One growing pain of increasing iterative development and shortening release cycles is a growing inability to detect and fix inefficient code – whether in the CI/CD pipeline or in production.
Engineering, QA, and SRE leaders have seen this trend cause critical setbacks in system reliability and resilience. One emerging solution is to load test-isolated components earlier in the software development lifecycle (SDLC) to give developers early feedback using mock servers, virtual users, and parameterized scenarios. However, load testing in the pipeline can delay feedback loops and extend shipping times.
In this guide, you will learn how modernizing load testing and performance monitoring practices with backend or API load testing allows developers to improve code efficiency throughout iterative changes without causing bottlenecks. You will also see how testers and SREs can use API load testing via container deployments to validate the performance of production traffic better than synthetic performance monitors alone behind the firewall.
API load testing is a type of backend performance testing used to assess an application programming interface's performance under varied load conditions. It is used to determine an API's overall performance as well as its capability of responding to concurrent queries from high numbers of virtual users. Shift-left API load testing simulates traffic to an API while it is still under development and before it is deployed to production in order to mitigate performance problems associated with excessive load. Using API load testing, developers and QA teams can locate performance bottlenecks that, if left unattended, may have severe effects on output and general business operations.
API load testing seeks to identify and monitor component metrics such as throughput, latency, and response times as well as general server conditions in order to validate system performance criteria under the anticipated workload. API load testing can be classified into several types, including:
A standard API load test evaluates your API's performance when it receives requests at the expected rate in production.
API stress tests determine whether your API continues to respond normally in the face of unusually high demand.
In spike testing, you alternate between moderate and peak request levels to see how the API reacts when request rates suddenly spike.
API soak testing entails subjecting your API to high request rates for an extended period to detect issues that may not be visible during shorter periods of high load.
API load testing is an important aspect of software testing. It provides several benefits, such as faster loading times, more efficient API performance, lower risk of system failure, and lower costs. This section discusses the benefits of API load testing in depth.
Detecting API performance issues early – especially before deployment – will cost an organization substantially less than having to deal with API downtime during production. The biggest threat to site uptime is API downtime, which is what happens when your APIs are unable to carry out their intended functions. This is because an API outage could cause irreparable damage to both the infrastructure used for the integration and the company's reputation. API load testing enables specialized testing to find and fix bugs in the code that can result in subpar performance under both anticipated and unforeseen stress, thus minimizing the cost of failure.
Inefficient code is one of the factors that contributes to bad API performance. API load testing makes it possible to spot implementation flaws and code oddities that would otherwise be difficult to find, thereby reducing API latency and improving performance.
API load testing demonstrates how many user requests an API can process without crashing, which helps you avoid API downtime. In addition, it reduces the possibility of API downtime by helping to locate and isolate the requests that need performance improvements. With the help of load testing, resources can be set aside to handle excessive traffic in order to minimize API downtime.
By measuring the volume of API requests and traffic for various use cases, API load testing ensures that the optimal infrastructure is set up. API load testing helps identify a single API endpoint's maximum number of concurrent user requests. With the help of this information, QA testers can keep extra resources on hand to manage any anticipated spikes in traffic in the event that the infrastructure proves insufficient. Therefore, it helps to estimate the scalability of the API infrastructure.
Customer churn is the main effect of API outages and poor performance, which can cause businesses to lose both current and potential customers. Thus, organizations that work with direct and third-party customers can think of API load testing as an investment. This investment leads to improved client satisfaction, which ensures customer retention.
With various endpoints, as well as end users' high expectations, API development can be incredibly difficult to implement properly. As a result, APIs frequently experience performance problems, and the things that suffer the most include response times, latency, and throughput. Therefore, teams must perform load testing on their APIs in order to enhance performance. API load testing can help detect any performance bottlenecks and enhance API performance in general before you deploy to production.
In a traditional approach, testing experts generally perform API load testing when a project is nearly finished in order to determine whether it is ready for deployment. By conducting these tests, they can spot and fix performance issues at an earlier stage, thus reducing development time and boosting project effectiveness. Teams should perform load testing as part of their deployment preparation strategies so that they can increase their confidence in their API product’s performance.
API load testing is also performed when teams want to ensure that the performance of individual API endpoints is assessed (and fixed, if necessary) separately. This guarantees that only one load is applied to each API endpoint at a time, which prevents performance imbalances.
The key to successful API load testing ultimately comes down to good collaboration between developers (or testers) and SREs. The need to improve handoffs is one reason why teams may move toward continuous API load testing. With the continuous approach, developers get the early feedback loops they need to ensure that code remains efficient and reliable throughout iterative changes, particularly, as real-world scenarios evolve and it becomes more difficult to emulate production environments. Further, this approach may reuse API functional tests as API load tests – resulting in API functional load tests that can go beyond uptime to reveal how stress may change how an API functions.
Consider the following API load testing example: An API load test passes for a team anticipating a traffic spike during a special holiday sale for their e-commerce app. Separately, a functional test also passes for the app’s API flows. However, on the day of the holiday sale, as traffic spikes, the app suddenly fails to let customers enter all of their payment information, and the sales process is abandoned. Only a continuous API functional load test might have provided the holistic feedback with mocked or production traffic to alert the e-commerce team before it was too late.
Sauce Labs API Testing makes use of an existing functional test to perform load testing on your endpoints. It does this by using a lightweight load agent within your infrastructure. To load test your APIs using Sauce Labs, you must first configure your infrastructure (such as Docker or Kubernetes) with your agents and identify them with separate group IDs. After that, you can execute the command to load test your APIs.
Use the following command to run an agent:
docker run --pull always --rm \
--env SAUCE_URI=wss://<api_domain>/api-testing/ws/v4/loadtesting \
--env WORKER_ID=<worker_name> \
--env POOL_ID=<pool_name> \
--env MAX_VIRTUAL_USERS=<max_virtual_users> \
After running the agents, you can follow the steps below to test your APIs with Sauce Labs:
Start by clicking API Testing in Sauce Labs.
On the Tests page, click the Load Test button next to the API you wish to test.
Select Create Load Test.
Fill in the necessary information on the Create Load Test screen, then click Save and Run. For further information, see the section called “Create Load Test Fields” in the Sauce Labs docs.
Examine the results of your load test.
The image below shows an example of an API load test report generated by Sauce Labs:
Learn more with the complete Sauce Labs API load testing tutorial.
API load testing, which identifies how stable your APIs are under different workloads, is a crucial part of performance testing. It helps eliminate performance issues that can lead to problems like slow API response times, wasteful code, hidden flaws, and API downtime. As we explained above, failure to implement API load testing could be detrimental to your business.