Modern software development rarely starts from a blank page. Instead, applications are assembled from a vast ecosystem of frameworks, libraries, and open-source components that accelerate development and enable teams to build complex systems quickly. In many cases, the majority of an application’s functionality comes not from code written internally, but from external dependencies - and lately, AI. This shift has dramatically improved developer productivity, but it has also i

Modern software delivery has transformed how quickly organizations can build and release software. Continuous integration and continuous delivery pipelines enable teams to deploy updates frequently, respond rapidly to customer needs, and iterate faster than ever before. However, this speed can expose a major weakness in traditional security models. Historically, security checks were performed as a final gate before release. Security specialists would review code, run vulnerab

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

When it comes to application security , compliance can often feel like a roadblock: a slow, manual process that lags behind the pace of...