How to Optimize Cloud Deployment for Column Design with Embodied Carbon Calculations

21 April 2023
Capture 11

This article by Murat Melek, PhD, PE, SE, originally appeared on


In this final installment of a four-part series on deploying structural applications to the cloud, we explore ad more advanced implementation by combining Docker images with Lambda Functions.

Kindly remember that the first article introduced the Flask framework, the second delved into Fully Managed Services like AWS Elastic Beanstalk, and the third article investigated the Lambda service through a basic implementation that calculated a column’s axial load carrying capacity. By integrating Docker images with Lambda Functions, we now aim to demonstrate a more complex cloud function deployment while retaining cost-efficiency.

Lambda functions present an optimal solution for deploying efficient Python functions that consist of merely a few lines of code. However, in use cases like the one we will address in this article, deploying functions with multiple dependencies necessitates additional steps. Before delving into the details, it is worth highlighting that this article focuses on AWS services, but comparable offerings are available within the Google Cloud and Microsoft Azure ecosystems, Google Cloud Functions and Azure Functions, respectively.

In this example, we’ll demonstrate the integration of structural steel column design with embodied carbon calculations, a critical aspect for us structural engineers as we increasingly need to provide embodied carbon values and optimize projects for carbon footprint. Unlike the previous article, we’ll use the AWS Lambda service alongside Jared Friedman’s EC3-Python-Wrapper library and Pandas. To streamline the deployment, we’ll utilize a Docker container image for the Lambda function. We’ll build the image, push it to the AWS Elastic Container Registry, develop a Lambda function using the image, and then deploy the function.

Before diving into the process, let’s take a moment to discuss the EC3-Python-Wrapper. This Python wrapper is designed to work seamlessly with the Building Transparency EC3 API. The EC3 tool, a joint effort by Building Transparency and the Carbon Leadership Forum at the University of Washington, equips the construction industry with a comprehensive database of Environmental Product Declarations (EPDs). By leveraging EC3, professionals can effectively compare products and make informed decisions, promoting sustainable building practices and reduced embodied carbon emissions.

Stay updated on our latest insights, news, events, advancements, and successes we’ve achieved with our clients.