Load Testing of an application, the simplest form of performance testing involves the creation of heavy user traffic and measuring its response in a testing Environment. A testing environment is a cloud infrastructure in which vendors deploy web-based applications in a cloud to validate their quality. A production environment is where the real-time staging of programs that run an organization is executed and includes the personnel, processes, data, hardware, and software needed to perform day-to-day operations. Since exactly replicating the production environment for the purpose of testing is very difficult, a few popular methods are used to build a test environment that is as close to the production environment as possible, in order to achieve the same.

1. Testing on a replica environment

Ideally, having a load test environment which is an exact replica of the production system, helps you obtain the load results in real-time. Though this seems to be the pacifying solution, it is, however, not practical when using big data. Building an exact replica of the production system is not always possible due to its associated costs, time and challenges. The biggest challenge here is that every aspect of the production environment has to be duplicated i.e., including the load balancers, machine profiles, configuration, DB, network architecture, etc.

2. Testing in a scalable environment

Preparing the exact performance test environment as the production environment might not be possible always because of the complexities involved in replications. To cover this loophole, what many performance engineers do is, perform the load testing on a smaller environment as compared to the production environment. The results obtained from the scaled environments are then extrapolated for a presumption. The advantages of testing on scaled environments are that it requires less infrastructure to set up, very cost-effective and easily identifies the application bottlenecks. The disadvantage is that it becomes very difficult to find out performance issues in the real environment.

3. Testing on duplicate customer environment

Testing on a duplicate environment works really well. What if you’re working on an on-premises solution, wouldn’t that be very difficult to simulate a real-life environment for testing? Wouldn’t that be a herculean task? It is hence, suggested to duplicate a customer’s production environment and perform the load testing. The purpose would serve better the performance analysts when they try working with selected customers who could provide them with all necessary information and help you with the privacy settings. By doing so, you are working on testing your customer’s real environment and this could turn out to be your best bet.

4. Load Test environment setup

Tired of building a duplicate environment? There is another way. Rather than building a testing environment every time, you can have a test environment setup established quickly which can be re-used when needed. Once the setup environment is configured and starts working, you can create images of it so that you can recreate the same in minutes as and when needed.

5. Testing in Production Environment

Testing in your own production environment is one of the best yet riskiest solution for testing as it requires no replications. Despite its better outcomes, testing in the production environment is still one of the rarest approaches followed in load testing. No additional costs or time required because you will not have any replications. Performing load testing on a live application facilitates validating the test environment results. However, it has to be made sure to back up the production data so that once the testing is done, you can quickly revert to the real environment. It is highly recommended to use the user accounts while simulating the activity you want to test. Moreover, not many would prefer testing on the live application as it has its own challenges.

Building a realistic test environment that is close to the ideal is critical for successful load testing. Though time-consuming, it prevents catastrophic failures.

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