During July 2025, Daniel Weineha developed Confidential Compute support for the intel/cluster-management-toolkit repository, focusing on enhancing security and visibility for sensitive Kubernetes workloads. He implemented new YAML-based configuration options and extended the toolkit’s configuration management capabilities to handle confidential compute contexts. Daniel built a parser for confidential containers to enable accurate runtime data collection and policy enforcement, and updated the Intel device plugin parser to recognize confidential workloads. Additionally, he introduced a user interface view for monitoring confidential runtime information, allowing for improved management and visualization. His work addressed the need for scalable, secure configuration management in Kubernetes environments.