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 the business revenue and 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 tests to identify these bugs at early stages rather than in production. 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. 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. 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. 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 test 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. As a specialized software testing team, it is essential to know how to properly execute the scalability testing to achieve the desired outcomes:. 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.

Published at DZone with permission of Rhea Dube. See the original article here. Trending Getting Hired as a Scrum Master or Agile Coach The Future of Rollouts: From Big Bang to Smart and Secure Approach to Web Application Deployments Amazon Web Services AWS : A Comprehensive Suite of Cloud Services Keep Calm and Column Wise.

DZone Software Design and Architecture Performance Scalability Testing Tutorial: A Comprehensive Guide With Examples and Best Practices Scalability Testing Tutorial: A Comprehensive Guide With Examples and Best Practices. In this tutorial, learn about scalability testing, its pros and cons, different scalability testing approaches, and how to perform it.

by Rhea Dube. Like 1. Join the DZone community and get the full member experience. Join For Free. What Is Scalability Testing? Why Perform Scalability Testing? Analyze how the application performs with an increase in workload and at what point the software product or application stops scaling so that we can identify the reasons behind it.

Helps to signify the user limit related to a software product or application. The x-axis represents the number of users while the y-axis represents response time in seconds.

As you can see, the results are almost perfectly proportional. A load of 20 users gives you an average response time of 5. If you increase the load to 60 users, the response time rises to 18 seconds.

If the outcome is not proportional, then you will experience bottlenecks with more simultaneous users. You may have to make adjustments to your server, software or hardware to achieve your desired results.

After every round of changes, you must perform testing all over again to make sure problems have been properly addressed. After your first round of testing, you can start upgrading your software and hardware by scaling up or scaling out. Scaling up and scaling out are not the same thing.

Both approaches to scalability testing come with their own advantages and disadvantages. While scaling up is theoretically simpler than scaling out, constantly upgrading hardware eventually produces diminishing returns. Each processor upgrade provides less benefit than the previous upgrade.

On the other hand, horizontal scaling might give you better results, but it can get expensive fast when you factor in the cost of maintenance.

The information in your reports will provide guidance for making improvements. For example, if your company's website is anticipating a percent increase in traffic over the next month, you may want to give your server performance a boost to minimize request processing time.

Possible options include upgrading your server hardware to allow for additional RAM. Alternatively, you could switch to a different server software.

Scalability testing should help you accurately project how changes in hardware and software will impact your server performance. That way you can gauge whether or not investing in upgrades is really worth it. Scalability test results are only helpful if designed correctly.

Proper scalability testing consists of a series of load tests using a number of hardware or software specifications while maintaining a consistent testing environment. Variables you have control over include CPU speed, server types, and available memory.

These are the essential steps to designing adequate tests:. Make sure to specify the same number of users and the same settings whenever you repeat tests. IBM has a terrific guide to designing performance tests with more details.

The best testing tools for you will depend on your project and your preferences. Fortunately, you'll find no shortage of free tools for testing performance, reliability, and scalability. We've written about a few testing tools in the past in our website performance optimization article, which included:.

Additionally, Tech Beacon has an impressive list of 12 open source performance testing tools. Blaze Meter also has a detailed comparison between popular performance testing tools like Gatling, Tsung, JMeter and the Grinder.

Scalability shouldn't be seen as optional; it's pivotal to the success of any growing web application. An old piece of business advice goes, "If you're not growing, you're dying.

Businesses that don't anticipate large increases in demand may find themselves facing hard times, so run those scalability tests to make sure your application is ready for whatever gets thrown at it.

Scaling when it pertains to web performance essentially means the ability to support any traffic…. Scalability Testing - A Guide and Checklist By Cody Arsenault.

Tags webtesting. How to Effectively Monitor and Scale for Website Traffic Scaling when it pertains to web performance essentially means the ability to support any traffic…. Supercharge your content delivery 🚀 Try KeyCDN with a free 14 day trial, no credit card required.

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This is a step that software engineers can easily forget. Every test should have a report that gives evidence of the outcome. The most important thing is to see if your targets are met.

If so, then you are ready for production. If your targets are not met, more work needs to be done. You should only change one variable at a time and observe its impact on the outcome.

Modifying multiple parameters like the quantity of RAM and the number of servers at the same time would not give conclusive results as to what the best scaling strategy is. When running a scalability test, reset as much of the system as possible between separate test runs. Systems will accumulate data during scalability tests and can affect future tests.

Do not rely on the first test results to make your changes. The dependencies of your application might change weekly or even daily. For example, NumPy , a Python package used to manage data types and arrays, has been releasing updates weekly.

If you set up your app like that, you need to ensure a test is done at least weekly to check if the dependencies are still working correctly. Your target and goal must be updated based on the company vision and potential for growth and then you need to revisit that test plan periodically.

How do you know when your application is ready for production? Your data is ready when it shows you that you can achieve some of the key targets you defined at the beginning of the scalability test process. Scalability tests ensure that as the load on your application increases, your servers, nodes, and other system resources scale properly to handle it.

It might feel like a lot of extra work to run these tests, but if your goal is to increase the user experience and avoid problems on the frontend, employing scalability tests is essential.

In this article, you learned about scalability tests, their benefits, and how to use their results in an advantageous way. But imagine if there was already a tool that can automatically design scalability tests specifically for your needs. Speedscale offers just that and more by providing a service that helps you test your APIs with real-life scenarios using data replay capabilities.

If you want to implement scalability testing, Speedscale is an incredible resource for you as you get started. All Rights Reserved Privacy Policy. SIGN UP.

Sign up for a free trial of Speedscale today! API Observability. Scalability Testing Best Practices. By Nate Lee January 29, Get started today. Replay past traffic, gain confidence in optimizations, and elevate performance. Try for free. The Importance of Scalability Tests Scalability tests are part of the performance test family.

Improves User Experience No one wants to use an application that takes a long time to load. Reduces Infrastructure Identifying critical points where performance becomes unacceptable is essential for architects to start thinking about the evolution toward a more scalable system. Remember your goals are: To validate that you can handle your target number of concurrent users To identify critical points where user experience becomes degradation To create a scaling plan to adapt your resource to the number of users Set Up Your Target Before you begin, you need to define your goals and decide what metric represents the best user experience.

Analyze the Data To ensure you understand what changes need to be implemented, you need to report what resulted from each test. Best Practices for Scalability Testing Before you begin implementing scalability tests, keep these best practices in mind.

Keep It as Scientific as Possible You should only change one variable at a time and observe its impact on the outcome. Test and Repeat Do not rely on the first test results to make your changes. Are You Ready for Production?

Your application is scalable when it can deliver the same response time even as the number of users increases. If the number of requests handled over time is maintained as user numbers increase, your application is ready.

CPU Load : The less CPU utilization you have, the more efficient your tool is. If you want to have more throughput and less CPU load, you should optimize your code. Memory Load : The less memory your tool uses, the more scalable it is.

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Data Warehouse. Introduction of Scalability Testing Another type of performance testing is scalability testing , which comes under the non-functional testing of software testing. The Objective of Scalability Testing Following are the critical purposes of scalability testing: The main objective of performing the scalability testing is to control how the application balances with an increasing workload and at what point the software product or the system stops scaling and identify the reason behind it.

The scalability testing is needed to signify the user limit for the software product. To find out the client-side degradation, end-user involvement under load, and server-side stability. The usages of scalability testing will make sure the ability of software to scale up with the increasing workload and data traffic.

Why do we need to perform the Scalability Testing? The scalability testing is needed if we encounter the following issues: In case of any modification in the software lead us to its failure?

After the enhancement, the software is working correctly and efficiently in meeting the user requirements and expectations. Whether the software can produce and improve as per extended needs? Types of Scalability testing Scalability testing is classified into two parts, which are as follows: Upward scalability testing Downward scalability testing Upward scalability testing The upward scalability testing is used to expand the number of users on a specific scale until we got a crash point.

Downward scalability testing Another type of scalability testing is downward scalability testing. The Precondition for Scalability Testing For the scalability testing, the test strategy can be changed based on the type of application being tested. We have some default precondition available for scalability testing, which is as follows: Operating System If we want to perform the scalability testing, we need to verify what operating systems are prepared by the load generation managers and load test master.

Load Distribution Capability It is used to analysis if the load testing tool allows the load to be created from several devices and measured from an essential point. Memory Before performing the scalability testing, we must analyze how much memory would be sufficient for the virtual user and load test master.

Processor We need to analyze what type of CPU is required for the load test master and virtual users before executing the scalability testing. Feature of Scalability testing Some of the vital components of scalability testing are listed below; let see them one by one: Throughput Performance measurement with many users Memory Usage CPU Usage Network Usage Response Time Throughput The throughput feature is used to specify the amount of work implemented by the application in the given time.

The throughput can change from one application to another.