Performance Testing: The What, Why, and How

The Performance Evaluation's Broad Interpretation

The practice of going through user flows to ensure that the business logic of any workflow meets requirements and provides a positive user experience is known as functional testing. It is important to highlight the word "the user" (i.e., one person). During functional testing, one person frequently fills out forms, clicks buttons, and uses your website in place of an actual user. Though multiple people (or automated systems) can perform this testing in parallel, the site will typically not be overloaded with too many concurrent users.

In order to ensure that each workflow path is effective during functional testing, you frequently need to run through both positive and negative test cases using various data sets.

Contrarily, performance testing uses simplified versions of these procedures with a high enough user count to assess the system's infrastructure as opposed to its business logic.

You can be certain that a specific user can finish the task if a functional test passes.

You may be certain that a sizable user base will be able to easily access the website if a performance test is successful.

The Exact Specifics of Test Results

We discover related sector-wide development trends:

1. On-premise servers are replaced by cloud-based servers.
2. Making the switch to microservices from standalone apps
3. Weekly releases instead of monthly, quarterly, or annual releases, or hourly, per commit, or both
4. Using free software rather than commercial
5. From specially designed servers to fleet-managed containers

Despite the fact that these movements are quite popular, there are just as many different approaches to putting together a tech stack as there are witty comments on Stack Overflow. Despite the fact that websites are fundamentally just browser-based queries for HTTP and APIs, every architectural decision made throughout the development process has an impact on the scalability of an application.

Performance testing, as I noted before, tests infrastructure, not business logic. That implies that anyone with performance testing expertise can work with any kind of program, even if that is generally true. In certain cases, the fundamental architecture of the software, including the business logic, might affect performance. 

Here are a few rare yet interesting examples; the list is not all-inclusive.

• a gallery of images that users or affiliates have contributed (such as profile or product shots). If performance testing is done, redirects and photo compression might be feasible (at scale).

• a time-consuming procedure that is rarely used, like tax software or flower delivery. If different teams working on these procedures forget to complete performance selenium automation testing, the strain on these procedures could extend to other areas of the program.

• You should also consider the possibility that not all of your pages will need to be inaccessible during an outage. At one major eCommerce site, we had a policy to profit from "page not found" (404) errors. If there was an error on any part of the website, we designed pages that still provided the user with something useful but made it clear the visitor had encountered an unforeseen circumstance.  

• It's not necessary to have ugly 404 pages.

Our static HTML "red button" website would go live when an outage grew particularly serious. It kept making money for the company, was always accessible, and was kept in a brand-new cloud environment. It wasn't as convenient as not needing to use the red button, but it made our bad luck go down and didn't negatively impact the user experience.

Types of Performance Testing

• These comprise 80–90% of the work, albeit this is not an entire list:
• Stress/capacity testing measures the upper bounds of a system's capacity to handle load.
• Load testing aims to comprehend the changes and behavior a system experiences at different traffic volumes.
• Tracking a system's performance over time with both consistent and irregular usage patterns is necessary for testing for soak and endurance.
• To test databases and APIs more thoroughly, volume testing entails dumping massive amounts of data into a system.
• Scalability testing examines a system's ability to expand with increased traffic, including the capacity to move between cloud regions.
• The purpose of spike testing is to observe how a system responds to sudden spikes in traffic volume. The traffic on Black Friday is one instance. Another would be the announcement of a tour by Taylor Swift or Beyoncé.

more compact subgenres

Continuous observation, sometimes known as "heartbeat" monitoring, is used to test availability and resilience in order to alert and mobilize people in the event that a specific system detects an interruption.

By ensuring that your system can automatically switch to a different server cluster or location in the case of an outage, failover testing helps minimize or eliminate downtime. Being able to turn blackouts into brownouts is a big success for any software team.

The process of ensuring you can quickly restore your system and don't lose any crucial data in the event of a system failure is known as disaster recovery. Don't forget to put the recovery component to the test in real life.

Not all organizations mandate every kind of performance testing. I will emphasize again how important it is to understand your organization, your customers, and the architecture of your product. There isn't a single approach that works for everyone. If you are a retirement community manager, your traffic patterns, demographics, and tech preferences will be very different from those of a platform such as TikTok.

Steer clear of silos

It is equally vital to understand how these different types of performance tests interact with one another as it is with other departments and testing teams. For example, if your company is a large consumer bank or a prominent eCommerce site, you may be in danger of losing your business. As a result, you need to make sure that your performance calculations take into account your user analytics events. When these kinds of technologies break down, you feel much less like you understand the real situation with your users.