I plan to present evolved architecture of the facility, such as the integration of advanced services (ML, data-delivery & data caching, and others) and to make them available to end users of the facility.
In the talk, I am also planning to highlight the composability of modern cyberinfrastructure tools used in coffee-casa design. These services also feature transparent access for user workflows to GPUs available at a facility via inference servers while using Kubernetes as enabling technology.
Coffea-casa analysis facility is one of the components of the Analysis Grand Challenge (cc @alexander-held ). This allows the Python packages from AGC pipeline to be tested at scale at the facility even on the stage of release candidates (applying DevOps strategy), making sure we could offer early adopters a reliable development environment for their analysis code.