When developing a software application, the developer usually sees how the application will work in an ideal scenario, not how it will work in the real world. Doesn't matter how well the software application functions; it could still fail when put under excessive load. Therefore, checking the software's functionality and whether it works flawlessly under increased or decreased workloads becomes imperative. This is where scalability testing comes in.
Scalability testing makes it easier to fix defects and ensure software applications' flawless functioning. As part of the testing process, testers usually draft test scenarios that force the system to meet new requirements. Additionally, they run regular tests and document and record the results to identify errors. After that, the obtained data and actionable insights are communicated to the relevant stakeholders.
Let us try and understand the fundamentals related to scalability testing and why organizations need to have strategies and processes around scalability testing.
Scalability testing is a type of non-functional testing that validates the performance of a system, network, or component by increasing or decreasing the load in particular scales. You can execute scalability tests based on hardware, software, or database requirements. Scalability testing aims to ensure that the system can cope with the projected increase in user traffic, data volume, transaction processing, etc.
It is also known as performance testing, where the focus is on evaluating the overall system behavior when it is tried and tested under extreme conditions, such as excess load or new deployments to a broader environment.
In software engineering, scalability testing helps measure the point when the application stops scaling and identifies possible reasons for it. Scalability testing should not be confused with capacity testing.
Capacity testing is all about measuring the maximum number of users that an application can handle at a given time. Scalability testing is more about scaling up and down aspects where fluctuations come and how the system handles them.
Scalability testing is a crucial factor in the deployment of software applications. It helps to achieve the following objectives, which are great from a business growth perspective.
When an organization tries to perform scalability testing for its website or web applications, it depends on various factors, such as the number of users accessing the application simultaneously, CPU usage, and network usage. The scalability testing of a server depends on the number of requests processed and the network bandwidth.
Consider a scenario of an e-commerce website whose performance remains top-notch on standard business days. Still, during the festive season or sales, the load or traffic increases by 3 or 4 times resulting in slowness and performance issues. This will impact not only the business revenue but the brand reputation in the long run.
Applications must be built to cope with many user requests, data volume, and other workload requirements. This means that the customers who use this application will have an incredible experience and recommend it to others.
Below are the benefits of running scalability tests into the software development and testing process.
On average, fixing a bug in production can cost up to 10 times more when compared to fixing it during the testing phase. That is why you need a reliable process related to scalability testing to identify these bugs at early stages rather than in production.
Let us understand some of the disadvantages of scalability testing, which you should be aware of.
Let us try and compare the two different testing types based on various factors.
|Scalability testing||Stress testing|
|It is performed to ensure that a software product or application can manage the scheduled spike in user traffic, data volume, etc.||It is performed to find the robustness of the software by testing it beyond the defined limits.|
|The load can be varied slowly.||The load is varied abruptly|
|Used for server-side testing robustness.||Used for testing the client-side robustness.|
|Used for testing end-user experience under heavy load.||Used for testing the experience under a sudden change in load.|
|It is performed to evaluate the threshold load.||It is performed to evaluate the system recovery ability when a sudden failure occurs.|
It is important to follow the right prerequisites before building a scalability test plan. Here are some of the attributes for creating a well-defined plan.
Here are some common attributes you need to consider during scalability testing.
For example, a web application throughput is tested by verifying the user requests processed per unit of time. In the case of a database, throughput is calculated by the number of queries processed at a time.
It is tested at various loads by increasing the number of users or the requests per user. You can use a load balancer to ensure that the load is distributed evenly in a clustered environment. The application will perform better if the response time is lower.
Following are important prerequisites to consider before taking up scalability testing.
There are two primary approaches you can follow for scalability testing.
It involves adding more and more physical machines and resources, resulting in a reduction of load on each machine or resource. This process is about increasing the number of nodes instead of increasing the existing capacity. The load is divided between the old and new resources that are added. It is also known as scaling out, which is done from an outward direction by gradually increasing the resources.
This type of scaling is done in big tech giants, such as Google, Facebook, Amazon, etc., that work with large projects or applications. Data partitioning is involved where the load is divided between different nodes, and the overall performance is improved in the long run.
It increases the power of existing machines in terms of CPU, RAM, and memory requirements. Vertical scaling can add more CPUs to the same single server. For example, the work handled by 1 CPU can now be handled by 4 CPUs for better performance and output. It is generally done by mid or small-sized businesses that manage small applications where the performance can be maintained by just increasing the size and capacity of the existing resources we use.
The industry standard tools can play a vital role in simplifying your scalability testing requirements. Some of the popular scalability testing tools that are used worldwide include
These tools can help you deliver exceptional outcomes when it comes to testing and overall product quality.
You can choose the tools based on the following factors.
As a specialized software testing team, it is essential to know how to properly execute the scalability testing to achieve the desired outcomes:
You can follow the steps below to get started.
Identifying a test environment that accurately mimics the intended production environment is crucial.
Using a real device cloud lets you test in real-world scenarios and ensure that results are accurate every time. Rigorous and bug-free testing ensures that no significant issues slip into production, allowing your software application to provide the best user experience.
Defining a process is crucial for the product’s success in the long run. The process should be finalized after getting approval from all the required project stakeholders. Once the process is streamlined, it becomes easier to define the required criteria and tools. You can improvise or redefine the process to get desired outcomes in the long run.
You can follow some best practices to ensure that your scalability testing delivers the desired outcomes:
In this tutorial, we discussed the different features and capabilities of scalability testing offers. Your software application and test infrastructure must be capable enough to withstand the dynamic requirements of today’s market. As the time to market and software quality become so important, you need to implement scalability testing to ensure that all fluctuations are not impacting your performance metrics or degrading your software quality.
Testers usually generate test scenarios so that the system meets new requirements. Furthermore, they execute the test regularly, document and record the results to detect errors. The obtained data and important insights are then communicated to relevant stakeholders.
Scalability testing uncovers major infrastructure errors often missed by other testing methods like load testing. You can quickly pinpoint the source of defects since this form of testing covers all levels (hardware, software, database).