When we run our software, we obviously want to see and understand what is happening and how well our software performs. To achieve this, we need observability as a key characteristic for our software. Observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs. This definition, borrowed from control theory, infers that metrics, tracing, and logging are key topics to be implemented in your software system.

Two of these pillars, metrics and tracing, are also of great importance to allow yourself to paint the complete picture. In this blog post, I will focus on getting the most benefits from your logging.

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All contending teams, without exception, experience a moment at which all members are standing around the table, looking at the robot; this is not what’s supposed to happen. Shouldn’t be a surprise, we told them in advance there would be bugs. Unfamiliar with the codebase and the hardware, it is now their job to find the bugs and fix them. They do know what the robot should do: ‘it should follow the black line, once you press the start button’.

We have been doing these robot challenge workshops for a while now. They’re great fun, for creating a shared understanding between business and IT, or experiencing an acceptance test-driven approach to software development. The mBot robots bring a highly visible aspect to the software’s behaviour.

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