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GreenWhisk: Emission-Aware Computing for Serverless Platform

Jayden Serenari, Sreekanth Sreekumar, Kaiwen Zhao, Saurabh Sarkar, Stephen Lee

TL;DR

GreenWhisk is introduced, a carbon-aware serverless computing platform built upon Apache OpenWhisk, operating in two modes - grid-connected and grid-isolated - addressing intermittency challenges arising from renewables and the grid’s carbon footprint and develops carbon-aware load balancing algorithms that leverage energy and carbon information to reduce the carbon footprint.

Abstract

Serverless computing is an emerging cloud computing abstraction wherein the cloud platform transparently manages all resources, including explicitly provisioning resources and geographical load balancing when the demand for service spikes. Users provide code as functions, and the cloud platform runs these functions handling all aspects of function execution. While prior work has primarily focused on optimizing performance, this paper focuses on reducing the carbon footprint of these systems making variations in grid carbon intensity and intermittency from renewables transparent to the user. We introduce GreenWhisk, a carbon-aware serverless computing platform built upon Apache OpenWhisk, operating in two modes - grid-connected and grid-isolated - addressing intermittency challenges arising from renewables and the grid's carbon footprint. Moreover, we develop carbon-aware load balancing algorithms that leverage energy and carbon information to reduce the carbon footprint. Our evaluation results show that GreenWhisk can easily incorporate carbon-aware algorithms, thereby reducing the carbon footprint of functions without significantly impacting the performance of function execution. In doing so, our system design enables the integration of new carbon-aware strategies into a serverless computing platform.

GreenWhisk: Emission-Aware Computing for Serverless Platform

TL;DR

GreenWhisk is introduced, a carbon-aware serverless computing platform built upon Apache OpenWhisk, operating in two modes - grid-connected and grid-isolated - addressing intermittency challenges arising from renewables and the grid’s carbon footprint and develops carbon-aware load balancing algorithms that leverage energy and carbon information to reduce the carbon footprint.

Abstract

Serverless computing is an emerging cloud computing abstraction wherein the cloud platform transparently manages all resources, including explicitly provisioning resources and geographical load balancing when the demand for service spikes. Users provide code as functions, and the cloud platform runs these functions handling all aspects of function execution. While prior work has primarily focused on optimizing performance, this paper focuses on reducing the carbon footprint of these systems making variations in grid carbon intensity and intermittency from renewables transparent to the user. We introduce GreenWhisk, a carbon-aware serverless computing platform built upon Apache OpenWhisk, operating in two modes - grid-connected and grid-isolated - addressing intermittency challenges arising from renewables and the grid's carbon footprint. Moreover, we develop carbon-aware load balancing algorithms that leverage energy and carbon information to reduce the carbon footprint. Our evaluation results show that GreenWhisk can easily incorporate carbon-aware algorithms, thereby reducing the carbon footprint of functions without significantly impacting the performance of function execution. In doing so, our system design enables the integration of new carbon-aware strategies into a serverless computing platform.
Paper Structure (28 sections, 4 equations, 13 figures, 3 tables)

This paper contains 28 sections, 4 equations, 13 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Background
  3. GreenWhisk Design
  4. System Architecture
  5. Energy Interface
  6. Energy Profile
  7. Retry Queue
  8. Controller
  9. Carbon-aware Load Balancer
  10. Implementation
  11. Evaluation
  12. Hardware Setup
  13. Datasets
  14. Data Center Location Selection
  15. Baseline Algorithms
  16. ...and 13 more sections

Figures (13)

  • Figure 1: OpenWhisk workflow.
  • Figure 2: Variations in carbon intensity across different US cities.
  • Figure 3: GreenWhisk system architecture. The system can operate on either grid-connected or grid-isolated mode.
  • Figure 4: GreenWhisk Raspberry PI FaaS cluster.
  • Figure 5: Emissions avoided by different baseline algorithms.
  • ...and 8 more figures