Developed a proof-of-concept JupyterLab workspace for the uc-cdis/containers repository, integrating a software repository to streamline the management and use of analytic tools within JupyterLab environments. Focused on containerization and DevOps practices, the solution leveraged Python, Bash, and Dockerfile to enable reproducible analytics workflows and reduce onboarding time for new tools. The workspace design supports end-to-end integration, allowing users to efficiently access and deploy analytic software directly from within JupyterLab. This foundational work established a platform for rapid prototyping and collaborative analytics, emphasizing Git-based version control and modular workspace concepts without addressing major bug fixes during the period.