Data scientist and container enthusiast Ayse Kaya and her team at Slim.AI analyzed more than 100 of the world’s most popular public container images using open source tools to better understand what developers encounter when running containers in Kubernetes. What they found was a vast, varied, and complex world that gives developers massive opportunities to scale, but also presents risks to both security and productivity. This talk shares the data, visualizations, and insights they generated from their research. Kaya shows the current paradox in software supply chain practices (i.e. taking advantage of abstraction vs. knowing what’s in the software you ship), and that even small, special purpose containers could have thousands of packages, libraries, and licenses, not to mention critical vulnerabilities. Finally, she’ll highlight the current trade-offs teams make between “developer experience” and “production readiness”, and open a discussion about how we can improve as an industry.