KubeCon + CloudNativeCon North America 2024

We present an open-source solution for the efficient management of resources and scheduling strategies in K8s. Our solution constructs workload-specific resource profiles based on their historical utilization patterns. This approach ensures that workloads receive adequate resources while optimizing overall resource utilization. To accomplish this objective, we employ a custom resource Service Profiling Description (SPD), facilitating a direct correlation between workloads and their resource usages, such as deployments and stateful sets etc. Resource utilization metrics, including CPU, disk I/O, and network I/O, are meticulously collected and aggregated. These usage indicators play a pivotal role in informing the scheduler's decisions regarding workloads allocation. This solution has been deployed within large-scale K8s clusters, addressing diverse workload demands, ranging from those requiring dedicated NUMA nodes to those capable of resource sharing among themselves.