The benefits of production traffic replication for testing builds over time. As your application changes, your test data also needs to be modified. By using traffic from production, continuous testing can be implemented, ensuring your application can always survive high data loads.

Start volume testing: how to prepare

Understand your environment

Understanding your environment is the first step toward volume testing. You can start by answering questions like:

• What tools are you planning to use?
• What is the state of your test and product environment?
• Under what conditions are you going to run your tests?
• What database is your system using?

Knowing the answers to these questions will help you create the most appropriate tests for your needs.

Design test cases

The next step is to design test cases that capture your desired metrics, while also considering any constraints. During this step, you should identify different user scenarios and gather data to simulate real-life conditions, as well as define your metrics. You’ll need to ensure that your test environment is set up properly and ready to go, your tools are configured correctly, and that your resources are organized.

Analyze, adjust, repeat

Next, you can run your tests and gather results. Then you can analyze your findings and make adjustments to your application based on what you learn. Lastly, you can repeat the process to verify whether your adjustments have improved your system’s performance.