Volume Testing

Volume testing

What is Volume Testing?

Volume testing is a type of performance testing that helps in checking the performance of an application when subjected to a large volume of data.

This data can be of two types-

  • First is the system database. If the system deals with large data frequently, volume testing becomes a necessary testing process. In this type of testing, the database size is increased to the size as per the requirement and multiple queries can be fired simultaneously.

  • The second is an interface file. If the system is interacting with a file i.e. the system might read from the file and/or the system might write onto the file. In such cases, the interface file can be created as per the requirement. After that, the system’s performance will be checked once the file interacts with the system.

The main goals of volume testing are as follows once the system is loaded with a high volume of data-

  • Verify that the system has not suffered any data loss.
  • Check the response time of the system.
  • Check data integrity.
  • Verify if the system crashes unexpectedly.

It is also known as flood testing since, in this testing type, a huge amount of data is flooded into the system to check the system’s behavior.

Importance of Volume testing with Example

For example, for any e-commerce website. Let’s assume that a couple of new brands are introduced on the platform that is very famous in the market and has a large number of products. Now, the system should be able to support this new data set without any failure.

Volume testing is also done to check the volume of data that is projected for future usage. Let’s say any new banking application generates x GB of data and in the next 2 years it is predicted that the generated data volume will exceed x*10 GB of data, and in 5 years it will generate x*50 GB of data.

Now, after the development of the code, it is advisable to check whether the system can support future predictions in terms of data volume abilities. For this check, volume testing is required.

It also helps in identifying any infrastructure need or database change that might require beforehand. This is because it is better to keep the system ready for future data volume rather than make changes later when the need arises.

It makes sure even with the excess database load, the system is working as expected and does not crash.

How is it different from Load testing and Stress testing?

Volume testing is done to make sure the system behaves expectedly when it is exposed to a large volume of data.

Load testing is done to check the system performance by gradually increasing the load until it reaches its threshold limit.

Stress testing is done to check the system’s robustness by feeding it the maximum number of users and data which surpasses the threshold limit. 

These three can be explained through examples given below-

  • Volume Testing – Increase the number of products on an e-commerce website.
  • Load Testing – Increase the number of users who use the system simultaneously.
  • Stress Testing – Increase the number of users who use the system simultaneously. Also, increase the input dataflow to the point that the system breaks.

How to do Volume testing?

In volume testing, there are some important factors on which the testing team should be clear-

  • The amount of data that the system is likely to interact with within the near future (next couple of years) and after that as well. This will be done with the help of business users, business analyst, and the marketing team.
  • Detailed knowledge of the database that is used in the system.
  • Clarity on the behavior of the system when large data is fed into the system.
  • A proper test plan to prepare test data that should mirror the somewhat exact real-time data.
  • A test plan to prepare the test environment including hardware configurations. 
  • A decision on which test automation tool(s) will be used.

Advantages of Volume testing

This section discusses some important advantages of volume testing-

  • Volume testing results in customer satisfaction. When the system is exposed to a large volume of data, it might cause a temporary system failure.

    Or, it might reduce system speed. Due to such issues, customers will have a negative experience. If these issues are found early in the testing, customer satisfaction can be increased.

  • It also helps in reducing the maintenance of the system. This is done by identifying failures arising due to data volume before the system is available to end users.

  • It helps to identify instances or areas of the system that will reduce system response time when the system is exposed to high data volume.

  • Volume testing gives assurance to the client and the development team that the system can work effectively in the real world with a high volume of data.

  • It makes sure the data is stored in the correct tables. In addition, it ensures that no data has been lost if multiple tables are updated with large data.

  • Using volume testing, the system can be checked and prepared for future predictions regarding the data volume.

  • It makes it possible to test the capacity of the system with respect to data volume.

  • It helps in reducing the overall risk of failures when it comes to the performance of the system. 

Challenges in Volume testing

The following are some of the challenges in volume testing-

  • It is a cost and time-consuming non-functional testing type as it requires the use of automation tools and skilled resources.

  • The testing team used for volume testing should be familiar with database concepts which might increase the project cost in some cases.

  • Sometimes for a small-scaled system, it is less likely that the system will engage in a large volume of data. In such cases, volume testing becomes an unnecessary step.

  • Sometimes it isn’t easy to prepare test cases for testing with specific data volumes. This is because it might not be possible to predict the volume of data that will interact with the system in the future.

  • Stimulating an exact type of real-world data for volume testing may not be possible.

Best Practices for Volume testing

  • Define clear objectives – Before starting with a volume test, we first need to clearly define the objectives, key performance metrics as well as success criteria of the test.
  • Perform the test in a controlled environment – We need to ensure that the test is performed in a controlled environment that closely resembles the production environment. This includes hardware, software, network configurations, etc.
  • Start with small loads and ramp up gradually – Just like in the case of a normal load test, we should start with a small volume of data and then gradually increase the data volume.
  • Use realistic test data – We should use realistic test data that simulate the actual production volume. This helps to ensure that the test results reflect the actual performance of the system under real-world conditions.

By following these best practices, we can ensure that the volume testing is effective, reliable, and delivers actionable insights that help to optimize the performance and scalability of the web application, database, or server.

Volume Testing Tools

Following is a list of some automation tools used by testers worldwide:

  • HammerDB – HammerDB is a load testing software supporting varieties of databases such as Oracle Database, SQL Server, IBM Db2, MySQL, MariaDB, PostgreSQL, and Redis.

    This software is free and open-source software. It is hosted by TPC on GitHub. It supports Linux and Windows operating systems. 

  • JdbcSlim – JdbcSlim is also an open-source free tool, the framework to integrate database queries and commands into Slim FitNesse testing. It is available on GitHub for download. This framework keeps test data, configuration data, and SQL code separate. This helps business users to understand the requirements which are written independently of the implementation. It supports databases with a JDBC driver.

  • DbFit – DBFit is an open-source tool for automated database testing. It was created by Gojko Adzic and is based on the FitNesse framework. It supports Oracle Database, SQL Server, MySQL, IBM Db2, Derby, and PostgreSQL.

  • JMeter – Volume testing with JMeter involves simulating a high volume of user traffic to test the performance and scalability of web applications, databases, and servers.

Conclusion

For any system, the quantity of data is an important parameter. Volume testing is a non-functional testing type. It is used to test the volume of data with which the system interacts or is likely to interact. It is a time-consuming testing process. But at the same time, it helps in identifying issues such as slow responsiveness and data loss.

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