The Sched app allows you to build your schedule but is not a substitute for your event registration. You must be registered for KubeCon + CloudNativeCon North America 2024 to participate in the sessions. If you have not registered but would like to join us, please go to the event registration page to purchase a registration.
Please note: This schedule is automatically displayed in Mountain Standard Time (UTC -7). To see the schedule in your preferred timezone, please select from the drop-down menu to the right, above "Filter by Date." The schedule is subject to change and session seating is available on a first-come, first-served basis.
A standout feature of Kubernetes is its sophisticated mechanism for pulling container images from repositories, aligning containers with the appropriate pods, and strategically deploying pods to nodes that meet their resource requirements—such as CPU, GPU, RAM, network, and storage. This process adheres to the defined affinity and anti-affinity specifications between pods and nodes. Despite these capabilities, the challenge of optimally arranging a multitude of workloads, each comprising several pods within a cluster, remains an ongoing endeavor. In our research, we illustrate that a set of YAML files, which detail a workload deployment request, can be systematically transformed into a Binary Integer Linear Programming (BILP) model. Depending on the specific optimization goals, the objective functions of the model can be tailored accordingly. With the imposition of broad conditions, it is feasible to derive an optimal solution that adheres to polynomial time complexity constraints.
