What are the best practices for testing software with API gateway request rate limiting policies?

1 Understand the rate limiting policies

Before you start testing, it is important to understand the rate limiting policies applied by the API gateway. These policies include fixed window, sliding window, token bucket, and leaky bucket. Each type has its own pros and cons that may affect your testing scenarios differently. Additionally, you should be aware of the granularity, scope, and enforcement of the policies, such as if they apply per user, per IP address, per endpoint, or per service, and if they are strict or lenient.

2 Design realistic test cases

Once you have a clear understanding of the rate limiting policies, you can design your test cases to simulate realistic scenarios and expectations. For instance, you can use representative data and parameters for your requests, such as user IDs, query strings, headers, and payloads. Additionally, you should vary the frequency, volume, and distribution of your requests, such as using different patterns, spikes, bursts, and intervals. You should also test different combinations of endpoints and services, such as using parallel, sequential, or nested calls. Moreover, you should test different types of requests (GET, POST, PUT, DELETE, and PATCH), as well as different error and success scenarios (429 Too Many Requests, 503 Service Unavailable, or 200 OK responses). Furthermore, you should consider the impact of the rate limiting policies on your software's functionality, usability, and security. This involves verifying that your software can handle rate limiting errors gracefully (e.g., displaying appropriate messages or retrying requests), performing its core tasks within the rate limits (e.g., completing workflows or transactions), and complying with the rate limiting policies without compromising its security (e.g., avoiding exposing sensitive data).

3 Use appropriate tools and methods

To execute your test cases effectively and efficiently, you need to use the right tools and methods for your software and the API gateway. For instance, Postman, SoapUI, or JMeter could be used as a testing framework or tool that supports API testing. Additionally, WireMock, MockServer, or Mountebank can be used as a mocking or stubbing tool to simulate the API gateway and its rate limiting policies. Furthermore, Prometheus, Grafana, or New Relic can be used as a monitoring or analytics tool to track and measure the API gateway's performance and behavior. SonarQube, Codecov, or Codacy can also be used as a code coverage or quality tool to assess and improve your software's code and design. It is important to follow best practices of software testing such as writing clear test cases and scripts with descriptive names, comments, and assertions; organizing and managing test cases with folders, labels, and tags; automating and scheduling tests with triggers, pipelines, and hooks; and reporting and documenting results with dashboards, charts, and logs.

4 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?