As a software engineer responsible for building new backend (micro) services, it’s not sufficient to only test that they meet functional requirements. There are additional technical tests, focusing on the quality of the software, that must also be completed to ensure that your new service/application is production-ready. Whilst such tests require additional effort and can push out the date for getting your new service into production, they’re essential if you want to be confident of how your service will operate in production, and avoid any surprises that could negatively impact your business. The main types of tests I’m referring to are load testing (itself a type of performance testing) and soak testing. I’ve covered the subject of load testing (specifically measuring throughput under load) in a previous blog post. In this blog post I cover soak testing, including the aims of this type of test; how to soak test any service (regardless of the language it’s written in) that runs on the Java Virtual Machine (JVM), including those that run in a (e.g. Docker) container.
As an online business grows in popularity it can highlight scalability problems in your architecture. Certain hardware and/or software components can struggle to keep up with increased demand and it may not be easy or cost-effective to address this by extending them in their present form, especially when the demand is ‘spiky’ in nature. My team was recently faced with such an issue. We decided to engineer our way out of the problem by designing a more scalable replacement solution. Key technical requirements for the new solution included the throughput and latency of a public web API. In this post I share details of how you can measure these performance characteristics of an API using Apache JMeter, and in the process I identify a very useful supporting JMeter plugin.