meta data for this page
  •  

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revisionPrevious revision
Next revision		Previous revision
ixc2024:tech:tools:greenframe [2024/05/22 11:20] – rubenhuygensixc2024:tech:tools:greenframe [2024/05/22 15:31] (current) – rubenhuygens
Line 1: Line 1:
-How Does GreenFrame Work?+=== What is GreenFrame and How Does It Work? ===
  
-GreenFrame relies on a scientific model of the energy consumption of a digital system built in collaboration with computer scientists at Loria.+{{:ixc2024:tech:tools:screenshot_2024-05-22_at_15.30.48.png?400|}}
  
-While running the scenario, GreenFrame uses docker stats to collect system metrics (CPU, memory, network and disk I/O, scenario duration) every second from the browser and containers.+**GreenFrame** is a command-line tool designed to estimate the carbon footprint of web applications at every stage of the development process. By integrating GreenFrame into your Continuous Integration workflow, you can monitor "carbon leaks" and enforce a maximum emissions threshold.
  
-It then uses the GreenFrame Model to convert each of these metrics into energy consumption in Watt.hours. GreenFrame sums up the energy of all containers over time, taking into account a theoretical datacenter PUE (set to 1.4, and configurable) for server containers. This energy consumption is then converted into CO2 emissions using a configurable "carbon cost of energy" parameter (set to 442g/kWh by default).+**Key Features:**
  
-GreenFrame repeats the scenario 3 times and computes the average energy consumption and CO2 emissions. It also computes the standard deviation of energy consumption and CO2 emissions to provide a confidence interval.+   - **Scientific Basis:** GreenFrame's energy consumption model was developed in collaboration with computer scientists at Loria. 
 +   - **Data Collection:** During scenario execution, GreenFrame uses Docker stats to collect system metrics (CPU, memory, network, disk I/O, and scenario duration) every second from the browser and containers. 
 +   - **Energy Calculation:** These metrics are converted into energy consumption (in Watt-hours) using the GreenFrame Model. The total energy consumption is calculated by summing the energy of all containers over time, considering a theoretical datacenter PUE (Power Usage Effectiveness) set to 1.4 (configurable). 
 +   - **CO2 Conversion:** The energy consumption is then converted into CO2 emissions using a configurable "carbon cost of energy" parameter, set to 442g/kWh by default. 
 +   - **Repetition for Accuracy:** The scenario is repeated three times to compute the average energy consumption and CO2 emissions, providing a confidence interval with the standard deviation of these values.
  
-For more details about the GreenFrame Model, check this article on the Marmelab blog:+For detailed information on the GreenFrame Model, refer to the article on the Marmelab blog: [[https://marmelab.com/blog/2021/04/08/greenframe-io-website-carbon.html|GreenFrame.io: What is the Carbon Footprint of a Web Page?]]
  
-GreenFrame.io: What is the carbon footprint of a web page?.+=== Factors Influencing the Carbon Footprint ===
  
-Which Factors Influence The Carbon Footprint?+According to our research, the carbon footprint of a web page is influenced by several factors:
  
-Based on our research, the carbon footprint of a web page depends on:+   - **Scenario Duration:** The length of time the scenario runs. 
 +   - **Page Size:** Includes HTML, CSS, JS, images, fonts, etc. 
 +   - **JavaScript Execution:** The amount of JavaScript executed in the browser. 
 +   - **Third-Party Tags:** Ads, analytics, and other external tags. 
 +   - **Page Complexity:** Number of DOM elements, layout changes, etc. 
 +   - **Server Impact:** Server containers usually contribute around 5% to the total carbon footprint.
  
-The duration of the scenario +Optimizing the emissions of a web page can be effectively achieved by employing Web Performance Optimization (WPO) techniques.
-The size of the page (HTML, CSS, JS, images, fonts, etc.) +
-The amount of JS executed on the browser +
-The number of third-party tags (ads, analytics, etc.) +
-The complexity of the page (number of DOM elements, number of layout changes, etc.) +
-Server containers have a low impact on the carbon footprint (around 5% in most cases).+
  
-This means that the lowest hanging fruit for optimizing the emissions of a web page is to use Web Performance Optimization (WPO) techniques.+=== Example Usage === 
 + 
 +To estimate the energy consumption and carbon emissions of a visit to a public web page, use the following GreenFrame command:
  
-=== What is GreenFrame? === 
-GreenFrame is a command-line tool that estimates the carbon footprint of web apps at every stage of the development process. Put it in your Continuous Integration workflow to get warned about "carbon leaks", and force a threshold of maximum emissions. 
  
-=== Example === 
-For instance, to estimate the energy consumption and carbon emissions of a visit to a public web page, call greenframe analyze: 
   $ greenframe analyze https://marmelab.com   $ greenframe analyze https://marmelab.com
   ✅ main scenario completed   ✅ main scenario completed
-  The estimated footprint is 0.038 g eq. co2 ± 1.3% (0.085 Wh).+  The estimated footprint is 0.038 g eq. CO2 ± 1.3% (0.085 Wh). 
 + 
 + 
 +GreenFrame provides a clear and actionable way to measure and reduce the carbon footprint of web applications, promoting more sustainable development practices. 
 + 
 + 
 +=== Links === 
 +   - [[https://github.com/marmelab/greenframe-cli|GitHub]] 
 +   - [[https://greenframe.io|Website]]