Demand-driven provisioning of Kubernetes-like resources in OSG

TL;DR

This paper presents a demand-driven provisioning system for Kubernetes-like resources in the OSG, enabling efficient resource utilization across multiple providers including Lancium, through a simple and automated mechanism.

Contribution

It introduces a novel demand-driven provisioner for Kubernetes resources that extends existing backfill containers, supporting multiple providers with minimal complexity.

Findings

Successfully provisioned resources from NRP and Lancium using the new system

Automated matchmaking improves resource utilization efficiency

The simple logic allows easy extension and low-cost deployment

Abstract

The OSG-operated Open Science Pool is an HTCondor-based virtual cluster that aggregates resources from compute clusters provided by several organizations. Most of the resources are not owned by OSG, so demand-based dynamic provisioning is important for maximizing usage without incurring excessive waste. OSG has long relied on GlideinWMS for most of its resource provisioning needs but is limited to resources that provide a Grid-compliant Compute Entrypoint. To work around this limitation, the OSG Software Team has developed a glidein container that resource providers could use to directly contribute to the OSPool. The problem of that approach is that it is not demand-driven, relegating it to backfill scenarios only. To address this limitation, a demand-driven direct provisioner of Kubernetes resources has been developed and successfully used on the NRP. The setup still relies on the OSG-maintained backfill container image but automates the provisioning matchmaking and successive requests. That provisioner has also been extended to support Lancium, a green computing cloud provider with a Kubernetes-like proprietary interface. The provisioner logic has been intentionally kept very simple, making this extension a low-cost project. Both NRP and Lancium resources have been provisioned exclusively using this mechanism for many months.