In the previous blog post , we looked at the importance of measuring quality and stability. These are important to ensure failures are reduced and system design remains optimal for the user experience. In complex software systems, failure is inevitable; what defines high-performing teams is not whether incidents happen, but how quickly, safely, and confidently they recover. Reliability and recovery metrics measure the resilience of your delivery ecosystem and your organisatio

In my previous blog post , I spoke about the importance of measuring flow metrics and how they can unlock blockers in your development practices and help you deliver more quickly. However, while speed and flow get software into production,  its quality and stability determine whether it stays there . High-performing engineering teams don’t optimise for velocity alone; they balance it with reliability, resilience, and customer trust. Quality and stability metrics reveal how sa

My last two blog posts have focused on the importance of metrics and how to capture your data to create meaningful metrics . I now want ot turn attention to focusing more specifically on the details of the metrics themselves that you should be looking at and why.  If we look at the modern expectations on software delivery, it is often about speed. How fast can you get ot the market, deliver a fix, or deploy a new feature? In software delivery, speed without flow is chaos  -

I started writing in my previous blog post  about the importance of metrics and how they provide detailed insight into the development life cycle and identify key areas for improvement in software delivery for teams. Before delving into the different metrics themselves, though, it’s important to look at how we actually gather the data in the first place. After all, there is no way we can gain insight into our delivery if we don’t have access to the data that provides it. How