With software development being required to scale up faster with optimized quality, testing is now taking center stage. Capacity Testing exercises the system to check if the application and infrastructure can actually take on the amount of traffic that they were designed to handle without compromising user experience. This also helps with planning and design of the infrastructure to optimize quality.
Capacity testing is a type of load testing that identifies the maximum number of users or transactions a system can handle while maintaining acceptable performance levels. This helps determine the “safety zone” of your system, ensuring it operates efficiently without compromising user experience.Capacity Testing ensures that the application and environment can smoothly handle the maximum number of users or transactions according to the performance requirements defined in your Service-Level Agreement (SLA). Capacity Testing is aimed at testing the maximum capacity of your system in terms of traffic, while still being able to deliver optimal user experience.
Common examples for performance SLAs include homepage load times, webpage response times, transaction durations (e.g., account login, search, and payment times).The overall objective is to identify the ‘safety zone’ of the system and keep it there as much as possible.Capacity Testing helps determine the extent to which it can be stretched without hurting end user experience. This is crucial business data. It is well known that 40% of users will abandon a site if it takes more than 3 seconds to load.Just a one second delay can cause small to medium sized eCommerce websites to bleed over $250,000 annually. Whether it is system or application software, the modern organization needs to know its performance data, as a sales tool and also to create quality benchmarks to improve long-term planning for maximum business profit.Knowing the application limitations can motivate the organization to improve development processes and deploy a more powerful infrastructure if needed. There should be no performance drop during peak times. This matrix calculation is only possible with Capacity Testing, which helps determine the number of users that can use the system with the optimal user-experience (performance) under different user cases and scenarios.
Capacity Testing is not to be confused with Load Testing, which is more about subjecting the application and environment to varying loads to learn about their behavior.
For example, Load Testing is used to learn how a system behaves with large and varying numbers of users by checking the response time received for pages or transactions under different scenarios. This type of testing is typically performed during the QA stage of software development.
Capacity Testing is also different from Stress Testing, which involves testing beyond operational capacity and subjecting the system to extreme conditions to deliberately try to break the system while observing its behavior. It is carried out prior to deployment to locate misconfigurations and server vulnerabilities.
Many organizations report spikes or surges in annual business volumes due to regular, seasonal, and sudden demand for their products. The COVID-19 plagued 2020 is a great example of a surge in online activity. The system design should be able to withstand this sudden surge without sacrificing user experience. This can immediately improve your Capacity Planning.
As explained earlier, a fraction of a second of delay or poor performance can lead to extensive losses that add up to millions of dollars in today’s uber-competitive market, where customers are demanding optimal quality (e.g., – page load times, duration of transactions) with fast time-to-market. Numerous factors could affect the software’s performance and it’s response time. An organization planning to deploy an application needs to have a realistic grasp of the load limitations of a given infrastructure under different use cases, business processes, and conditions. It needs to make sure to test against the right SLAs and performance metrics, against the right use cases and business processes and against varying, diverse and realistic user conditions simulating the experience of real users in the production environment.
This helps detect and mitigate the factors that may impact the performance and user experience. Capacity Testing helps identify the right infrastructure for different user scenarios and business needs, ensuring that the customers get an optimal and consistent user experience regardless of the circumstances (e.g., – holiday season, product launch, the beginning of the school year). Here are some Capacity Testing best practices you should consider.
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Before even getting started with Capacity Testing, you should be creating Pareto charts, not before identifying the stakeholders that are most relevant to the testing and determining the processes that will actually be tested. The most common people involved in Capacity Testing processes are Database Administrators (DBAs), developers, SMEs, product owners, and business executives.
Furthermore, it’s highly recommended to stick to the 80/20 Rule, which can be applied to all aspects of Capacity Testing – performance, load, volume, and more. By applying the 80/20 rule to your Capacity Testing, you can focus on the more problematic and volatile processes that are likely to affect the organization’s profits and create the biggest bottlenecks.
Sometimes the automated test tool used before the deployment to the production environment may not understand the business processes associated with the application or the most generated traffic business processes.
To avoid these loopholes, the automation engineer should consult with the Product Owner, SMEs, and business analysts for the real-life use case.
You need to make sure that the SLAs you are testing against are realistic, accurate, and relevant to the most important use-cases.
Before conducting any test or capacity test, it is recommended to document the detailed test specification, which can include various parameters like the hardware specification, the version of the Software and Client type, if any (thick, thin), the number of processes running in the background, volume test, type of network, data volumes, and other relevant database details.
You should also factor in the environment type into your Capacity Testing process. Knowing and defining whether it is QA, Sandbox or Pre-Production environment will let you duplicate the production environment in the best possible manner. The more detailed information you can create while testing, the closest you will get to remediating potential issues.
It’s recommended to repeat the Capacity Testing and run it continuously with different data sets to fine-tune the app and infrastructure. Some unidentified issues get reported with a different set of data or are plagued with memory-related issues, which can happen after a few test runs. By reducing manual intervention, some intermittent problems also will get identified after a few test runs.
Automate the process for better results. With more and more organizations scaling up exponentially, there are limited available resources. Automated Capacity Testing, integrated to your CI/CD pipeline, is the best way out. Some capacity test automation tools have the limitation of providing only black-box results, making it very difficult to isolate the issue and pinpoint the root cause of a particular problem.
This is a crucial part of capacity planning. If possible, go for the advanced tool, which will help monitor the white box result as well. When your business is time-sensitive, it can’t wait for a different report from the black-box test.
Cross-department friction is to be found in all organizations today, at one level or another. This is especially common when there are bottlenecks or during unexpected downtimes. These unpleasant instances can be reduced or eliminated with proper Capacity Testing.
By creating comprehensive reports that can be shared with the key stakeholders, you can improve transparency and boost collaboration between departments.
Capacity Testing reporting should always include response time numbers, transaction metrics, error percentage, throughput, and server utilization.
Once these performance metrics are available and accessible to all relevant stakeholders, it also becomes easier to analyze performance history and plan design improvements to keep on improving. Besides the aforementioned Capacity Testing best practices, you should be conducting capacity tests for different infrastructure configurations and sizes (CPUs, memory, etc.).With most websites now serving audiences from different parts of the world, it’s also important to run Capacity Tests with different network conditions and also for different geographical locations.
Below, we look at different types of capacity tests and how they are used in real-life examples.
Example: An online retailer prepares for Black Friday by conducting capacity testing to ensure their website can handle the massive influx of users. They simulate peak loads to identify the maximum number of concurrent users the site can support without slowing down or crashing.
This helps ensure a smooth shopping experience during the high-traffic event.
Example: A streaming service like Netflix or Disney+ performs capacity testing before a major live event, such as a highly anticipated series premiere or sports event. They test the system’s ability to handle a surge in viewers, ensuring that the streaming quality remains high and the service doesn’t crash under heavy demand.
Example: A bank conducts capacity testing on its online banking system before the end-of-year financial closure period. This period typically sees a high volume of transactions as individuals and businesses finalize their accounts. Capacity testing helps ensure that the system can handle the increased load of transactions and user logins without any performance issues.
Example: A ticketing platform like Ticketmaster performs capacity testing before tickets for a major concert or event go on sale. They simulate high traffic conditions to ensure that the platform can handle the rush of users trying to purchase tickets simultaneously, preventing crashes and long wait times.
Example: An educational institution conducts capacity testing on its enrollment portal before the registration period begins. This ensures that the system can handle the influx of students registering for classes simultaneously, maintaining smooth and efficient performance.
To sum it up, your performance SLAs need to be set, enforced, and tested constantly to achieve the organization’s business and financial goals. With time to market and code quality becoming increasingly important, you need to improve your Capacity Planning with Capacity Testing to determine the right infrastructure for each given scenario.
This is the only way to avoid surprises, keep customers happy, create an optimal user-experience, and optimize quality to increase revenue in a sustainable manner.
