The recent decade has seen a rise in community resilience modeling, including a quest to model infrastructure resilience (its exposure, damage, and restoration) under extreme events. These efforts entail measuring, visualizing, and probing alternatives to support mitigation, recovery, and resilience-enhancing interventions. However, the practice demands developing different input sub-models, considering various layers of uncertainty, and integrating these for the final assessment. In this project, we present how the resources of the DesignSafe Cyberinfrastructure (DesignSafe-CI) can support such efforts. We present different tools that can be leveraged from DesignSafe directly or through its interoperability with other platforms, such as the Interdependent Networked Community Resilience Modeling Environment (IN-CORE). We present illustrative examples of how to leverage publicly available data in DesignSafe-CI and models within the IN-CORE platform to create an infrastructure resilience assessment pipeline. These examples are developed and analyzed using JupyterLab in DesignSafe. Furthermore, we present how JupyterLab HPC in DesignSafe-CI enhances the modeling and testing capabilities as the analysis of larger infrastructure systems (e.g., detailed transportation networks) becomes feasible. While the illustrative example uses earthquakes as the hazard type, the leveraged tools, platforms, and shared codes can be adapted to multiple hazards. This project is created to share the material presented on December 11 (2024) in the DesignSafe Webinar "Resilience Assessment of Community Infrastructure: Leveraging HPC Resources at DesignSafe-CI and Interoperability with IN-CORE". You can find the recording of the webinar at the following link: https://youtu.be/Bdb8s4Rc4h4?feature=shared