testsigma
Topics
left-mobile-bg

What is Volume Testing | How to Perform & Best Practices

December 8, 2023Kiruthika Devaraj
right-mobile-bg
What is Volume Testing How to Perform & Best Practices
imageimage

Start automating your tests 5X Faster in Simple English with Testsigma

Try for free

“Volume testing is like a fire drill. It’s better to be prepared than to learn the hard way.”

As we navigate the ever-evolving business world, it’s impossible to ignore the growing importance of digital applications. We want to ensure these applications can easily handle the expected user traffic. 

Luckily, volume testing is here to help! We can ensure that our digital applications are in tip-top shape by identifying potential performance issues and scalability problems before they become major obstacles. 

It also provides a clear picture of the application’s ability to handle large datasets, identify memory leaks, and pinpoint any other issues affecting performance. Join us in exploring more about volume testing in the software development process and how it can pave the way for the continued success of our digital applications.

What is Volume Testing?

Volume testing, a non-functional testing, is essential software testing that evaluates the system’s ability to handle extensive data or transactions efficiently and reliably. This type of testing is a part of performance testing.

It ensures the application can operate under expected and peak load conditions without impacting performance or causing outages. During this testing, testers generate large amounts of data to simulate real-world usage scenarios and observe the system’s response. 

This helps to identify potential bottlenecks and performance issues, such as slow response times, data loss, and memory leaks.

🧞Do you know Volume Testing is also called Flood Testing?

Best practices for volume testing include:

  • Accurately replicate production environments: This testing should be conducted in an environment as similar to production as possible. This includes using the same hardware, software, and network configuration.
  • Use automated tools to generate high volumes of data: Automated tools can create a large volume of data quickly and easily. This helps to reduce the time and effort required to conduct volume testing.
  • Check system resources: System resources, such as CPU usage, memory usage, and disk I/O, should be monitored during volume testing to identify potential bottlenecks.
  • Analyze performance metrics: Performance metrics, such as response time, throughput, and error rate, should be analyzed to assess the system’s performance under load.
  • Optimize the application for scalability and reliability: The application should be optimized for scalability and reliability based on the findings of volume testing. This may involve scaling up the infrastructure, optimizing the database, or caching frequently accessed data.

By following these best practices, businesses can ensure that their applications are ready to handle the expected volume of data and transactions without impacting performance or causing outages.

volume testing

When is Volume Testing Needed?

Volume testing is essential for ensuring the scalability and reliability of software systems, applications, and platforms that need to handle a significant load of data, transactions, or concurrent users. 

It is essential in scenarios where the expected volume is substantial, such as:

  • Social media platforms during viral events
  • E-commerce websites during peak shopping seasons
  • Financial systems during high transaction periods
  • Healthcare information systems with a large patient database

This testing is beneficial in identifying performance bottlenecks and scalability issues before they affect users. Testers can simulate real-world usage scenarios and observe system performance under load, which helps identify areas that need improvement. 

This information can be used to optimize the system and ensure it can handle the expected load without experiencing slowdowns or outages.

Why Volume Testing?

Volume Testing is essential to determine the point at which a system’s stability begins to deteriorate under load. This testing can also help verify the system’s response time and ensure that data is overwritten with proper notification. 

Also, this testing can be used to verify that data is stored correctly, which is crucial for ensuring the reliability and accuracy of the system. 

By conducting this testing, testers can identify potential performance bottlenecks and scalability issues before they impact users, allowing for optimization and improved system performance.

Importance of Volume testing with Example

Volume testing is an essential testing process that aims to achieve several objectives. 

  • One of the primary goals is to identify any potential issues that may arise when dealing with a large amount of data. 
  • This testing process also helps assess the system’s performance by increasing the volume of data in the database. Doing so enables the system to handle vast data and maintain its stability. 
  • Moreover, this testing allows you to determine the point at which the system’s stability starts to decrease, which is crucial to ensuring the system’s reliability. 
  • Finally, this testing process is essential to evaluate the system or application’s capacity, which helps identify any limitations or bottlenecks.

We have seen a lot of real-time examples before. 

Here is a similar example: 

Testing a social media platform during a major event like the FIFA World Cup. 

The platform must handle a surge in traffic and user activity without experiencing performance degradation or outages. Volume testing can be used to simulate this peak load and identify any areas where the platform needs to be improved.

Characteristics of Volume Testing

Let me share some major characteristics:

  • Type of non-functional testing. This means it is focused on testing the system’s performance under high volume rather than its functionality.
  • Typically performed after unit testing and integration testing. This is because ensuring the system works correctly before testing it under high volume is essential.
  • Testing can be performed manually or by using a load testing tool. Load testing tools can simulate a high-volume load and track the system’s performance.

This testing is essential for ensuring that the system can handle expected load in production. It can also help identify bottlenecks and performance issues that must be addressed.

Features of Volume Testing

Key features of volume testing include:

  • Data handling assessment: Evaluates how the system handles and processes large amounts of data, ensuring that it remains efficient, accurate, and responsive.
  • Scalability testing: Determines the system’s ability to scale up or down to handle increased data volumes, users, or transactions without compromising performance, response time, or system stability.
  • Resource utilization monitoring: Checks and analyzes resource usage such as CPU, memory, disk space, and network bandwidth to identify potential resource bottlenecks.
  • Database performance evaluation: Assesses the system’s database performance and responsiveness when dealing with a large volume of data transactions, ensuring that data retrieval, updates, and storage operations remain optimized.
  • Boundary testing: Validates the system’s behavior at data volume thresholds, ensuring it gracefully handles reaching maximum capacity without crashing or displaying erroneous behavior.
  • Error handling and recovery testing: Verifies the system’s ability to appropriately handle errors, exceptions, and failures under high volume conditions, ensuring data integrity and system reliability.
  • Load balancing verification: Tests the system’s load balancing mechanisms to distribute the increased load effectively across servers or components, maintaining optimal performance and preventing overload on specific resources.
  • Response time assessment: Measures and analyzes the system’s response time for various operations under heavy data volume to ensure acceptable performance levels are maintained within defined benchmarks.

Volume testing helps to ensure that software systems can handle the expected load in production and deliver a smooth and reliable user experience.

Objectives of Volume Testing

The objectives are:

  • To identify the system’s performance under high volume.
  • To identify any bottlenecks or performance issues.
  • To ensure that the system can handle the expected load in production.
  • To improve the system’s performance.

Prerequisites to Testing Volume

  • The system should be stable and working correctly.
  • The test environment should be set up to simulate a high-volume load.
  • A test plan should be created.
  • The necessary resources, such as a load testing tool, should be available.

Volume Testing Examples in Real-Life

Volume testing ensures digital applications can handle the expected user load and perform reliably under peak conditions. Here are three real-life situations you meet every day:

Social media platforms: 

Imagine that Facebook is preparing to launch a new feature expected to generate user interest. 

  • Facebook engineers conduct a volume test to ensure the platform can handle the expected load.
  • They start by creating a test environment, duplicating the production environment as closely as possible. This includes using the same hardware, software, and network configuration.
  • Next, they use automated tools to generate a large volume of data that simulates real-world usage scenarios. 
  • This data includes images, videos, and posts that users might upload to Facebook during the launch of the new feature.
  • The engineers then check the platform’s performance and health throughout the volume test. 
  • They track metrics such as response time, throughput, and error rate. 
  • If the engineers identify any performance bottlenecks or scalability issues, they can take corrective action before the new feature is launched into production. 
  • This could involve scaling up the infrastructure, optimizing the database, or caching frequently accessed data.

The volume test is successful if Facebook can handle the expected load without experiencing slowdowns or outages. This gives Facebook confidence that the platform is ready to launch the new feature.

E-commerce websites:

We all shop online. Imagine an e-commerce website preparing for Black Friday sale, one of the year’s busiest shopping days. To ensure that the website can handle the expected load, the website’s engineers conduct a volume test.

  • First, engineers create a test environment, replicating the production environment as closely as possible. 
  • This includes using the same hardware, software, and network configuration.
  • Next, they use automated tools to generate a large volume of data that simulates real-world usage scenarios. 
  • This data includes product views, add-to-cart events, and checkout transactions.
  • The engineers then monitor the website’s performance and health throughout the volume test. 
  • They track metrics such as response time, throughput, and error rate. 
  • Engineers can take corrective action before Black Friday if they identify performance bottlenecks or scalability issues. 
  • This could involve scaling up the infrastructure, optimizing the database, or caching frequently accessed data.

The volume test is successful if the e-commerce website can handle the expected load without experiencing slowdowns or errors. This gives the website’s owners confidence that the website is ready for Black Friday.

Online gaming platforms: 

Imagine a video game developer launching a new online game expected to be very popular. The testers conduct a volume test to ensure the game’s servers handle the expected load.

  • Again, it is started by creating a test environment replicating the production environment as closely as possible. 
  • This includes using the same hardware, software, and network configuration.
  • Next, they use automated tools to generate a large volume of data that simulates real-world usage scenarios. 
  • This data includes player logins, character movement, and combat.
  • The testers then watch the servers’ performance and health throughout the volume test. 
  • They track metrics such as response time, throughput, and error rate. 
  • If the developers identify any performance bottlenecks or scalability issues, they can take corrective action before the game is launched to the public. 
  • This could involve scaling the infrastructure, optimizing the game code, or caching frequently accessed data.

The volume test is successful if the servers can handle the expected load without experiencing slowdowns or errors. This gives the developers confidence that the game’s servers are ready for launch.

Financial systems: 

The last but essential example is while checking financial systems. Imagine that a bank is preparing for end-of-month processing, which is a time when there is a high volume of transactions. 

To ensure that the bank’s systems can handle the expected load, the bank’s engineers conduct a volume test.

  • Engineers start by creating a test environment and replicating the production environment as closely as possible. 
  • This includes using the same hardware, software, and network configuration.
  • Next, they use automated tools to generate a large volume of data that simulates real-world usage scenarios. 
  • This data includes account deposits, withdrawals, transfers, and payments.
  • The engineers then observe the system’s performance and health throughout the volume test. 
  • They track metrics such as response time, throughput, and error rate. 
  • Engineers can take corrective action before end-of-month processing if they identify performance bottlenecks or scalability issues. 
  • This could involve scaling up the infrastructure, optimizing the database, or caching frequently accessed data.

The volume test is successful if the bank’s systems can handle the expected load without experiencing slowdowns or errors. This gives the bank confidence that its systems are ready for end-of-month processing.

Apart from these, you take healthcare systems, and there are still more real-time examples we can discuss.

Volume Testing Attributes: 

Important attributes checked during volume testing:

  • System response time: This testing measures the time it takes to respond to requests under high load. This ensures the system meets user expectations and provides a good user experience.
  • Data loss: This testing verifies that the system does not lose data under high load. This is important to protect the integrity of the system’s data and prevent any negative impact on users.
  • Data storage: This testing ensures the system can store data correctly under high load. This prevents data corruption and ensures that users can always access their data when needed.
  • Data overwriting: This testing ensures the system does not overwrite data without proper authorization. This is important to protect the integrity of the system’s data and prevent any accidental data loss.

Also, with these attributes, volume testing can assess other system performance aspects, such as scalability, resource utilization, and error handling.

Other tips:

  • Be specific about the data types and transactions that will be tested during the volume test. This will help ensure the test is complete and covers all system functionality aspects.
  • Use realistic test data to simulate real-world usage conditions. This will help identify performance bottlenecks or scalability issues that may be absent during testing with smaller amounts of data.
  • Check the system’s performance and health throughout the volume test. This will help to identify any potential problems early on.
  • Analyze the volume test results and identify any areas for improvement. This information can be used to optimize the system and ensure that it is ready for peak usage conditions.

How to do Volume Testing?

The following steps can be followed for volume testing:

  • Identify the scope of the test. What aspects of the system will be tested under high volume? This could include the number of users, the data amount, or the request frequency.
  • Create a test plan. This should include the test objectives, cases, and the expected results.
  • Set up the test environment. This may involve creating dummy data or simulating a high-volume load.
  • Execute the test cases. This may involve using a volume testing tool or simply running the system under high volume manually.
  • Monitor the system’s performance. This may involve tracking response times, error rates, and resource usage.
  • Analyze the test results. Identify any areas where the system is struggling to handle the high volume.

Make recommendations to improve the system’s performance. This may involve scaling the system, optimizing the code, or fixing bottlenecks.

Advantages & Disadvantages of Volume Testing

Some of the advantages of volume testing include:

  • Scalability assessment: This testing can help to see how well the software can handle more data. This is essential for ensuring that the application can meet the needs of its users and grow with the business.
  • Identification of bottlenecks: This testing can help to find areas of the software that are slow or have other problems. This information can improve the software’s performance under real-world conditions.
  • Reliability and stability testing: This testing ensures that the software remains reliable and stable even when dealing with a high volume of data. This is necessary for preventing crashes and other service disruptions that could impact the user experience and business operations.
  • Optimization and tuning: Conducting volume testing helps to optimize the system’s performance by identifying areas needing improvement. It provides insights into the system’s resource use, allowing adjustments and fine-tuning to enhance performance.
  • Early detection of issues: This testing detects issues related to database performance, disk space, memory, and processing speed. Identifying these issues early in the development lifecycle enables timely corrective actions and reduces the cost of fixing problems later.

Example:

A company is developing a new e-commerce platform. They use volume testing to simulate a large number of users accessing the platform at the same time. This helps them to identify and fix performance problems before the platform is launched to the public.

Some of the disadvantages of volume testing include:

  • Resource intensive: It can be expensive and time-consuming because it requires a lot of computing power, storage space, and memory.
  • Complexity and setup: It can be challenging to set up and test a system with a lot of data. This requires careful planning, data generation, and management.
  • Data privacy concerns: Handling a large volume of data during testing raises concerns about privacy and security. Companies must ensure that sensitive or confidential data is handled and protected during volume testing.
  • Limited realism: Generating massive data for testing may not always represent real-world scenarios. Simulating diverse and complex data patterns the system might encounter in actual usage might be challenging.
  • Difficulty in analysis: Analyzing the results of volume testing can be complex due to the vast amount of data generated. Extracting meaningful insights and pinpointing specific performance issues can be challenging, requiring sophisticated analysis tools and expertise.

Example:

Small companies with limited resources may find performing volume testing on their software application challenging. This is because volume testing requires a lot of computing power, storage space, and memory.

Challenges in Volume testing

Volume testing deals with large amounts of data, creating challenges for testers. Here are a few things to keep in mind when executing this testing:

  • Data size: Testing requires extensive datasets, which can be expensive and time-consuming to generate and manage.
  • Database structure: Relational databases used in testing have a complex structure and many related tables. Testers must understand the database structure and connections to generate realistic test data.
  • Data types and validation: Testing involves working with many data types, including valid, invalid, absent, boundary, and erroneous data. Testers need to understand the different data types and how to confirm them.
Challenges in volume testing

More challenges you may face during this testing:

  • Inhabiting a database: Populating a database with a large volume of data can be challenging, especially if the database is relational and has a complex structure.
  • Reviewing data types and connections: Testers need to understand the different data types and how they are connected in the database to understand the database structure and connections.
  • Handling various data: Testing involves working with a wide range of data, including valid, invalid, absent, boundary, and erroneous data. Testers must be able to test the system with all these data types.

Be an early bird, use these tips, and overcome the volume testing challenges:

  • Use data generation tools: Many tools can help you create large, realistic datasets for testing.
  • Use a test environment like production: You must test your system in an environment like production hardware, software, and data. This will help you to identify and fix performance problems before they occur in production.
  • Use a performance monitoring tool: A performance monitoring tool can help you track the performance of your system under load. This information can be used to identify and fix performance bottlenecks.
  • Plan and execute volume testing early: This will help you identify and fix performance problems when they are less expensive and time-consuming.

Volume Testing Checklist

Some checkpoints to look at:

  • Test Environment Setup: Ensure that the test environment is configured to handle the expected volume of data. This includes allocating enough storage, memory, and processing resources.
  • Data Generation: Create or get a realistic dataset that represents the expected production data. Ensure that the data is diverse and covers a wide range of scenarios.
  • Data Injection: Develop scripts or tools to inject the test data into the application or database under test. Verify that data injection is accurate and complete.
  • Test Scenarios: Define various test scenarios involving different data volume levels, including edge cases where data exceeds normal limits.
  • Performance Monitoring: Install robust monitoring tools and metrics to track system performance during volume testing. Check response times, CPU and memory use, and database performance.
  • Data Validation: Design validation checks to ensure the application handles the data. This includes verifying data integrity, accuracy, and consistency.
  • Scalability Testing: Test how the application scales with increasing data volume. Test its ability to handle sudden spikes in data load and assess whether it can scale.
  • Stress Testing: Also,  perform stress testing to push the system beyond its intended limits to identify potential failure points and bottlenecks.

Best Practices for Volume Testing

Volume Testing Best Practices are:

Specify clear objectives

Before starting a volume test, define the goals, key performance metrics, and success criteria.

Testing in a controlled environment

Ensure the test is performed in a controlled environment that resembles the production environment. This includes hardware, software, and network configurations.

Start with small loads and boost

With a normal load test, start with a small volume of data and then increase it.

Use practical test data

Use test data that simulates the actual production volume. This will help ensure that the test results reflect the system’s performance under real-world conditions.

Conclusion

It is an essential part of the software development lifecycle but can be complex and challenging.

Before performing volume testing, testers must understand the system under test, database languages, and volume testing tools well. They also need to develop a comprehensive test plan.

Testers can start executing the test cases once the plan is in place. Volume testing can be time-consuming, but it is essential for ensuring that the system can handle a large volume of data without performance problems.

Frequently Asked Questions

What is the difference between Volume Testing and Load Testing?

Volume testing focuses on how much data a system can handle, while load testing focuses on how many users a system can handle at the same time. 

What is the difference between Stress testing and Volume testing?

Stress testing checks how the system performs under extreme conditions, while volume testing checks how the system performs with a lot of data. 

To learn more about Stress Testing, click here.

Is Volume testing Functional testing?

No, Volume testing is non-functional testing. Read more on Non-function testing here.

Is volume testing the same as Performance testing?

Volume testing is performance testing that checks how the system performs with a lot of data. Read more about Performance Testing here.

imageimage
Subscribe to get all our latest blogs,
updates delivered directly to your inbox.

RELATED BLOGS


How to Write Test Scenarios For Swiggy?

AAYUSH SAXENA
13 MIN READ
TESTING DISCUSSIONS

API Examples: A Complete List of 10 Use Cases

TESTSIGMA ENGINEERING TEAM
12 MIN READ
TESTING DISCUSSIONS

SDET vs QA – What are the top 10 key differences?

KIRUTHIKA DEVARAJ
7 MIN READ
TESTING DISCUSSIONS