Performance testing is basically a non-functional testing technique, designed and implemented to check how a system performs in terms of responsiveness and stability under the desired workloads.
It validates and verifies that the application meets the desired requirements under normal conditions. This can monitor how database, application code and hardware perform under load.
Imagine an ecommerce website on the biggest sale days of the year. There is unprecedented spike in traffic around holidays and sale days and to handle the sudden surge in traffic, it has to be prepared for the maximum number of users completing their transaction without a glitch. This is just one routine use case where carrying out performance testing to check the maximum capacity of the website would hep the retailer prepare better.
What are some common objectives of performance testing?
To determine speed/ or business transaction response time
Find out system bottlenecks if any:
- Network bandwidth and latency
- Server resource usage
Identify the optimal configuration for hardware/software
Verify the current system’s capacity and scalability from the future perspective:
- Number of users the system can support
- Whether the application will meet SLA
While performance testing measures system attributes such as reliability, scalability, resource usage, there are many types of techniques involved.
Types of Performance Testing
Load Testing: it is the most essential form of performance testing that is carried out to understand system behavior under specific loads. It is critical to measure important transactions and their load on the database or server.
Stress Testing: This is also known as endurance testing. It basically determines the system’s robustness and error-handling capacity under high load conditions. So, it tests beyond the normal operating boundaries and verifies how the system performs under extreme conditions. This is done to ensure that the system doesn’t cash under heavy load.
Soak Testing: This is also known as endurance testing. Soak tests are designed to run a controlled load, over a prolonged period of time. The idea is to test for resource conception and non-release. These can only be identified over time.
For instance, if there is a gradual memory leak, there is no impact on system over the short term. Over a period of time this could cause a major resource crunch. Using soak tests, you can determine if the system can take the expected load continuously and consistently.
Spike Testing: It is implemented by causing sudden spikes in the load or number of users by a significant amount and then measuring system performance. This helps to verify if the system will function or break with sudden spikes in usage. One noteworthy aspect of spike testing is that the system should be able to normalize back to the steady state processing after the spike.
Scalability Testing: It tests any system that has been load tested or peak load tested but at the controlled multiples of the previous tests. For example, if you have load tested at 100%, then the scalability test would increase this load to 200%, 300%, 400% etc. However, here the spike is not sudden but gradual and controlled, and granular to identify performance issues at specific levels of scaling.
This is executed to find out the impact of configuration changes in the system’s performance. Configuration testing relies on the results of other performance tests. It tunes and tests various system and component configurations iteratively to reach the optimal performance or specified requirements.
Common Performance Challenges
Most issues related to performance involve speed, load time, response time and scalability. One of the most important attributes is speed. Slow running applications and websites lose user interest.
Performance testing process
The techniques and processes applied for performance testing vary based on type of application, expected outcomes and needs. But the larger goals are still the same. It can ensure your software meets pre-defined performance standards. It can also help you to compare the performance of two different systems. Most importantly, it can help identify where the problem is so that you can fix it.
Here’s a generic outline of a typical performance test process:
Knowing your test environment
Identifying the physical test environment, production environment and the testing tools that are available. You understand the hardware details, software and network configurations used in testing before beginning the process. This helps in the creation of more useful and relevant tests. It also enables to discover any potential challenges testers may encounter during the performance testing process.
Setting the performance acceptance standard
You need goals and constraints for throughput, response times and resource allocation. Also identify the success criteria outside of these goals. It is a good idea to find a similar application to include a variety of performance goals.
Planning and design
Design the tests and workload model around key scenarios but do test for all likely use cases. Try to simulate a variety of end users and planning performance test data outlining the metrics will be gathered.
Configure the test environment
Arrange tools, resources and support. Prepare the test environment.
Implementation and Execution
Finally, create the tests as per design and execute and monitor the performance.
Analyze the results
Last but not the least, analyze the results. Tweak and tune as required and retest to see if there is an improvement or deterioration.
The Importance of Performance Testing Complex Apps
Performance testing becomes all the more relevant in the context of today’s multi-tier architecture and complex apps. The implications of software failure are very serious. From huge monetary losses, to reputation and competitive risks, there is too much at stake. With the shift towards Agile and DevOps practices, performance testing is increasingly being automated now.
For business-critical apps, end-to-end performance monitoring is the solution. Performance testing goals should also target choosing the best of breed tools. Especially with new technology like AI and ML aiding the software testing lifecycle. You can now achieve remarkable optimization and outcomes owing to intelligent test automation that predict failures and prescribe remedies.
Performance Testing Best Practices
- Start earlier in the software cycle preferably at the design phase
- Thorough understanding of business requirements and expectations
- Design realistic tests that match the real-life application consumption
- Automated testing tools combined with quick backup and restore mechanisms are necessary because of the repetitive nature of performance tests.
It is the age of the customer; where user experience, security and expectations have a very high benchmark. The vast majority of software releases are deployed on shorter deadlines than ever before. At the same time, the cost of software failure is too high for any organization to overlook the importance of performance testing.