In this paper and demo, we will present and showcase the Data Release Infrastructure we have developed and deploy using state of the art technologies like Kuberentes, Jupyter, Celery and Python to allow scientist to access, explore and analyze the catalogs and images generated by the Dark Energy Survey project, which is a scientific community-based project (with over 500 scientists) with the goal of understanding the origin of dark matter and dark energy by surveying the night sky and observe millions of galaxies and stars for a 5 year period. This Infrastructure includes novel data visualizations and exploration tools to enable scientific discovery. I will review the deployment and development process, the scientific output and feedback as well as the main features of our gateway.
