TY - GEN
T1 - A low carbon kubernetes scheduler
AU - James, Aled
AU - Schien, Daniel
PY - 2019/6/17
Y1 - 2019/6/17
N2 - A major source of global greenhouse gas emissions is the burning of fossil fuels for the generation of electricity. The portion of electricity generated from fossil fuel varies across regions, and within a region with demand for electricity and the availability of renewable energy sources. Cloud providers operate data centres in locations around the planet. And certain kind of server computation can tolerate migrating between data centres. In this paper we describe the design and implementation of a low carbon scheduling policy for the open-source Kubernetes container orchestrator. We apply this scheduler in a form of demand side management by migrating consumption of electric energy to countries with the lowest carbon intensity of electricity. The primary contributions of this text are (i) the scheduler’s design, which provides a generic model for optimising workload placement in regions with the lowest carbon intensity (ii) an evaluation of its performance in a case study with a major public cloud provider (iii) an implementation of a demand side management solution that consumes electricity where, instead of when, grid carbon intensity is lowest.
AB - A major source of global greenhouse gas emissions is the burning of fossil fuels for the generation of electricity. The portion of electricity generated from fossil fuel varies across regions, and within a region with demand for electricity and the availability of renewable energy sources. Cloud providers operate data centres in locations around the planet. And certain kind of server computation can tolerate migrating between data centres. In this paper we describe the design and implementation of a low carbon scheduling policy for the open-source Kubernetes container orchestrator. We apply this scheduler in a form of demand side management by migrating consumption of electric energy to countries with the lowest carbon intensity of electricity. The primary contributions of this text are (i) the scheduler’s design, which provides a generic model for optimising workload placement in regions with the lowest carbon intensity (ii) an evaluation of its performance in a case study with a major public cloud provider (iii) an implementation of a demand side management solution that consumes electricity where, instead of when, grid carbon intensity is lowest.
UR - http://www.scopus.com/inward/record.url?scp=85067802264&partnerID=8YFLogxK
M3 - Conference Contribution (Conference Proceeding)
AN - SCOPUS:85067802264
VL - 2382
T3 - CEUR Workshop Proceedings
BT - 6th International Conference on ICT for Sustainability, ICT4S 2019
PB - CEUR-WS
T2 - 6th International Conference on ICT for Sustainability, ICT4S 2019
Y2 - 10 June 2019 through 14 June 2019
ER -