Reduce your cloud carbon footprint with new Active Assist recommendations

Last year, we analyzed the aggregate data from all customers across Google Cloud, and found over 600,000 gross kgCO2e in seemingly idle projects that could be cleaned up or reclaimed — which would have a similar impact to planting almost 10,000 trees1. Today, we’re making it easy for you to identify if any of those idle workloads are yours, with new Active Assist sustainability recommendations.  Active Assist is a part of Google Cloud’s AIOps solution that uses data, intelligence, and machine learning to reduce cloud complexity and administrative toil. Under the Active Assist portfolio, we have products and tools like Policy Intelligence, Network Intelligence Center, Predictive Autoscaler, and a collection of Recommendations for various Google Cloud services — all focused on helping you achieve your operational goals. Today, we are broadening the scope of Active Assist to help you achieve your sustainability targets and reduce the carbon footprint of your workloads.The carbon emissions associated with your cloud infrastructure can be a big part of your overall environmental footprint. Choosing to run on Google Cloud is a great first step — we’ve matched the energy used by our data centers with 100% renewable energy since 2017, and are committed to running our operations on carbon-free energy 24/7 by 2030. But once you’re running on Google Cloud, if you want to reduce the gross carbon emissions of your workload you can take action to optimize your usage.Assessing the gross carbon impact of unattended projectsYou can now estimate the gross carbon emissions you’ll save by removing these idle projects with Active Assist Unattended Project Recommender, which provides rich utilization insights for all the projects in your organization, and uses machine learning to identify ones that are idle and most likely unattended. The data points Active Assist surfaces as a part of its utilization insights now include the carbonFootprintDailyKgCO2 field, which allows you to estimate carbon emissions associated with any given project. Recommendations also estimate the impact of removing an idle project in terms of kilograms of CO2 reduced per month. The capability is available via the Recommender API, Recommendation Hub, the Carbon Footprint dashboard, and BigQuery export of recommendations, making it easy for you to integrate with your company’s existing tools and workflows.Example unattended project in Recommendation HubIntroducing the Carbon Sense suiteIncreasing the sustainability of digital applications and infrastructure is a priority for 90% of global IT leaders2, and we’ll be continuing to invest across a number of product areas in Google Cloud, including AIOps features like Active Assist’s recommendations, to help you make progress towards your sustainability goals. To make it easy for you to find and consume these new features, we’re bundling our existing and future product work into the Carbon Sense suite — a collection of features that makes it easy to accurately report your carbon emissions, and reduce them. Active Assist joins products like Carbon Footprint, which provides you with the ability to understand and measure the gross carbon emissions of your Google Cloud usage, and our low-carbon signals, which help users choose cleaner regions to run their workloads, in the Carbon Sense suite. Stay tuned for more updates on Carbon Sense in the coming months. Getting started with sustainability recommendationsTo get started with Active Assist sustainability recommendations, check the Carbon Footprint dashboard and Recommendation Hub to review projects that may be idle and assess the carbon emissions associated with them. See recommendations in Google Cloud Console.To view the recommendations, you will need IAM permissions for Unattended Project Recommender itself and permissions to view resources in a given organization.You can also automatically export the recommendations from your Organization to BigQuery and then investigate any idle projects with DataStudio or Looker. Or, you can use Connected Sheets to use Google Workspace Sheets to interact with the data stored in BigQuery without having to write SQL queries.As with any other Recommender, you can choose to opt out of data processing for your organization or your projects at any time by disabling the appropriate data groups in the Transparency & Control tab under Privacy & Security settings.We hope you use Unattended Project Recommender to reduce the carbon footprint associated with your idle cloud resources, and can’t wait to hear your feedback and thoughts about this feature! Please feel free to reach us at active-assist-feedback@google.com. We also invite you to sign up for our Active Assist Trusted Tester Group if you would like to get early access to new features as they are developed.1. https://www.epa.gov/energy/greenhouse-gas-equivalencies-calculator2. https://inthecloud.withgoogle.com/it-leaders-research-21/sustainability-dl-cd.html
Quelle: Google Cloud Platform