Sustainability Research the Cloud Native Way

The presentation discusses the use of cloud-native patterns to improve cloud efficiency in sustainable architecture, with a focus on Project Kepler and its integration with Kubernetes ecosystems.

• Cloud-native sustainability infrastructure can improve cloud efficiency in sustainable architecture
• Project Kepler uses eBPF programs and system libraries to measure energy, performance, and resource usage
• Kepler enables energy-relevant observability and sustainable management on clusters
• Kepler can be used for research topics like energy-efficient workload scheduling and energy-aware autoscaling
• The presentation includes a case study of a Kepler integration for building an advanced vertical autoscaler to improve energy performance objectives of Kubernetes applications

The presenter uses the example of a condominium to explain the concept of fairness in a shared offering system, and how it applies to the methodology used in presenting accurate metrics for cloud-native sustainability infrastructure.

Do you want to help combat climate change? Are you interested in sustainability research? Then join our open systems for Cloud-native sustainability infrastructure. We present the research opportunities of using Cloud-native patterns, observing, optimizing, and executing, to improve Cloud efficiency in sustainable architecture. Core to this architecture is Project Kepler (Kubernetes-based Efficient Power Level Exporter) and its integration with Kubernetes ecosystems. By leveraging eBPF programs and other system libraries, Kepler probes the full spectrum of energy, performance, and resource measurements to enable energy-relevant observability and further empower advanced sustainable management on clusters. Kepler is an open system for exciting research topics like energy-efficient workload scheduling, energy-aware autoscaling, and frequency tuning. In this session, a sample Kepler integration is case-studied to help researchers build their advanced vertical autoscaler to improve the energy performance objectives of the Kubernetes applications.