A full-day course exploring techniques for improving the performance of microservices.

We will begin by considering a very simple JSON/REST-based service, built using a few popular open-source libraries. In order to measure any improvements made during the course, the next step will be to add a simple load-testing harness and monitoring capabilities for latency and throughput.

At this point, we will spend some time reviewing the gathered metrics, and determining some areas for improvement to help us understand where performance problems lie.

Now that suitable monitoring is in place, we will then apply a scientific approach to experimentation. This will be an iterative process where we will continue to improve the performance of the service to its limits.

In our world of continuous delivery with repeatable builds and automated deployments, performance testing is often bolted on as an afterthought.

This can be an acceptable strategy until your application becomes popular, after which customers can start complaining about application response. As technologists, it is our responsibility to be able to reason about and improve the responsiveness of our systems.

Good performance testing is not only about catching regressions; it is a key enabler of measurement, investigation & optimisation. With integrated profiling and measurement we can determine how to drive efficient use of compute, network, and memory resources.

In this talk we will cover techniques for making performance testing a first-class citizen in your Continuous Delivery pipeline. Along the way, we will cover a number of war stories experienced by the team building one of the world's most advanced trading exchanges. Finally, we will explore how this approach fits in to the landscape of containerisation, virtual machines, and provider-managed resources.