Cloud Carbon Footprint provides a way for organizations to measure, monitor, and reduce their carbon emissions from the cloud. It supports connecting to multiple cloud providers, allowing you to get a full picture of your cloud emissions.
Cloud Carbon Footprint (CCF) is an open-source tool that uses cloud APIs to provide visualizations of estimated carbon emissions based on usage across AWS, GCP and Azure. Our team has successfully used the tool with several organizations, including energy technology companies, retailers, digital service providers and companies that use AI. Cloud platform providers realize that it’s important to help their customers understand the carbon impact of using their services, so they’ve begun to build similar functionality themselves. Because CCF is cloud agnostic, it allows users to view energy usage and carbon emissions for multiple cloud providers in one place, while translating carbon footprints into real-world impact such as flights or trees planted. In recent releases, CCF has begun to include Google Cloud and AWS-sourced optimisation recommendations alongside potential energy and CO2 savings, as well as to support more cloud instance types such as GPU instances.
Cloud Carbon Footprint works by taking the cloud provider usage data, converting it into energy, and then taking into account the power usage effectiveness of the cloud provider’s data centers and the carbon intensity of the region where the data center pulls power from.
The code has been written using domain driven design, to allow for easy extension and customization. With the core estimation logic, API, front-end dashboard, and CLI separated, it is possible to fit it to user needs, for instance using the core logic or API within an existing application, or displaying the dashboard within an existing dev portal.
There are three different ways to get started with Cloud Carbon Footprint:
- Create a standalone app using the command line interface
- Clone the Cloud Carbon Footprint repository
- Run Cloud Carbon Footprint in an ephemeral workspace with a hosted development environment provider
You can make a standalone app that is easily customizable to meet your demands for the best approach to keep up to date with the project. This approach creates a lighter standalone app by using the @cloud-carbon-footprint packages as npm dependencies.
Forking and cloning the repository is the best way to contribute to the project. Cloning the project will include all of the @cloud-carbon-footprint packages for local development and configuration. This path offers the option to create Pull Requests and to stay up to date with the latest changes.
Classifying Usage Types
We must first categorise a row of usage as either Compute, SSD Storage, HDD Storage, Networking, or Memory in order to estimate the energy and carbon emissions for a certain amount of cloud provider usage. It’s also possible that the usage row is unsupported, in which case the application ignores these rows, or that it’s unknown, which we can analyse or reclassify here. The corresponding use amount is used by the application to estimate energy consumption and carbon emissions after the usage row has been classified.
Our team has successfully used the tool with several organizations, including energy technology companies, retailers, digital service providers and companies that use AI. Cloud platform providers realize that it’s important to help their customers understand the carbon impact of using their services, so they’ve begun to build similar functionality themselves. Because CCF is cloud agnostic, it allows users to view energy usage and carbon emissions for multiple cloud providers in one place, while translating carbon footprints into real-world impact such as flights or trees planted.
In recent releases, CCF has begun to include Google Cloud and AWS-sourced optimization recommendations alongside potential energy and CO2 savings, as well as to support more cloud instance types such as GPU instances.
Stakeholders increasingly expect businesses to account for the environmental externalities of their decisions, as evidenced by the rise of environmental, social and corporate governance (ESG) investing and employee activism around climate change. Migrating to the cloud offers the potential for more efficient energy usage — the cloud providers have much more scale to justify investment in green energy sources and R&D — but the downside of software abstractions for cloud users is that those abstractions also hide the energy impact as the actual data centers are hidden from view and financed by another company. Cloud Carbon Footprint, a new open-source tool, takes advantage of cloud APIs to provide visualizations of estimated carbon emissions based on usage across AWS, GCP and Azure. It uses heuristics like Etsy’s Cloud Jewels to estimate energy usage and public data sources to convert energy usage into emissions based on the carbon intensity of the cloud region’s underlying energy grid (GCP publishes this data already). The tool’s dashboards act as information radiators, allowing decision makers to modify setups to cut costs and emissions at the same time. The linkage of cloud regions to carbon intensity of the underlying grid provides a nudge to switch dirty workloads to regions with greener energy sources.
The Need for Sustainable Cloud Adoption
The value of the global cloud computing market is estimated to be $945 million by 2025. Gartner says that cloud computing will be “pervasive” by the same milestone year. At the same time, the World Meteorological Organization reports that “the world is poised to break a crucial heat barrier by 2025”.
Sustainability and ecological conservation are needed to sustain life on earth, and that includes sustainability in cloud computing. Given the ubiquity of cloud computing, and the present high carbon consumption by the sector, sustainability in cloud adoption is a key motivator for all major cloud services providers, and should drive investment decisions by IT teams around the world as well.
Making Strides in Cloud Sustainability
Knowing their significant electricity requirements, hyperscale data centre operators such as Amazon Web Services (AWS), GCP and Azure have set and are making great efforts to meet sustainability goals. They are on track to using 100% renewable energy for their operations.
AWS considers sustainability in the cloud a major goal, focusing primarily on creating “energy reduction and efficiency across all components of a workload”. AWS provides a variety of tools using which the cloud user can make their workloads more efficient.
The user can select the most efficient programming language, adopting modern algorithms, using efficient data storage and infrastructure, and using less high-powered hardware, to minimize the impact of each cloud workload deployed.
You can also use the AWS Cloud to run workloads specifically designed to support broader sustainability goals. “For example, you can use a machine learning service like Amazon Monitron to detect abnormal behavior in industrial machinery. Using this detection data, you can conduct preventive maintenance to reduce the risk of environmental incidents caused by unexpected equipment failures and ensure that the machinery continues to operate at peak efficiency.”
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