AWS Architecture Blog

How to select a Region for your workload based on sustainability goals

The Amazon Web Services (AWS) Cloud is a constantly expanding network of Regions and points of presence (PoP), with a global network infrastructure linking them together. The choice of Regions for your workload significantly affects your workload KPIs, including performance, cost, and carbon footprint.

The Well-Architected Framework’s sustainability pillar offers design principles and best practices that you can use to meet sustainability goals for your AWS workloads. It recommends choosing Regions for your workload based on both your business requirements and sustainability goals. In this blog, we explain how to select an appropriate AWS Region for your workload. This process includes two key steps:

  • Assess and shortlist potential Regions for your workload based on your business requirements.
  • Choose Regions near Amazon renewable energy projects and Region(s) where the grid has a lower published carbon intensity.

To demonstrate this two-step process, let’s assume we have a web application that must be deployed in the AWS Cloud to support end users in the UK and Sweden. Also, let’s assume there is no local regulation that binds the data residency to a specific location. Let’s select a Region for this workload based on guidance in the sustainability pillar of AWS Well-Architected Framework.

Shortlist potential Regions for your workload

Let’s follow the best practice on Region selection in the sustainability pillar of AWS Well-Architected Framework. The first step is to assess and shortlist potential Regions for your workload based on your business requirements.

In What to Consider when Selecting a Region for your Workloads, there are four key business factors to consider when evaluating and shortlisting each AWS Region for a workload:

  • Latency
  • Cost
  • Services and features
  • Compliance

To shortlist your potential Regions:

  • Confirm that these Regions are compliant, based on your local regulations.
  • Use the AWS Regional Services Lists to check if the Regions have the services and features you need to run your workload.
  • Calculate the cost of the workload on each Region using the AWS Pricing Calculator.
  • Test the network latency between your end user locations and each AWS Region.

At this point, you should have a list of AWS Regions. For this sample workload, let’s assume only Europe (London) and Europe (Stockholm) Regions are shortlisted. They can address the requirements for latency, cost, and features for our use case.

Choose Regions for your workload

After shortlisting the potential Regions, the next step is to choose Regions for your workload. Choose Regions near Amazon renewable energy projects or Regions where the grid has a lower published carbon intensity. To understand this step, you need to first understand the Greenhouse Gas (GHG) Protocol to track emissions.

Based on the GHG Protocol, there are two methods to track emissions from electricity production: market-based and location-based. Companies may choose one of these methods based on their relevant sustainability guidelines to track and compare their year-to-year emissions. Amazon uses the market-based model to report our emissions.

AWS Region(s) selection based on market-based method

With the market-based method, emissions are calculated based on the electricity that businesses have chosen to purchase. For example, the business could decide to contract and purchase electricity produced by renewable energy sources like solar and wind.

Amazon’s goal is to power our operations with 100% renewable energy by 2025 – five years ahead of our original 2030 target. We contract for renewable power from utility-scale wind and solar projects that add clean energy to the grid. These new renewable projects support hundreds of jobs and hundreds of millions of dollars investment in local communities. Find more details about our work around the globe. We support these grids through the purchase of environmental attributes, like Renewable Energy Certificates (RECs) and Guarantees of Origin (GoO), in line with our renewable energy methodology. As a result, we have a number of Regions listed that are powered by more than 95% renewable energy on the Amazon sustainability website.

Choose one of these Regions to help you power your workload with more renewable energy and reduce your carbon footprint. For the sample workload we’re using as our example, both the Europe (London) and Europe (Stockholm) Regions are in this list. They are powered by over 95% renewable energy based on the market-based emission method.

AWS Regions selection based on location-based method 

The location-based method considers the average emissions intensity of the energy grids where consumption takes place. As a result, wherever the organization conducts business, it assesses emissions from the local electricity system. You can use the emissions intensity of the energy grids through a trusted data source to assess Regions for your workload.

Let’s look how we can use Electricity Maps data to select a Region for our sample workload:

1. Go to Electricity Maps (see Figure 1)

2. Search for South Central Sweden zone to get carbon intensity of electricity consumed for Europe (Stockholm) Region (display aggregated data on yearly basis)

Carbon intensity of electricity for South Central Sweden

Figure 1. Carbon intensity of electricity for South Central Sweden

3. Search for Great Britain to get carbon intensity of electricity consumed for Europe (London) Region (display aggregated data on yearly basis)

Carbon intensity of electricity for Great Britain

Figure 2. Carbon intensity of electricity for Great Britain

As you can determine from Figure 2, the Europe (Stockholm) Region has a lower carbon intensity of electricity consumed compared to the Europe (London) Region.

For our sample workload, we have selected the Europe (Stockholm) Region due to latency, cost, features, and compliance. It also provides 95% renewable energy using the market-based method, and low grid carbon intensity with the location-based method.

Conclusion

In this blog, we explained the process for selecting an appropriate AWS Region for your workload based on both business requirements and sustainability goals.

Further reading:

Sam Mokhtari

Sam Mokhtari

Dr. Sam Mokhtari is leading the sustainability pillar of AWS Well-Architected framework. His main area of depth is data and analytics, and he has published more than 30 influential articles in this field.

Isha Dua

Isha Dua

Isha Dua is a Senior Solutions Architect based in San Francisco Bay Area. She helps AWS Enterprise customers grow, by understanding their goals and challenges. She offers guidance to companies on architecting their applications in a cloud native manner, while making sure they are resilient and scalable. She’s passionate about machine learning technologies and Environmental Sustainability.

Amit Khanal

Amit Khanal

Amit Khanal is a Senior Solutions Architect based in the San Francisco Bay Area. He works with AWS customers to understand their business objectives and helps them achieve desired outcomes using AWS services. He is passionate about container technologies and environmental sustainability.