Performance testing for APIs and microservices
API performance testing measures how the interfaces through which your systems communicate behave under load, without a browser or page rendering. It helps separate backend behaviour from the user interface and narrow the search for problems such as slow database queries, an exhausted connection pool, or an overloaded integration.
Common problem: the interface hides the cause of a slowdown
A test through the user interface is useful for verifying the complete customer journey, but it combines several layers at once. The browser adds rendering, script loading, and network requests, so the result alone may not show whether the slowdown originated in the API or while the page was being assembled.
With microservices, one service may call several others, and a slowdown in the chain appears externally as a “slow website”. Measuring selected APIs together with tracing and system metrics helps determine which part of the chain to investigate first.
How to measure performance directly at the API
We can first load-test selected API interfaces separately to measure their behaviour without browser overhead. It then makes sense to prepare a realistic mix of calls that reflects actual traffic. A separate measurement shows which call slows under a given load; the cause needs to be confirmed with application and infrastructure data.
We measure response times in percentiles (p95 and p99), along with the error rate and throughput. If server, database, and individual-service metrics are available, we compare them on one timeline. This makes it possible to narrow the search for a bottleneck to a particular endpoint, query, connection pool, or dependent service.
Depending on the risk, we choose a load, stress, or spike test: expected traffic presents a different question from a sudden surge. Scenarios in k6 or Locust can live in the repository, and selected checks of an appropriate size can also run in CI. Larger measurements usually run in a controlled environment and time window. These are the same APIs that we cover with functional tests, but here we measure their behaviour under load.
What API measurement gives you
- A narrower set of likely causes: a specific endpoint, query, or service instead of a general “the website is slow”.
- Backend measurement without browser overhead, complementing a test of the entire user journey.
- Capacity risks in APIs, databases, and integrations identified early.
Next step
Select the API interfaces that matter to a key process or already show slow responses. Add the expected load, response-time and error-rate limits, and available system metrics. This information can be used to prepare a measurement that answers a specific capacity question.