In this content, we will explain the importance of performance tests. Furthermore, we will show some of the main tests carried out, explaining their main steps so that the application reaches users in the most functional and useful way possible. Good reading!
Why are performance tests important?
Once a solution is sold to the public, there will always be a risk of bugs. That’s why performance tests are so important, as, through them, several points are checked, such as the capacity of the system to support a certain number of accesses at the same time.
Another aspect considered in performance tests is the inconsistency of the solution between different platforms. In other words, the behavior or appearance of the system changes significantly between one platform and another, including environments, devices and operational systems.
Some possible reasons for these inconsistencies are:
- differences between APIs;
- system settings;
- hardware resources;
- available libraries;
- design guidelines for each of the platforms.
To prevent users from experiencing this type of problem, it is very important to carry out comprehensive testing in various environments and operating systems during development. Carrying out this check before the final result reaches users’ hands reduces the risk of a bad experience, which could harm the company’s image and affect its revenue.
Identifying performance bottlenecks
For a user, one of the most desired things is a quick response system, but it is necessary to know, for example, how many simultaneous accesses the application allows without its responsiveness being affected. It is important to highlight that not every user request will have a quick response, considering the degree of complexity of each one.
This optimization is based on human psychology. To explain further, if a person tolerates waiting five seconds for the system to respond, they will be irritated if a product is delivered that responds in longer. Therefore, both the application and user preferences are considered in identifying bottlenecks performance.
To give you a more precise idea, in an online system where users perform many tasks simultaneously, the response time, most of the time, should be, at most, one second. This consistency is measured over several test cycles.
When the system load grows (that is, the number of simultaneous users increases), the development team needs to find bottlenecks. In general, these bottlenecks can be:
- in application;
- in the database;
- in the operating system;
- on the data network.
In addition to the long response time, another possible bottleneck is the high consumption of hardware resources, such as memory and CPU.computers and notebooks. If a company works with a certain data processing speed, a system like this will certainly harm its operation, potentially affecting customer experience and business profitability.
Optimizing the code first requires identifying the application’s bottlenecks. In practice, one of the ways to improve performance is to use linear or logarithmic time algorithms, as both run faster compared to, for example, a sequential search code, whose time complexity is O(n).
Improved user experience
One of the worst scenarios for the user is when the system goes down due to a spike in access. In this case, there is a scalability problem, which reduces the propensity of this system to remain functional and useful to users for a long time.
Long-term cost reduction
If a system does not require much of the hardware, the tendency is to exchange equipment take longer to happen, which helps reduce long-term costs. Furthermore, if the application is scalable, it will not need to be changed when the company has a greater volume of operations.
Even though the current investment may be high, the business and users will feel how beneficial this system is in terms of costs. It is also worth highlighting that performance tests contribute to reducing costs in maintaining these systems. Therefore, the user will not spend a long time without using the application — and, therefore, will be more productive.
What are the main types of existing tests?
There are many performance tests, but in the following topics we will focus on four of the main ones: load, stress, volume and scalability. Follow along!
During development, you must submit the software to certain loads and see if it maintains its responsiveness. In practice, the idea is to know how the system behaves with concurrent access, resource overload and internal processing.
As there are no real users to access the application at the same time, so-called simultaneous virtual users, or VUs, are used, which are responsible for executing different usage scenarios in parallel.
The main steps of load testing are:
- definition of scenarios: may include, for example, executing transactions in a web application or sending service requests to a backend system;
- load configuration: consists of defining the number of VUs, the transaction arrival rate, the expected response time and other relevant parameters;
- Test execution: During testing, the system is monitored, so various data is collected, such as response time, resource usage, and error rate.
Stress tests are used to evaluate the behavior of software under extreme conditions of use. Unlike load testing, it only aims to check how the application behaves with a predictable number of users.
In addition to being carried out in a controlled environment, the stress test seeks to assess whether the system has the power to recover in an extreme load or stress condition.
The general objective of volume testing is to know how the system behaves when it is dealing with many data. This involves not only the processing, but also the storage and transmission of these records, including both normal operation and scenarios where the volume of data is more significant.
Some types of systems that must be subjected to volume testing are:
- database management systems;
- cloud storage systems;
- real-time processing platforms;
- e-commerce applications.
Scalability tests evaluate the software from both a horizontal and vertical point of view. In the first, the distribution of the workload across several machines is considered, and in the second, the addition of more hardware resources to just one machine. The idea is to check whether the software correctly meets the growing demands of users, data volume and processing.
How to perform performance tests?
Check out the main steps to be taken when carrying out a performance test below!
Choose testing tools
This is a choice that will depend on the type of software being tested, the execution environment, the available budget and the specific needs of the project. Furthermore, the tools that will be used must be flexible and scalable, considering that it is necessary to deal with different scenarios and workloads.
In practice, these tools must allow personalized scripts, so that it is possible to simulate different user interactions and behaviors. Another important point when choosing a performance testing tool is its ease of use, as well as the ability to generate reports and visualizations that facilitate the analysis of results.
Define performance metrics
Some of the main metrics adopted in performance tests are:
- response time: it is usually measured in milliseconds and can be divided into average, maximum and minimum response time;
- transfer rate: measures the amount of data that can be transmitted between systems and users in a specific time interval, measured in bytes or transactions per second;
- competitors: are the simultaneous users of the system that do not affect performance, and are used to check how scalable the application is.
Create realistic test scenarios
Depending on the software tested, the scenarios need to match its actual use. This means, among other things, knowing the number of simultaneous users and the types of transactions that will be executed. It is also important to capture real data from the system in use, including access logs, recorded transactions or historical data, for example.
Analyze the results
The type of software is directly related to what the analysis considers to be a satisfactory result or not. Furthermore, the chosen metrics must be considered in this process, so that a comparison can be made between what was expected and what was obtained in the performance test.
For example, it’s important to analyze how these metrics vary as workload increases. It is essential, in this case, to identify whether the system behaves linearly, whether there are saturation points or specific limitations in terms of scalability.