In this article, I'm going to write about the Cloud Carbon Footprint tool. In short, it's an application that estimates energy usage and carbon emissions of various cloud providers.

We will explore the following:

• What this tool is?
• How it works?
• How the application looks like?
• How it differs from tools provided by other cloud platforms?
• How to run it locally?

What is the Cloud Carbon Footprint tool?

This application helps you see all your energy usage estimates and carbon emissions in one place. If you have resources running in multiple cloud providers, this tool can be of help. It shows all the estimates in one place. There is no need to jump from one cloud provider service to another. All in one place.

How it works?

In a nutshell, it pulls usage data from cloud providers and calculates the estimated energy and GHG emissions. Estimated energy is expressed in Watt-Hours, and GHG emissions in metric tons CO2e. If you need a reminder on what CO2e is, check out my earlier article.

How much carbon does my server emit?

Have you ever wondered how much carbon your server, laptop, or virtual machine use? Well, I did, and in this article, I present you with the findings.

Wondering ChimpMarjan Bugarinović

The estimations are calculated in the following way. (Copy from the documentation alert!)

Total CO2e = operational emissions + embodied Emissions

Where:

Operational emissions = (Cloud provider service usage) x (Cloud energy conversion factors [kWh]) x (Cloud provider Power Usage Effectiveness (PUE)) x (grid emissions factors [metric tons CO2e])

And:

Embodied Emissions = estimated metric tons CO2e emissions from the manufacturing of datacenter servers, for compute usage

The documentation of the application is great! Check out the longer version of the methodology on the link below.

Methodology | Cloud Carbon Footprint

Summary

Cloud Carbon Footprint

How the application looks like?

The Application Web UI is pretty neat! The image below shows the overview of it.

To check it out yourself, and play around, visit the application demo on the link below.

Cloud Carbon Footprint

Carbon Carbon Footprint

How it differs from tools provided by other cloud platforms?

The application currently supports AWS, Google Cloud and Microsoft Azure. It provides the estimated values. Those estimates are not meant as a replacement for data from cloud providers. More like a complement.

They also provide integration with Electricity Maps API. For real-time carbon intensity emissions factors instead of the default values. To find out more about Electricity Maps API, check out my article below.

Exploring the Green APIs

Have you ever wondered, is there an API you can call and get the carbon emission data of a specific location? It would be cool to have something like this, so we can make our applications carbon-aware, wouldn’t it? Look no further! In this article I’m exploring just that!

Wondering ChimpMarjan Bugarinović

How to run it locally?

Let's get our hands dirty now, and run the application locally. You can run it by executing yarn scripts or using docker compose. I chose the latter approach, because I'm lazy. And also, running yarn would require for me to install it, and also install node.js. I opted for an easier approach. Yeah, right.

In this demo, I'm going to configure the CCF to run with the GCP platform. I already prepared some resources running there, so let's give it a try.

I first started with cloning the application repository, as recommended in the documentation.

git clone --branch latest https://github.com/cloud-carbon-footprint/cloud-carbon-footprint.git
cd cloud-carbon-footprint

After that, I went through the guide on connecting the GCP data to the application. In a nutshell, I did the following:

1. Create a GCP service account with roles/bigquery.dataViewer and roles/bigquery.jobUser permissions
2. Set up a Google Cloud billing data to export to BigQuery
3. Create an .env file based on the env.template in the repository
4. Created docker secrets
5. Updated the docker-compose.yml file
6. Run the docker compose up from the root of the repo.

The following link provides you thorough instructions on how to complete most of the steps above. Heads up, it also links to a lot of GCP instruction documents to set up service account and BigQuery.

Google Cloud (GCP) | Cloud Carbon Footprint

Account Setup

Cloud Carbon Footprint

Here is the overview of the .env file I've been using.

# GCP

# Variables needed for the Billing Data (Holistic) approach with GCP:
GCP_USE_BILLING_DATA=true
# Optionally set this variable if you want to include or not include from estimation request - defaults to true.
GCP_INCLUDE_ESTIMATES=true
GCP_USE_CARBON_FREE_ENERGY_PERCENTAGE=true
GOOGLE_APPLICATION_CREDENTIALS=/location/of/service-account-keys.json
GCP_BIG_QUERY_TABLE=your-project-id.data-set-name.table
GCP_BILLING_PROJECT_ID=your-project-id
GCP_BILLING_PROJECT_NAME="Your Project Name"

# Variables to help configure average vcpu's to get more accurate date from GKE and Cloud Composer
GCP_VCPUS_PER_GKE_CLUSTER=10
GCP_VCPUS_PER_CLOUD_COMPOSER_ENVIRONMENT=10

# Variables needed for the Cloud Usage API (Higher Accuracy) approach with GCP:
GCP_PROJECTS=[{"id":"your-project-id","name":"Your Project Name"}]

GCP_RESOURCE_TAG_NAMES=[] # ["tag:ise-api-enabler-access, label:goog-composer-location, project:twproject"]


# Additional Configurations

# To enable the use of the Electricity Maps API for carbon intensity data, set the following variable to your token:
ELECTRICITY_MAPS_TOKEN=api-token

As you can see, I've also tried to enable the integration with Electricity Maps API by adding the token.

Heads up! You will need to update the .env file per your settings. Make sure that you copy the whole value for GCP_BIG_QUERY_TABLE from GCP BigQuery table. I had some issues with not providing the correct name, so running of the application failed.

After that, I wanted to generate docker secrets. In the documentation, they recommend running the yarn create-docker-secrets. Since I don't have yarn installed, I've checked the package.json file and saw that the script is calling the create-docker-secrets.sh script. I found it in the packages/api/ directory, and run it.

Heads up! You will also need to put your .env file in this (packages/api) directory!

./create-docker-secrets.sh

This script generated all necessary secrets in the $HOME/.docker/secrets directory. Here is the output of the directory.

$ ls -lha ~/.docker/secrets/
total 56K
drwxrwxr-x 2 user group 4.0K Feb 16 09:23 .
drwxrwxr-x 3 user group 4.0K Feb 16 08:36 ..
-rw-rw-r-- 1 user group   14 Feb 16 08:48 ELECTRICITY_MAPS_TOKEN
-rw-rw-r-- 1 user group   89 Feb 16 09:23 GCP_BIG_QUERY_TABLE
-rw-rw-r-- 1 user group   20 Feb 16 08:48 GCP_BILLING_PROJECT_ID
-rw-rw-r-- 1 user group   19 Feb 16 08:48 GCP_BILLING_PROJECT_NAME
-rw-rw-r-- 1 user group    5 Feb 16 08:48 GCP_INCLUDE_ESTIMATES
-rw-rw-r-- 1 user group   57 Feb 16 08:48 GCP_PROJECTS
-rw-rw-r-- 1 user group   85 Feb 16 08:48 GCP_RESOURCE_TAG_NAMES
-rw-rw-r-- 1 user group    5 Feb 16 08:48 GCP_USE_BILLING_DATA
-rw-rw-r-- 1 user group    5 Feb 16 08:48 GCP_USE_CARBON_FREE_ENERGY_PERCENTAGE
-rw-rw-r-- 1 user group    3 Feb 16 08:48 GCP_VCPUS_PER_CLOUD_COMPOSER_ENVIRONMENT
-rw-rw-r-- 1 user group    3 Feb 16 08:48 GCP_VCPUS_PER_GKE_CLUSTER
-rw-rw-r-- 1 user group   54 Feb 16 08:48 GOOGLE_APPLICATION_CREDENTIALS

The final edit was to the docker-compose.yml file. I needed to remove all the values that I was not using, so the docker compose setup completes. Here is the overview of the file I've used.

version: '3.9'

services:
  client:
    image: cloudcarbonfootprint/client:latest
    ports:
      - '80:80'
    volumes:
      - ./docker/nginx.conf:/etc/nginx/nginx.conf
    depends_on:
      - api
  api:
    image: cloudcarbonfootprint/api:latest
    ports:
      - '4000:4000'
    volumes:
      - $HOME/.config/gcloud/service-account-keys.json:/root/.config/gcloud/service-account-keys.json
    secrets:
      - GCP_BIG_QUERY_TABLE
      - GCP_BILLING_PROJECT_ID
      - GCP_BILLING_PROJECT_NAME
      - ELECTRICITY_MAPS_TOKEN
    environment:
      # set the CACHE_MODE to MONGODB to use MongoDB
      - CACHE_MODE=LOCAL
      - GCP_USE_BILLING_DATA=true
      - GCP_USE_CARBON_FREE_ENERGY_PERCENTAGE=true
      - GOOGLE_APPLICATION_CREDENTIALS=/root/.config/gcloud/service-account-keys.json
      - GCP_BIG_QUERY_TABLE=/run/secrets/GOOGLE_APPLICATION_CREDENTIALS
      - GCP_BILLING_PROJECT_ID=/run/secrets/GCP_BIG_QUERY_TABLE
      - GCP_BILLING_PROJECT_NAME=/run/secrets/GCP_BILLING_PROJECT_ID
secrets:
  GCP_BIG_QUERY_TABLE:
    file: ~/.docker/secrets/GCP_BIG_QUERY_TABLE
  GCP_BILLING_PROJECT_ID:
    file: ~/.docker/secrets/GCP_BILLING_PROJECT_ID
  GCP_BILLING_PROJECT_NAME:
    file: ~/.docker/secrets/GCP_BILLING_PROJECT_NAME
  ELECTRICITY_MAPS_TOKEN:
    file: ~/.docker/secrets/ELECTRICITY_MAPS_TOKEN

After I had everything of the above set and complete, I run the following command.

docker compose up

This created two containers, one for the application, and the other for the API.

$ docker ps
CONTAINER ID   IMAGE                                COMMAND                  CREATED       STATUS          PORTS                                       NAMES
22aca61d4487   cloudcarbonfootprint/client:latest   "/docker-entrypoint.…"   2 hours ago   Up 29 minutes   0.0.0.0:80->80/tcp, :::80->80/tcp           cloud-carbon-footprint-client-1
04624e02bab2   cloudcarbonfootprint/api:latest      "docker-entrypoint.s…"   2 hours ago   Up 29 minutes   0.0.0.0:4000->4000/tcp, :::4000->4000/tcp   cloud-carbon-footprint-api-1

Opening the localhost on my local browser, I got the following screen.

As you can see, the data is available! You (in this case I), can go through the dashboards and further check where are the emissions coming from. Pretty nice!

Notes on the side! When I configured everything, I needed to wait for some time to get the data. This might be due to BigQuery setup on GCP. Additionally, I've used a trial token for Electricity Maps API. It has only a couple of regions available. This made the application timeout a couple of times. In the end, I needed to remove the token, so the application could start. I got plenty of warnings, similar to below.

...
api-1     | 2024-02-17T08:03:47.476Z [BillingExportTable] warn: Electricity Maps zone data was not found for us-west1. Using default emissions factors. 
api-1     | 2024-02-17T08:03:47.567Z [BillingExportTable] warn: Electricity Maps zone data was not found for us-west1. Using default emissions factors. 
api-1     | 2024-02-17T08:03:47.802Z [BillingExportTable] warn: Electricity Maps zone data was not found for southamerica-west1. Using default emissions factors. 
api-1     | 2024-02-17T08:03:47.903Z [BillingExportTable] warn: Electricity Maps zone data was not found for southamerica-west1. Using default emissions factors. 
api-1     | 2024-02-17T08:03:48.059Z [BillingExportTable] warn: Electricity Maps zone data was not found for europe-west3. Using default emissions factors.
...

Let's now compare the values with the ones from the GCP Carbon Footprint tool. Check out the image below.

From first look, it seems that the values from the CCF are more fine-grained than those on the GCP. CCF also can connect to Electricity Maps API, which shows live emissions factors. I'm not sure if GCP shows that. Probably not.

Anyhow, the CCF is not meant to replace the tools from cloud providers, it complements them.

Summary

Even though I had some challenges with the setup, I find it quite nice and useful. I really like the Emissions Equivalencies panel (I named it). The one on the bottom left. It puts emissions from your resources into different contexts - flights, phones, and how many trees could sequester the carbon emissions from resources. It might need some improvements (talking from the deployment side). Nevertheless, I am looking forward to future releases.

The application itself is small, not requiring a lot of resources, sort of easy to set up and run... And the most important thing - it shows you necessary data in one place! It's definitely a good starting point.

Check out the GitHub repository for more information.

GitHub - cloud-carbon-footprint/cloud-carbon-footprint: Cloud Carbon Footprint is a tool to estimate energy use (kilowatt-hours) and carbon emissions (metric tons CO2e) from public cloud usage

Cloud Carbon Footprint is a tool to estimate energy use (kilowatt-hours) and carbon emissions (metric tons CO2e) from public cloud usage - cloud-carbon-footprint/cloud-carbon-footprint

GitHubcloud-carbon-footprint

Now, in an ideal world, cloud providers would expose more comprehensive data about resource energy usage and GHG emissions. Not just only scope 1 and 2, but also scope 3. Better yet, we wouldn't be in this place to start with.

However, since we're not living in an ideal world, this tool can help us improve the reporting and knowledge about our resource emissions.

Let me know the in the comments below, what do you think about the tool and the article itself!

Fatigue, noun
2a: weariness or exhaustion from labor, exertion, or stress.

Hm, interesting. Yes, it's somewhat like that. But, maybe not the same. Then I read along.

2c: a state or attitude of indifference or apathy brought on by overexposure (as to a repeated series of similar events or appeals).

There we are. This is how I would describe the feeling I experienced from time to time. Especially at the end of the last year. Even writing this article felt a bit apathetic in the beginning... I wonder what Merriam-Webster has to say about the word apathetic?

Now, this is not a lesson in English dictionary, and I am, by no means, a person to give you one. This is a story of the state of indifference or apathy brought on by overexposure. I couldn't help myself, sorry. Overexposure to sustainability-related content. The state I fell into a couple of times in the past. The state I'll fall into in future, probably.

This is a story for all of you who feel, or have felt, the same. Or at least somewhat similar. It also has a selfish goal - it is a lesson for my future self on how not to fall into that trap again.

How it all started?

Imagine you're in nature, surrounded by greenery. Trees, plants, meadows... Everything is perfect! In the background you can hear the soft sound of birds chirping, wind blowing. It's idyllic. You enjoy it...

This is how I felt in the beginning, with all my brain juices flowing. Exploring the possibilities on how to make our planet better, simpler, more sustainable.

And I read along. Days on end, even weeks. Not all the time, but whenever I had some moment to spare. All those news, e-mails, how-to guides, videos, posts here and there...

In my head, it all started to change. Trees were cut down, plants were drying, meadows covered with concrete buildings... All you can hear in the background is the endless hum of the traffic with the sound of an emergency vehicle from time to time...

This was the feeling I ended up with. By continuously immersing myself in the topic. Reading about the solutions, but somehow getting more and more aware of the problems. News weren't great, either. Both on a local and global level.

It started as an optimistic quest wrapped in green. And it ended as a pessimistic reality wrapped in dark gray.

The feeling itself wasn't immediate. It was the result of an ongoing content consumption. The process of getting into fatigue wrapped in dark gray was slow. I wasn't aware of it for quite a while. Up until I saw how I felt reading about the consequences of global warming some time ago. It was the feeling you can explain with the simple word - meh! Which was, if we consult Merriam-Webster dictionary, again, to the point.

apathetic, indifferent.

How to cope?

When something is wrong in my life, I feel different, or somehow strange, I turn to books. They're my first line of defence. I tried reading a couple of them, but nothing felt right. I felt disconnected from each of them I took.

After that, I turned to my second line of defence - something to listen to or watch. Podcasts, conference talks, documentaries... Result was the same - nada.

All those things like: Five easy steps to recover from fatigue; Do this, and you'll be better; Check this great advice on how to X and Y... It all reminded me of a book called - McMindfulness: How Mindfulness Became the New Capitalist Spirituality, by Ronald Purser. Just a note, I didn't read it, yet, but I found the title somehow convenient.

Then, I took a step back. I was trying to fix the feeling of overexposure with another one. That same overexposure, but to other type of content. Like fighting fire with fire. Which in some cases makes sense. However, in this case, it didn't. My focus and attention needed a rest. My brain needed a rest.

So, I just stopped. Stopped checking all the news. Stopped reading all those newsletters, blogs, articles... Listening all those podcasts. Yes, even The Huberman Lab.

Instead of push-based, I took the pull-based approach. I felt that information was getting pushed to me all the time. Via e-mails, notifications, pop-ups, and what-nots... In a pull-based approach, you control when you get the information. When and how you want to get the information.

Now, is there an app for that? Well, yes, sort of. It's actually a functionality that's been there all the time.

All apps were designed to shoot dopamine in your brain with all those pop-ups and notifications. Most of them not even relevant or necessary. Yes, I'm looking at you, LinkedIn! Now, the thing that you can do is just to turn off all those notifications. All applications allow that. Or the system you're using allows it. In that way, you can control how you get the information. Simple as that.

If you think you need to be online all the time, that is also okay. I hope you can manage it. I can't. Let me tell you this, and I'm aware it's a boomer-alert, I think if something is dead-urgent, people will always call. Either by phone or some application of choice. I tend to leave the call notifications on. For the apps I use the most frequently at least.

And that's it. That is how I manage. Somehow I manage.

So, what are some results? Well, at first, it was a bit strange. A couple of times I caught myself reaching for a phone and looking for some new thing, notification, e-mail, anything... Just to feel the excitement. Then, that desire started to slowly fade away. I often see myself leaving the phone unchecked for quite some time. And yes, when it was urgent, people called.

This approach helps me sort out the plethora of information I'm bombarded with every day. And see that it's not everything so dark gray and pessimistic...

Now I need to go, I heard my phone buzzing.

It linked to the research paper titled Frugal Computing - On the need for low-carbon and sustainable computing and the path towards zero-carbon computing. My thought process was the following - Hm, this seems interesting, but what the hell is frugal?

After a short research (one search query), I found out that frugal actually means economical, not wasteful, wise in expenditure of resources. Since I'm not a native English speaker, I felt a small sense of accomplishment after learning a new word.

The Frugal Computing

All jokes aside, the title of the paper was now making way more sense to me than in the beginning. So I decided to have a look, and find out more. I've opened the paper, and read the abstract.

The current emissions from computing are almost 4% of the world total. This is already more than emissions from the airline industry and are projected to rise steeply over the next two decades. By 2040 emissions from computing alone will account for more than half of the emissions budget to keep global warming below 1.5°C. Consequently, this growth in computing emissions is unsustainable. The emissions from production of computing devices exceed the emissions from operating them, so even if devices are more energy efficient producing more of them will make the emissions problem worse. Therefore we must extend the useful life of our computing devices.
As a society we need to start treating computational resources as finite and precious, to be utilised only when necessary, and as effectively as possible. We need frugal computing: achieving our aims with less energy and material.

Great! - I thought. There is a paper that I can turn to when I need to convince myself and others about the importance of economical use of computational resources. And yes, I'm aware that this is coming from a person who has continued to think in the well-known sysadmin's way - Sure, we can add more CPU or Memory to your server, machine, VM, pod, container...

But, the important question here is - do we actually need that much of CPU or Memory? Probably not.

About the author

The author of the paper is Wim Vanderbauwhede, a professor from the University of Glasgow. He's the lead of the Low Carbon and Sustainable Computing activity at the School of Computing Science at the University. You can find more about him on the link below.

University of Glasgow - Schools - School of Computing Science - Our staff - Dr Wim A Vanderbauwhede

Dr Wim A VanderbauwhedeUKRI Net Zero Digital Research Infrastructure Scoping Project

If you are on Mastodon, you can also check his profile there.

WimⓂ️ (@wim_v12e@merveilles.town)

1.9K Posts, 197 Following, 334 Followers · λ🐫, -Ofun probably a Luddite we need frugal computing

Merveilles

Aaaand, he also has a great blog!

Musings of an Accidental Computing Scientist

Wim Vanderbauwhede

Into the paper

This person knows what he's writing about, I thought. Unlike some of us (I mean me, yes). So, I continued reading the paper. In the following text, I'll go through each section and write down what I learned and how I understand it. I hope it helps!

What are computational resources?

In the first section, the author gives an explanation of what computational resources are. He uses a simple example.

... when you perform a web search on your phone or participate in a video conference on your laptop, the computational resources involved are those for production and running of your phone or laptop, the mobile network or WiFi you are connected to, the fixed network it connects to, the data centres that perform the search or video delivery operations.

There is no more to be added here. It's all summed in a nice and a comprehensive way. So let's go to the next part.

Are they infinite?

The second section is about the fact that computational resources are finite.

We tend to see the computational resources as infinite. We can always have more servers, storage, VMs... New, and more powerful laptop, smartphone, this new smartwatch... The last one was personal. When will it end?

Well, it turns out that, first - the energy usage of these devices will grow. And second - the resources used to create these devices and infrastructure are finite. So, it should end sooner rather than later.

The author sums the section with the following.

.. as a society we need to start treating computational resources as finite and precious, to be utilised only when necessary, and as frugally as possible. And as computing scientists, we need to ensure that computing has the lowest possible energy consumption. And we should achieve this with the currently available technologies because the lifetimes of compute devices needs to be extended dramatically.

I would like to call this “frugal computing”: achieving the same results for less energy by being more frugal with our computing resources.

So, the term frugal computing was born.

Why so serious?

The third section is going into details about why this is a problem and why we need frugal computing.

Meeting the climate targets. As stated in the paper - we cannot count on renewables to eliminate CO2 emissions from electricity in time to meet the climate targets. We also need to reduce our energy consumption.

Emissions from consumption of computational resources. Research shows that the emissions only from using devices will grow. From 3%-3.5% in 2020 to 10%-14% by 2040. In other words - the emissions of using will increase 3x or 4x times. This is a problem because by 2040 these emissions will equate to 5 GtCO2e. The target for the world total emissions from all sources by 2040 is 13 GtCO2e.

Emissions from production of computational resources. Yet another thing we don't think about.

Okay, new model of the phone is out, I need to have it! (Even though I used this model for only a couple of months...)

Well, emissions from producing them are actually way bigger than those of using them. For laptops and similar, production, distribution, and disposal is 52% of the total. The total being emission from both usage and production. For smartphones, that number is 72%, which is even bigger! And for servers is 20%.

We can fix all this by increasing the life span of the devices we use. Simple as that, isn't it?

Total emissions cost from computing. When we add things together, they don't look good. Based on the above, emissions from both consumption and production by 2040 will be 10 GtCO2e. And remember that the target is still 13 GtCO2e.

The main carbon cost of the resources is their production and the use of the mobile network. We must extend their useful life very considerably and reduce network utilisation.

How we can achieve computational frugality?

The fourth section is about a vision on how we can achieve that. To put it simple:

• use devices for longer time,
• support those devices for longer time (maintenance, spare parts...)
• incentivise the long-term support and usage (with taxes and policies).

Challenges ahead

The fifth section is about research challenges to the vision presented earlier.

There are numerous challenges in various aspects: cloud computing, ultra-HD video & VR/AR, IoT, mobile devices, AI... How we approach each aspect will determine the ending result.

Where to next?

This section is about research directions. Where we can go so we contribute to the vision stated above.

• Systems must be as energy-efficient and long-lived as possible.
• Sustainable systems need to be data-driven.
• Human-computer interfaces should bring awareness to users. Also nudge them towards more sustainable practices.
• Programming languages need to be aware of the full-system energy usage.
• Algorithms should focus on minimising energy consumption.
• Compilers need to compile for minimal energy consumption.

Conclusion

Whenever I hear something like less is more, I remind myself of a joke - Minimalism is just something made up by Big Small™ to sell more less. It always brings a smile to my face.

Joke aside, the way forward to reducing emissions from computing is by using less energy and less materials. And this is a fact!

Here is the link to the research paper. I hope you will find it as useful as I did.

Frugal Computing -- On the need for low-carbon and sustainable computing and the path towards zero-carbon computing

The current emissions from computing are almost 4% of the world total. This is already more than emissions from the airline industry and are projected to rise steeply over the next two decades. By 2040 emissions from computing alone will account for more than half of the emissions budget to keep global warming below 1.5$^\circ$C. Consequently, this growth in computing emissions is unsustainable. The emissions from production of computing devices exceed the emissions from operating them, so even if devices are more energy efficient producing more of them will make the emissions problem worse. Therefore we must extend the useful life of our computing devices. As a society we need to start treating computational resources as finite and precious, to be utilised only when necessary, and as effectively as possible. We need frugal computing: achieving our aims with less energy and material.

arXiv.orgWim Vanderbauwhede

Let me know in the comments below what do you think about the article. How do you find my comments to the research article presented? Is my analysis/explanation of the sections understandable?

Thank you and see you in the next article!

It's been a full calendar year of writing! That's almost two years in total! I've started these writings on the end of January last year. And, as you may already know, it's cool to have a review of the year, so that is my plan with the last post of the year.

Disclaimer, it's not going to be like Spotify Wrapped, or what not, so don't expect much. I will reflect on the things I've written this year. What, how, and why. I'll also mention the things that inspired me, gave me ideas, and were wind at my back, so to say.

So, let's get started!

Writings

Throughout the year, I've written about various topics. I was still in my exploratory phase, so I've started with couple of articles about Kubernetes. I've written the guide on how to get started with Kubernetes, ways to deploy it, and Kubernetes Ingress. How did that got in the list? Well, looking back now, I didn't understood how Kubernetes Ingress works, so I wanted to write about it. You might've discovered already, but the things I don't know is usually what I write about here. The one to point out from this list is the guide on where to start with Kubernetes.

Kubernetes - where to start?

You heard about Kubernetes but are not sure what it is? You have dabbled in it but you are still not sure how it works? You tried to find out about it yourself, but found the material overwhelming?

Wondering ChimpMarjan Bugarinović

Next in line were articles about learning and growth. These are the topics I go back to quite often. I like learning new stuff, and exploring ways to grow myself. I believe that writing helps me grow, hence the articles on various topics. Two that I would like to point out are about journaling and life-long learning, linked below.

Everyday Epiphanies: The Benefits of Keeping a Daily Journal

Some time ago I read a line in an article that said something like this - instead of opening your phone and social media first thing in the morning, try journaling instead. Try asking yourself some questions like - what are my goals for today, what did I do yesterday,

Wondering ChimpMarjan Bugarinović

Learning to Learn

The thing we often forget when thinking of learning is that we are not officially thought how to learn. When we start school, we don’t usually go through different learning processes, how to approach math, biology, history, or any other class. At least this wasn’t a thing that we did.

Wondering ChimpMarjan Bugarinović

I also wrote about climbing, so (I) you won't forget my hobby that is more than a hobby. There, I've touched one of the lessons I learned (and still learning) from climbing - patience!

Lessons from climbing I’m applying in life - patience

As I embarked on my journey as a rock climber, little did I know that beyond the physical challenges and adrenaline rushes, there lay a profound lesson in patience. The vertical world became my classroom, and each ascent taught me the art of embracing patience in the face of obstacles.

Wondering ChimpMarjan Bugarinović

Now that I look back, middle of the year was my patience-awareness period. I saw how I'm impatient, and wanted to do something about it. It's an everyday battle!

The topic I found the most interesting this year, and the one I will explore further is sustainability. I feel that by writing about this topic, I can do something that will be good for our planet. To learn, teach, and act.

As you may or may not know, the climate change is not just a today's problem, but the problem that will impact our future. The COP28 didn't go well, but that should not stop us from learning about new ways to help, and act. The articles I want to mention here are, well, all of them! If you have any time to spare during the holidays (and we all know we do), check them out!

sustainability - Wondering Chimp

Wondering Chimp

Inspirations

This year, one of my articles was mentioned in the Green Software Foundation newsletter! The article shared is about Carbon Awareness. You can find it linked below.

Exploring Carbon Awareness: No, It’s Not a Trendy Mindfulness Practice

Have you ever heard about carbon awareness? What it is and how can be implemented? In this article, we’ll cover just that, and also bring you an overall understanding of the concept and what it means for the environment.

Wondering ChimpMarjan Bugarinović

And here is the screenshot where they mention my article under Latest Resources and Perspectives. I was THRILLED!

During this year, I started exploring Mastodon. I liked the idea of it, and got active there. I would highly recommend you to check it out, explore, and see for yourself! I think of this network as a social network for people. There are no ads, you follow what you want, see what you follow... Below is the link to my profile there.

Marjan (@wonderingchimp@fosstodon.org)

391 Posts, 100 Following, 26 Followers · Rock climber and a wannabe writer working in Tech. I also read a lot, like to learn new things, and currently learning to play go. 🌍Born at 354ppm

Fosstodon

One of my tut (post on Mastodon) was an inspiration for an article! It was about AI prompts and how we can start using them in a sensible way.

This tut was mentioned in an article from Friedemann Ebelt about AI and new AI legislation in the EU. I'm sharing below the original article in German.

KI und Klima – was kann der AI Act (vielleicht)? - Campact Blog

Wird der AI Act, wenn er denn kommt, dafür sorgen, dass künstliche Intelligenz in der EU klimagerechter wird?

Campact BlogFriedemann Ebelt

Again, I was THRILLED!

Ideas

Here, I want to mention the things that impacted me the most - the books and articles I've read, podcasts I've listened... Sort of like the link dump of the things.

Podcasts

List of podcast episodes I've listened to is quite extensive, so I won't go into too much details. Here are the three podcast episodes that I've listened, re-listened, and re-re-listened.

How to Enhance Performance & Learning by Applying a Growth Mindset - Huberman Lab

In this episode, I discuss how to build and apply a growth mindset — the practice of self-rewarding and focusing on learning and skill development through effort — to improve learning and performance.

Home

A great episode on the science behind the growth mindset, and action points we all can take towards applying it!

We Answer Your Questions!

On this episode of Environment Variables, host Chris Adams is joined by Asim Hussain as they dive into a mailbag session, bringing you the most burning unanswered questions from the recent live virtual event on World Environment Day that was hosted by the Green Software Foundation on June 5 2023. Asim and Chris will tackle your questions on the environmental impact of AI computation, the challenges of location shifting, the importance of low-carbon modes, and how to shift the tech mindset from “more is more” (Jevons Paradox). Chock-full of stories about projects implementing green software practices, and valuable resources, listen now to have your thirst for curiosity quenched!

We Answer Your Questions!Green Software Foundation

One of the many episodes of Green Variables podcast. This one is a session where hosts answer questions and doubts about sustainability.

REMIX | EFFORT: How to Try Harder

Climbers Bill Ramsey, Jonathan Siegrist, Jason Kehl, Hazel Findlay, Troy Fauteux, and others weigh in on how we as athletes can refocus our effort.

Power Company ClimbingKris Hampton

Last but not the least is the one about applying effort. It is about applying effort in climbing, but, I use it as a firecracker when I feel down about everything. It helps a lot!

Books

Somewhat like the podcast episodes, this year I've read quite a bunch of books. I want to mention only three (two plus a book series) that affected me the most.

Greenlights by Matthew McConaughey

#1 NEW YORK TIMES BESTSELLER - From the Academy Award(R)-winning actor, an unconventional memoir…

The StoryGraphMatthew McConaughey

Full of simple, hard, and honest truths about people, world, and life in general. I recommend it.

Life and Death in Shanghai by Nien Cheng

This is a first-hand account of China’s cultural revolution. Nien Cheng, an anglophile and fluent…

The StoryGraphNien Cheng

A great book about how to approach life when everything and everyone is aginst you. How to live through and persist!

Mistborn - Wikipedia

Wikimedia Foundation, Inc.Contributors to Wikimedia projects

This I've read in almost one breath, Era One, at least. Great books full of ups and downs, tragic deaths, and so forth. Even though the ending was a bit abstract for my taste, I find the Era One of the series great! We'll see how I feel about the Era Two in next years.

Articles

We live in the information age, thus, content is abundant. Keeping the list as short as possible, below are the three articles that affected me the most.

Overchoice and How to Avoid it

Five Heuristics to Help You Decide

The PrismGurwinder

A practical guide on what to do when you have to make some choice. It's full of great advices!

How to Remember What You Read

The benefits of reading are negated if you forget remember what you read. This article discusses a tested system to increase retention. Learn how to use active reading to remember more from books.

Farnam StreetRosie

How to actually read books and remember the most from them. Spoiler alert - note-taking!

A few words on taking notes

As we are about to start the planning meetings for 2024 at AWS, I’ve been thinking a lot about how I take notes.

All Things DistributedWerner Vogels

This article motivated me to review my note-taking techniques. In the end, got me back to the handwritten notes.

Year in numbers

Now, to wrap up the story with some numbers. These are the following:

• 22 articles written (23, if we include this one).
• Somewhat similar number of posts on LinkedIn, where I shared the articles.
• More than 200 hours spent in exploring, reading, preparing, and writting. Then editing, and re-writting these articles.*

* 1 article x min 5h to write.

• More than 68000 post impressions just on LinkedIn!

My goals when I started all this were:

1. Learn ✅
2. Write ✅
3. Stay curious ✅
4. Publish every two weeks ✅❌

Reflecting to the goals, I've learned a lot! And I think the articles I've written so far can be a sort of a measure for that. And for the second goal as well, now that I'm mentioning. The range of topics I've covered this year can easily show me being curious. The fourth one is partially complete. Throughout the year, I wasn't always able to post once in a fortnight. I missed the schedule on couple of ocassions.

Continuing on, I'm keeping the above goals the same. The only thing I want to change is my approach to them. Write and learn in a more active way, and stay curious along the way.

Thank you for staying this long with me and see you next year!

It's been a while. A full month since my last e-mail (article) that, hopefully, didn't end in your spam.

For quite some time, I was trying the idea of doing what I preach and move my website to be carbon-aware. In this article I want to dive in what I've learned so far and what is the progress of turning this website carbon aware.

A bit on Carbon Awareness

Let us remind ourselves first. To put it simple, Carbon awareness is - do more when the energy is coming from renewable sources. Do less when it comes from non-renewable sources. I first wrote about the basics some time ago. To check them out, follow the link below.

Exploring Carbon Awareness: No, It’s Not a Trendy Mindfulness Practice

Have you ever heard about carbon awareness? What it is and how can be implemented? In this article, we’ll cover just that, and also bring you an overall understanding of the concept and what it means for the environment.

Wondering ChimpMarjan Bugarinović

Making a website carbon aware means that it can serve more or less high-intensive content based on the user's location. If the carbon intensity of the users' location is high, don't load images and videos, for example. Let the users decide.

This practice is called demand shaping. You shape your demand based on the carbon intensity.

Another example of it could be that different AI engines prompt users the following, before running each query:

Hey, do you know that this query will consume THIS MUCH litres of water and produce THIS amount of CO2eq. Do you still want to run it?"

Could this be a possible feature request for all those GPTs developers? What do you think?

Sorry, I went a bit off the topic. The initial inspiration for making the website carbon-aware came from the Branch Magazine.

Branch Magazine Issue 6: Green Screen

Branch is an online magazine written by and for people who dream of a sustainable and just internet. Issue 6 out now: Green Screen.

Branch

First steps

As in almost everything in life, I first searched the Internet. Since I'm hosting my website on Ghost, my use-case was quite specific.

After a couple of dead-ends, I stumbled upon an awesome blog from Fershad Irani. A web sustainability consultant working with Green Web Foundation. Following is the link to his website.

Web Sustainability Consultant

Hey, I’m Fershad. I am a web sustainability consultant working with the Green Web Foundation towards a fossil free internet by 2030.

Fershad Irani

The articles that provided more info and inspired action were the following.

This website is carbon aware

Information about how I have made this website climate aware, and how it changes depending on how clean/dirty the electricity grid is.

Fershad Irani

The above one is a general info about the website and the fact that it is carbon aware.

Making this website carbon aware

Building carbon awareness into products is an important strategy to in the challenge to develop a more sustainable future. In this post, I cover how I used Cloudflare Workers and real-time data to make this website carbon aware.

Fershad Digital LTDFershad Irani

This one is a step-by-step guide to how the site was made carbon aware. With examples, links to libraries and different configuration options. Excellent!

Okay, I thought, this is great. It will be easy!

Consider here the fact that I don't know much about web development. But, I was eager to learn.

Contacting the support

Then I decided to contact the support. See their opinion on this. I've written them an e-mail about the idea, where I got it from, and so on. And sent it.

Not long after came the response. It was quite nice and comprehensive. They explained to me why it wouldn't be so easy, or even possible. With examples of challenges.

I was a bit disappointed. Not by their response, but the fact that it wouldn't be an easy job. I'm so satisfied with the Ghost provider, and I didn't want to move from there. Still don't.

Then I stopped looking. It was like somebody burst my idea bubble.

Personal doubts

I'm not sure why, but when I'm hyped about the idea, I tend to lose the sense of time and place. And sometimes, I become impatient. Like in that song from Queen - I want it all, and I want it now! And when I see it's not so easy, or even possible, well, then I lose that initial hype.

This doesn't happen often, but it happened here. And it lasted for quite some time. Not sure why. Who knows, maybe it's because the end of year is upon us?

Doing what I can

Finally, I got to my senses, and decided to take some action. I cannot change the website easily, okay, let's go with what I can do. At the moment, at least.

First, I've decided to change the theme of the website to be more text-based, rather than full of images.

This was easy, but creating a landing page is still a challenge. I hope I finished it before publishing the article.

Next, I went through all my articles so far, and removed unnecessary feature images. I was never a fan of them. Even though, they've added a certain professionality and eye-catchiness to my website. Now, my website looks rather plain, and I don't mind it at all. I hope you don't mind.

I'm not stopping here, but I'm slowing down. First I'll try to create a theme in Ghost with a minimalistic, text-based, approach. Then, I'll see if something else/new comes up.

Let me know in the comments, what do you think about this. Also, do let me know what do you think about my text-based approach.

See you in the next, once-a-fortnight, article!

This week, we're exploring Green APIs. APIs that show you carbon intensity data you can use in your code. And based on that data create some logic. For example:

• If users' location has high carbon intensity, don't load carbon intensive content on a webpage. Carbon intensive content - videos or images, for example.
• If carbon intensity in a region is high, you can automatically shift your workloads into a green one.
• Schedule batch jobs of your application when the carbon intensity is lower.

In this article, we'll go through two of them. First, I'll write a short overview about each. Then, I'll create a small Go application we can use to call these APIs. And last we'll see the methodologies used within both of them.

That's the plan. Will I be able to stick to it? Let's dive and see.

Electricity Maps

First in line is the Electricity Maps. They provide electricity data for more than 160 regions. Founded in 2016 with a goal to get us to a decarbonized electricity system. You can find more about them on their website linked below.

Electricity Maps | Reduce carbon emissions with actionable electricity data

Electricity Maps provides actionable electricity carbon data. We help companies effectively reduce their emissions, while differentiating their offerings.

© Copyright 2022 Electricity Maps ApS - Univate, Njalsgade 76, 2300 Copenhagen | CVR: DK-39101211. All Rights Reserved.

They are the people behind the electricity map I have mentioned in the previous posts. And they are doing a great job!

Let's see what do they offer. Checking their website, they have free and paid plans. Based on the option you choose, different features are available. They offer free-tier API calls (up to 100,000), and paid options. I am going to look into the free-tier.

On the type of data they are offering, you have two options:

1. Use APIs to make applications carbon-aware
2. Granular carbon accounting

With the first option, they provide data based on which you can create logic in your app. You call the API, you get a JSON response. The second option focuses on carbon accounting and creating reports on the scope 2 emissions. Data includes consumption-based emissions factors from both direct operations and life cycle analysis (LCA) for the years 2021-2022.

Here, we'll use the first option, and the Free subscription for that option. I want to play around and test the APIs available in the free tier. Maybe I'll use it in future to make my website carbon-aware. Who knows...

Testing out the APIs

After selecting the Free option, I easily log in by providing e-mail, name, last name, password... You know the drill. When I filled this information in, I am redirected to their API Portal. The screenshot of the portal is below.

And this portal has everything you need! It has extensive documentation, list of available APIs with example code snippets. You can use those snippets in your app rather easy. Which as it turns out, will be quite useful for this article!

Below is the example application written in Go. It shows you latest carbon intensity per specified zone. I've specified RS zone for the country where I live in. I've also omitted the auth-token which is a way to authenticate with the API.

package main

import (
  "fmt"
  "io/ioutil"
  "net/http"
  "encoding/json"
  "bytes"
)

func main() {

  url := "https://api-access.electricitymaps.com/free-tier/carbon-intensity/latest?zone=RS"

  req, _ := http.NewRequest("GET", url, nil)

  // here you need to change YOUR_AUTH_TOKEN with the token from your registered profile
  req.Header.Add("auth-token", "YOUR_AUTH_TOKEN")

  res, _ := http.DefaultClient.Do(req)
  defer res.Body.Close()

  body, _ := ioutil.ReadAll(res.Body)

  fmt.Println(jsonPrettyPrint(string(body)))

}

// jsonPrettyPrint() takes the JSON string and formats it to a readable format
func jsonPrettyPrint(in string) string {
  var out bytes.Buffer
  err := json.Indent(&out, []byte(in), "", "\t")
  if err != nil {
      return in
  }
  return out.String()
}

The output data is shown below.

{
	"zone": "RS",
	"carbonIntensity": 510,
	"datetime": "2023-11-10T07:00:00.000Z",
	"updatedAt": "2023-11-10T06:45:48.660Z",
	"createdAt": "2023-11-07T07:47:23.027Z",
	"emissionFactorType": "lifecycle",
	"isEstimated": true,
	"estimationMethod": "TIME_SLICER_AVERAGE"
}

Here you can see the time when I've queried the API, and the carbon intensity. The value is in grams of CO2 equivalence per kWh, or gCO2eq/kWh. You also have the emission factor type, and the estimation method. Both of which we'll explain in the next section.

I was able to create this example in a couple of minutes after logging. Without using any AI prompts. Just by following examples and instructions clearly written and stated on the portal. That is how it should be!

Methodology

Now, what about the data provided by the Electricity Maps, where is it from? How do they calculate the carbon intensity?

The data comes from a variety of public data sources. Those sources can be transmission system operators, balancing entities, or market operators. The complete list of data sources shows where the data is sourced from.

If I go a step further and check out the data source for Serbia, it shows the ENTSOE. I don't know what this means, so I'll dig deeper.

The ENTSOE stands for European Network of Transmission System Operators for Electricity. It represents 39 electricity TSOs (Transmission System Operators) from 35 countries across Europe. It is established to promote closer cooperation of the TSOs across Europe. To support the implementation of EU energy policy, and achieve Europe's energy and climate policy objectives.

This organization publishes an Implementation Guide for the transparent data extraction process.

Thanks, Wikipedia!

The data the Electricity Maps gets is then processed and formatted with different parsers in a uniform way. The formatted data is then saved in the db and processed using the flow-tracing algorithm.

The flow-tracing algorithm follows the flow (whether it’s power, data, or something else) through a system to understand how it operates or to identify specific characteristics. It’s like a roadmap that shows you how to get from point A to point B, and all the stops you make along the way.

The ENTSOE.py parser, used for Serbia and other ENTSOE members, can be found on the link below. All parsers are open-source, and the contribution is more than welcome! Pretty neat, isn't it!

electricitymaps-contrib/parsers/ENTSOE.py at master · electricitymaps/electricitymaps-contrib

A real-time visualisation of the CO2 emissions of electricity consumption - electricitymaps/electricitymaps-contrib

GitHubelectricitymaps

Calculation of carbon intensity is done by multiplying the power production from each source by the corresponding emission factors. The emission factors depend on different parameters. These parameters can be production source, the region and many others. Data is calculated with a number of regional and global emission factors. The table below shows the default Life-cycle emission factors.

Some part of the methodology used is published on the Electricity Maps GitHub Wiki, and their Blog. Feel free to check them out for more information and reference.

WattTime API

The second API that I'm going to explore is the WattTime. It is a nonprofit that offers technology solutions that help in achieving emissions reductions. The nonprofit was founded in 2014, first tried on hackathon in 2013! Similar to the Electricity Maps, WattTime provides the electricity data for many regions across the world. To find out more, check out their website linked below.

(https://www.watttime.org/).

The WattTime has, as well, an excellent documentation of the API.

By default, they offer a free plan, which is nice. But, it's a rather limited one. You can access and query only one region/zone. All others are forbidden. Like Electricity Maps, they offer paid plans, but, the price is not published. You need to e-mail them for paid plans.

Anyhow, the registration and the login process is done via API. They offer comprehensive Python scripts/snippets on how to register, and perform login. I'm going to use Golang in my use-case. And I'll register for the free plan.

Testing out the API

First, let's register by running the below code.

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "log"
    "net/http"
)

func main() {

    // add your USERNAME and PASSWORD
    values := map[string]string{
      "username": "USERNAME",
      "password": "PASSWORD",
      "email": "wondering.chimp@tuta.io",
      "org": "Wondering Chimp",
    }

    json_data, err := json.Marshal(values)

    if err != nil {
        log.Fatal(err)
    }

    url := "https://api2.watttime.org/v2/register"
    resp, err := http.Post(url, "application/json",
        bytes.NewBuffer(json_data))

    if err != nil {
        log.Fatal(err)
    }

    defer resp.Body.Close()

    var res map[string]interface{}

    json.NewDecoder(resp.Body).Decode(&res)

    fmt.Println(res)
}

After that, you should get the somewhat similar response to the below one.

{
  "user": "USERNAME",
  "ok": "User created"
}

Next, let's get a token and get the grid emission data for the only one available region (CAISO_NORTH).

package main

import (
  "fmt"
  "io/ioutil"
  "net/http"
  "net/url"
  "strings"
  "bytes"
  "encoding/json"
)

func main() {
  loginURL := "https://api2.watttime.org/v2/login"
  req, _ := http.NewRequest("GET", loginURL, nil)
  // you will need to change this line with your USERNAME and PASSWORD
  req.SetBasicAuth("USERNAME", "PASSWORD")
 
  resp, _ := http.DefaultClient.Do(req)
  defer resp.Body.Close()
  body, _ := ioutil.ReadAll(resp.Body)
  token := strings.Split(string(body), ":")[1]
  token = strings.TrimRight(strings.TrimLeft(token, "\""), "\"}\n")
 
  dataURL := "https://api2.watttime.org/v2/data"
  req, _ = http.NewRequest("GET", dataURL, nil)
  req.Header.Add("Authorization", "Bearer "+token)
 
  params := url.Values{}
  params.Add("ba", "CAISO_NORTH")
  params.Add("starttime", "2023-11-05T20:30:00-0800")
  params.Add("endtime", "2023-11-05T22:30:00-0800")
  req.URL.RawQuery = params.Encode()
 
  resp, _ = http.DefaultClient.Do(req)
  defer resp.Body.Close()
  body, _ = ioutil.ReadAll(resp.Body)
 
  fmt.Println(jsonPrettyPrint(string(body)))
}

func jsonPrettyPrint(in string) string {
  var out bytes.Buffer
  err := json.Indent(&out, []byte(in), "", "\t")
  if err != nil {
      return in
  }
  return out.String()
}

You should get the response similar to the below one.

[
...
        {
                "point_time": "2023-11-06T04:50:00.000Z",
                "value": 950.0,
                "frequency": 300,
                "market": "RTM",
                "ba": "CAISO_NORTH",
                "datatype": "MOER",
                "version": "3.2"
        },
        {
                "point_time": "2023-11-06T04:45:00.000Z",
                "value": 950.0,
                "frequency": 300,
                "market": "RTM",
                "ba": "CAISO_NORTH",
                "datatype": "MOER",
                "version": "3.2"
        },
        {
                "point_time": "2023-11-06T04:40:00.000Z",
                "value": 954.0,
                "frequency": 300,
                "market": "RTM",
                "ba": "CAISO_NORTH",
                "datatype": "MOER",
                "version": "3.2"
        },
        {
                "point_time": "2023-11-06T04:35:00.000Z",
                "value": 955.0,
                "frequency": 300,
                "market": "RTM",
                "ba": "CAISO_NORTH",
                "datatype": "MOER",
                "version": "3.2"
        },
        {
                "point_time": "2023-11-06T04:30:00.000Z",
                "value": 963.0,
                "frequency": 300,
                "market": "RTM",
                "ba": "CAISO_NORTH",
                "datatype": "MOER",
                "version": "3.2"
        }
]

Same as the above, we get the JSON data with which we can play around further.

Methodology

WattTime uses grid's marginal emissions rate. And the API provides access to real-time, forecast, and historical marginal emission data. The rate provided is the Marginal Operating Emissions Rate (MOER). The unit is pounds of emissions per megawatt-hour (e.g. CO2 lbs/MWh). So to use it in the metric system part of the world, we would need to convert that to gCO2eq/kWh.

WattTime has built a marginal emissions model based on the empirical technique founder Gavin McCormick published. The fundamental approach of all those models is a somewhat similar.

1. Data is reported by emissions monitoring system through EPA CAMPD program from the power plants within the US. Through the US Environmental Protection Agency Clean Air Markets Program Data. And now I finally understand why do they abbreviate everything there! I assume this is something similar to ENTSOE.
2. Each system then applies a regression-based modeling to ask every time a rise or fall in electricity demand occurs, which power plants increase/decrease their output in response.

This allows for comparing marginal emissions by time and place.

To discover more about their methodology, check out the link below.

Marginal Emissions Methodology – Watttime

WattTime Logo

Key Takeaways

The purpose of this article is not a comparison of the two. My goal was to explore the options and write down the things I found. Following are some key points I would like you to take from this article.

• The APIs that give us carbon emissions data are there and waiting to be used!
• Both of these I've written about offer free and paid options, which is good. If you are not paying for services, that often times means that you are the product.
• The first step would be to use any of them.
• To achieve the best results, we can test and use both, and compare them. Maybe one works better for us.

Thanks for staying with the article until the end! If you liked it, feel free to share it with your friends, colleagues, peers, and on your social media. Also, feel free to use the comment section below to add your comments, overview, experience.

See you in the next article!

The idea for this article came up as a result from a presentation I've held within my company. There, I was talking about the basics of Green Software and how to put it into practice. One of the topics we've covered was about emission scopes. There I've got an interesting question, to which I couldn't respond at the moment. The question was (and I'm paraphrasing) - isn't a scope 3 a bit a utopia? How can you differentiate between different companies? What all things go into the scope 3?

All these are valid questions, and I'll try to respond to them in this article.

Which emission scopes are there?

Scopes were briefly mentioned in The greenest regions in Azure article. But, let's revisit them once more.

Scopes were defined by the Greenhouse Gas protocol. This is the most widely used gas accounting standard. Almost all Fortune 500 companies use it when calculating and disclosing emissions.

There are three scopes of emissions:

• Scope 1 - direct emissions (on-site fuel combustion, vehicles emission).
• Scope 2 - indirect emissions, by purchased energy (heat or electricity).
• Scope 3 - all other indirect emissions in which we engage. For example, all emissions from organization's supply chain, and so on.

We know that the scope 3 is the most significant and the hardest one to calculate. Why? Because it includes all other activities that the organization is doing. Which can be many, and a bit hard to track.

A simple example of scopes

For this, let's use a Coffee brewing analogy.

In the image below, you can see how you can think of emission scopes in the example of brewing your coffee or tea.

What goes into scope 3?

Here, I want to focus on what's the most important - scope 3. What goes into scope 3? This is a summary of my understanding. I'll ask the questions first, and then do the follow-up research.

If we have a look at the example above, all activities in our supply chain, so we can have a coffee, go into scope 3. This means emissions from the whole chain of production of coffee beans. Including packaging those beans, transporting them to various locations, including ours.

Next, emissions from producing the coffee pots and all the material that goes into them, right? Also, the packaging and transportation to our location... All this is part of scope 3?

Is this correct?

What about if the coffee pot producer and coffee producer already calculate and disclose their emissions. Do we include those emissions in our calculation as well? By adding them to our calculation, wouldn't that be a duplication of emissions?

Am I understanding this right?

Here, a deeper look into what scope 3 is, is needed. And then based on that we'll see what goes where. To help us with that, we'll use the GHG protocol standards.

GHG Protocol Standards

Let's start first with the Corporate Value Chain (Scope 3) Standard. This standard provides methods that can be used to account for and report emissions. From companies of all sectors, globally. Its goal is to make calculating and reporting of Scope 3 easy.

Corporate Value Chain (Scope 3) Standard | GHG Protocol

The Corporate Value Chain (Scope 3) Standard allows companies to assess their entire value chain emissions impact and identify where to focus reduction activities.

GHG Protocol

Following this Scope 3 Standard, is the Scope 3 Guidance. This is a calculation guidance. It's designed to reduce barriers of complexity of Scope 3. It provides a detailed, technical guidance on all the relevant calculation methods. It provides information not contained in the Scope 3 Standard.

• Methods for calculating GHG emissions.
• Guidance on selecting the appropriate calculation methods.
• Examples to show each calculation method.

Scope 3 Calculation Guidance | GHG Protocol

Building on the Scope 3 Standard, this companion guide makes it easier than ever for businesses to complete their scope 3 inventories.

GHG Protocol

To answer the questions from above, we'll use these two documents for guidance.

Types of Scope 3 emissions

There are two types of the Scope 3 emissions. These are the following:

• Upstream activities - everything that goes into the stream (purchased goods and services, capital goods...). Indirect GHG emissions related to purchased or acquired goods and services.
• Downstream activities - everything that goes out of the stream. Processing of sold products, transportation and distribution. Indirect GHG emissions related to sold goods and services.

In my above uncertainties, I've looked at these two types interchangeably. Without even knowing it.

In the case of goods purchased or sold by the reporting company, upstream emissions occur up to the point of receipt by the reporting company, while downstream emissions occur subsequent to their sale by the reporting company and transfer of control from the reporting company to another entity (e.g., a customer).^[1]

In the coffee pot example, yes, we use emissions from coffee pot producer and coffee producer. We use their scope 1 and scope 2 emissions and include them in our Scope 3 emissions.

The following image from the Scope 3 Standard shows an overview of the upstream and downstream activities.

Categories of Scope 3 emissions

These two types of Scope 3 emissions are then divided into different categories. All 15 of them! First 8 are upstream, last 7 are downstream Scope 3 emissions.

1. Purchased goods and services. All upstream emissions from the production of products purchased by the reporting company in the reporting year. Products include goods and services.
2. Capital goods. All upstream emissions from the production of capital goods purchased by the reporting company. Capital goods are final products that have extended life. They are used by the company to manufacture a product, provide a service (e.g. run an application).
3. Fuel- and energy-related emissions not included in scope 1 or scope 2. Includes emissions related to the production of fuels and energy purchased and consumed by the reporting company, not included in the scope 1 and 2. For example - mining of coal, refining of petrol, electricity consumed in a transport and distribution system.
4. Upstream transportation and distribution. It includes transportation and distribution of products purchased by the reporting company from suppliers to operations. Also, third-party transportation and distribution services. In essence - scope 1 and scope 2 emissions of third-party transportation companies.
5. Waste generated in operations. Emissions from disposing waste and waste water. They include scope 1 and 2 emissions from solid waste and wastewater management companies.
6. Business travel. Emissions from employees business-related travels in vehicles owned or operated by third parties. They include scope 1 and 2 from transportation companies (e.g. airline).
7. Employee commuting. Emissions from employee commuting between homes and worksites. Remote work can be included in this category.
8. Upstream leased assets. Emissions from the assets that the company leases.
9. Downstream transportation and distribution. Emissions from transporting and distributing of sold products.
10. Processing of sold products. They include scope 1 and 2 emissions of downstream value chain partners (e.g. manufacturers).
11. Use of sold products. Emissions from the use of goods and services sold by the reporting company.
12. End-of-life treatment of sold products. Waste disposal and treatment of products sold by the reporting company at the end of their life.
13. Downstream leased assets. Emissions from assets owned by the reporting company, but leased to other entities. And not already included in scope 1 or 2.
14. Franchises. Emissions from operating of franchises not included in scope 1 or scope 2. This category applies to those companies selling franchise.
15. Investments. Investments of the reporting company, not included in scope 1 or 2.

These categories are intended to provide companies with a systematic way to organize, understand, and report the scope 3 activities. They are mutually exclusive - there is no double counting of emissions between categories.

Putting it all together

Here, I want to answer my questions from above.

• This means that the whole chain of production of coffee beans... goes into our scope 3? Yes. The whole value chain goes into scope 3, within a certain category, as part of the upstream emissions.
• Emissions from producing coffee pots and all the material that goes into them is part of scope 3? Yes, as a category 2, capital goods.
• Transport and packaging to our location? Yes, in the fourth category - upstream transport and distribution.
• Do we include (or duplicate) emissions from coffee beans producer and coffee pot producer? No. We include their own scope 1 and scope 2 emissions into our scope 3.

Key takeaways

This was a mouth full article. I hope I didn't confuse you, and didn't go on to confuse me even more, when talking about scope 3. The main things to have in mind and to take away from this article are the following.

• Scope 3 represents all other indirect emissions in which we are engaged in.
• There can be an upstream and downstream scope 3 emissions.
• Upstream emissions - emissions from what goes into the value stream.
• Downstream emissions - emissions from what goes out of the value stream as a result.
• There are 15 categories (8 upstream, 7 downstream) that help in calculating the scope 3 emissions.

If you find this article more confusing, or I missed the point, do let me know. I'm eager to see your opinion on the topic.

Thank you and see you in the next article(s)!

Footnotes

1. Section 5.3, page 29 of the Corporate Value Chain (Scope 3) Accounting and Reporting Standard ↩︎

To start on the same note as before - it's been a while! I wasn't able to keep up with my initial plan of publishing an article every second Monday. Last one was 4 weeks ago. Sorry for that! Anyhow, the over planned months/weeks are over, hopefully, and I'll continue to post on a more regular basis.

In this week's article, we'll cover one of the most important parts of the IT industry, one of its cores. The Data centres. What is their impact on the environment, how we measure that impact, what other resources are consumed within a data centre... We'll also examine a study about the importance of eco-friendly and sustainable computing.

What are Data centres and how to measure their effectiveness?

Since I am fond of starting from scratch, let's see what Data centres are? You've heard about the term Cloud, right? Well, most of the data centres are places where that cloud is actually running. These are the buildings where servers, storages, networking machines are running. Location of actual physical resources. This is a rather simplified explanation.

To determine the effectiveness of data centres, we use Power Usage Effectiveness. I've written already about it in the article about The greenest regions in GCP. If you haven't had chance to check it out, now's the time.

To calculate the PUE, you can can use the formula below.

PUE = Total facility energy usage / IT equipment energy usage

The following image is a simplified example of PUE.

What other resource, besides electricity, DCs use?

Water. The equipment uses a lot of water for cooling. Besides the electricity. As with PUE, we also have a measurement called WUE - Water usage effectiveness. This is the litres of water consumed per Kilowatt Hour - L/kWh. Now, the numbers from Google, Microsoft, and Amazon are big.

In 2022, Google used about 21 billion litres of water in their data centres and offices^[1]. Most of it went to the data centres. Microsoft consumed ~6.3 billion of litres of water in 2022 in their Data centres.^[2]

And Amazon, well, they provided WUE. Their data centres consume 0.19 l/kWh on average. ^[3]. I tried finding the exact number of litres consumed, but I wasn't able to do that. I also tried to find the exact amount of kWh of electricity consumed, and then multiply, but with no luck. Amazon reports everything in a bit different way.

A bit about cooling in Data centres

Now, the cooling in Data centres takes a big percentage of the electricity (and water) consumed. If the PUE is 1.5, as in the image above, roughly the 1/3rd of energy consumed goes into cooling. That's a lot!

What can we do about that? Well, for starters, we can increase the temperature in the DCs. The ideal temperature in the DCs is 18-27°C. The ASHRAE envelope provides this guideline. For optimal performance. In practice, temperatures go between 18-21°C.

Now, what they did in Singapore is quite interesting. They've launched a standard for optimizing the energy consumption in data centres. The end goal is to increase the temperature in the DCs at 26°C and above. This could lead to potential 2-5% savings of energy used for cooling for every 1°C increase. They tested it at two DCs, raising the temperature by 2°C. This reduced energy consumption by 2-3% during the trial. To find out more, visit the link below.

IMDA Launches Sustainability Standard for Tropical Climate Data Centres

Singapore has launched one of the world’s first standards for optimising energy efficiency for data centres (DCs) in tropical climate countries. Announced by Singapore’s Senior Minister of

Data Storage Asean

Efficient Computing

Recently, I read an article by Wim Vanderbauwhede called Frugal Computing. The article discusses the importance of low-carbon and sustainable computing and the journey towards zero-carbon computing. A rather interesting article with an interesting conclusion. To prevent IT from worsening global warming and climate change, we must take these steps.

• We cannot count on only using renewables, we must reduce energy consumption.
• We must increase the life-span of hardware resources (phones, laptops, servers).

Now, this article considers all IT devices - laptops, smartphones, servers, IoT devices, and so on. I wanted to focus on the servers. Most of which are in the Data centres.

Manufacturing, distribution, and disposal of servers accounts for 20% of their total emissions. This percent is higher in other types of devices (e.g. smartphones and laptops). And the current life-span of servers in DCs is between 3-5 years. Somewhere is more, but the general rule of thumb is to replace servers every 5 years. We would definitely need to increase that!

As a society, we need to start treating computational resources as finite and precious, to be used only when necessary, and as effectively as possible.

To check out the complete research article, follow the link below.

Frugal Computing -- On the need for low-carbon and sustainable computing and the path towards zero-carbon computing

The current emissions from computing are almost 4% of the world total. This is already more than emissions from the airline industry and are projected to rise steeply over the next two decades. By 2040 emissions from computing alone will account for more than half of the emissions budget to keep glo…

arXiv.orgWim Vanderbauwhede

Summary

With this article, I only scratched the surface of the energy consumption of DCs. I'm aware of that. To give you some more info - Ireland released a report for electricity consumption in 2022. They found that data centres use 18% of all electricity. The same amount as urban dwellings, and 8% more than rural dwellings. That is a lot!

So, Data centres are a big part of the IT infrastructure, and how we treat them has and will have an impact on our planet. That impact is not immediate, but rather long-term. In the next 10, or 20 years. But it is important to act now.

• We need to reduce the energy consumption of DCs, increasing cooling temperatures is one of the way.
• We need to increase the approximate life-span of servers and DC equipment.
• Furthermore, we need to consider computing as a finite resource.

See you in the next article!

Footnotes

1. page 50 of the Google Environmental Report ↩︎
2. page 6 of the Microsoft Environmental Fact Sheet ↩︎
3. page 35 of the Amazon Sustainability Report ↩︎

This week, we'll cover the Carbon Awareness. We'll go from the beginning - what it is, and why is it important. Then we'll check out how you and your team can be more carbon aware. I'll also mention some examples of carbon awareness. In the end, we'll cover if there is a negative side to it.

I hope you'll find this topic interesting and engaging. And I hope it will help us better understand the idea of how can we all help in fighting climate change. One server at a time.

What it is?

To explain this, we need to first address what is awareness? Just kidding. Paragraphs below explain the carbon awareness in somewhat simple terms.

What we all know is that not all electricity production is equal. There are renewable sources, with little to no carbon emission. Then there are non-renewable sources which, well, brought us here.

What I wasn't aware before is that at different times or locations, these sources vary. This means that on sunny or windy days, you can get electricity from solar or wind power. And in opposite cases, you'll usually get it from a regular coal burning power plant.

This might not apply as much to the state of things in Serbia. As you can see on the image below, we don't consume that much electricity from renewable sources. Well, there is hydroelectric energy, sure. But then again, we also have those Mini hydroelectric power plants that are quite a touchy topic.

As a country, we might be good at sports. But, when it comes to energy production and consumption, well... But we'll not cover that here.

What is carbon awareness? Do more when the energy is coming from renewable sources. Do less when it comes from non-renewable sources.

That is neat. But, it's easier said than done.

Why is this important?

The answer to this is quite simple - it is important because it can help saving our planet. One of the things that can be helpful is to stop using electricity from carbon intensive sources. That is not an easy thing to do at once, so we need to be more patient there. Step by step our consumption from those sources needs to decrease.

An advantage for renewable sources is that they're cheaper than coal. And studies show that carbon aware actions can result in 45% to 99% carbon reductions. Depending on the number of renewables powering the grid. More information on the link below.

Putting a CO<inf>2</inf> figure on a piece of computation

In recent years, energy efficiency has become a major focus of data centre designers and operators. This has predominantly been due to the rising cost of energy and the exponential increase in the absolute energy consumption of data centres. As carbon taxes, emissions trading and environmental imper…

IEEE Xplore

How to be more carbon aware?

There are two ways to be more carbon aware - demand shifting and demand shaping.

Demand shifting

If workloads are flexible about when and where they run, we can shift our demand accordingly. We can run our workloads more when the energy is cleaner, and less or not at all when the energy is dirtier. For example, we can train a Machine Learning model at a different time or region with a cleaner energy.

We can break down demand shifting to the following.

• Spatial shifting. Moving our workloads to regions where the energy is cleaner.
• Temporal shifting. If we cannot move our workloads to different regions, it's possible to run them at different times. During the sunny or windy day, we can opt for running our workloads more.

Demand shaping

Like the above, demand shaping means that we shape our demand to match the existing supply. Demand shaping for carbon-aware applications is all about the supply of carbon. When the carbon cost becomes high, shape the demand to match the supply of carbon. This can happen automatically, or the user can make a choice.

One example of demand shaping is eco-mode found in cars or washing machines. When activated, some amount of performance is sacrificed to consume fewer resources.

Applications can also have eco-modes that can make decisions to reduce emissions. Automatically or with user's consent. A couple of examples are the following.

• Video conferencing software that adjusts streaming quality automatically. This means reducing the video quality to focus on audio when the bandwidth is low. Instead of streaming at high quality all the time.
• TCP/IP. The transfer speed increases in response to how much data is broadcast over the wire.
• Progressive enhancement with the web. The user experience improves based on the resources and bandwidth available on the end devices.

Demand shaping relates to a broader concept in sustainability - reducing consumption. We can achieve a lot by becoming more efficient with resources, but we also need to consume less at some point.

Carbon awareness in the wild

Example of demand shaping

A good example of demand shaping is the website of the Branch Magazine. It is an online magazine written by and for people who dream of a sustainable and a just internet for all. It is published by the Green Web Foundation.

The image below shows how it looks when you visit their site.

You have a way to choose your experience on their site. If the grid intensity is low, the web page will load full-blown content - images, videos, GIFs, and so on. Grid carbon intensity is low = energy coming from renewables. If the grid intensity is high, they will not load full content. Instead, the web page will show ALT text for images, videos and GIFs. Website will consume less energy.

If you want to find out more about the way they design their website and why, visit the link below.

Designing Branch: Sustainable Interaction Design Principles - Branch

There’s a need to reconnect the digital to the physical, from minerals and energy to the physical infrastructure that powers the internet. We have to repurpose our digital design processes to consider and reflect these ecological needs, instead of optimising only for business and growth objectives,…

BranchTom Jarrett

Example of demand shifting

A good example of demand shifting, is the Carbon Aware KEDA Operator. Now, KEDA stands for Kubernetes-based Event Driven Autoscaler. This application can schedule workloads in Kubernetes clusters based on certain events. One of them is carbon intensity of the grid.

Based on the documentation, you can use this Operator to schedule workloads by looking at the data from the Watttime or Electricity Maps. Then it dynamically adjusts the behaviour of the KEDA scheduler.

To find out more about it, visit their GitHub repository on the link below.

GitHub - Azure/carbon-aware-keda-operator

Contribute to Azure/carbon-aware-keda-operator development by creating an account on GitHub.

GitHubAzure

Now, I haven't played around with this Operator, but I'll do a demo on it in some future article. It would be nice to provide some technical setup of it.

Is there a negative side to carbon awareness?

Before concluding the topic, I want to mention the following question.

Is there a concern that when everyone time shifts to the same location or the same greener grids, that can increase the demand of those grid's energy, which could increase fossil fuel burning to meet that new demand?

There are two parts of this question. The first part is - why we can burn more fossil fuels when we move computing to the greener parts of the world? And the second is - should we be concerned with that?

To answer the first part - in theory, this can happen. If the grid becomes overloaded, power grid companies will end up burning fossil fuels to match this increase. The energy coming from the burning of coal can be dispatched. Meaning, it's easy to predict how much energy you will get from it. Unlike the solar and energy from the wind. You cannot predict easily if there will be wind or more sun, and so on.

Can this happen? In the event that we have only one location providing the renewable energy - it might. The fact that we have plenty of regions in the world that provide the renewables, this is unlikely.

To provide an answer to the second part, I will quote an answer from Asim Hussain. He is the executive director and chairperson of the Green Software Foundation and the director of Green Software at Intel.

... that's one of them good problems. And that's what I think about this thing. So someone's telling me a problem and I'm like, this is a good problem to have. If we are ever even remotely getting to the point where demand shifting is affecting a grid, that is a level of achievement, which is excellent.
...
Yes, there are negative consequences to that approach, but we are not even remotely there right now. So worrying about that is I think, a little bit too hyperbolic at the moment. You shouldn't do something because if you take that thing to the absolute extreme, it will be negative
...
I would say demand shifting is never going to be the one solution you have in your pocket to reduce your emissions of your application, your architecture. I always describe it as one of the things that you can do. It's one of the easier things to do. It gets you started on the much more challenging journey of energy efficiency, hardware efficiency, reducing the amount of energy you use, reduce the amount of compute you use.

This question was raised on the Environment Variables podcast. One of my favourite ones. This podcast provides the latest news on how to reduce the emissions of software and how the industry is dealing with its own environmental impact. You can find the full episode and the transcript on the link below.

We Answer Your Questions!

On this episode of Environment Variables, host Chris Adams is joined by Asim Hussain as they dive into a mailbag session, bringing you the most burning unanswered questions from the recent live virtual event on World Environment Day that was hosted by the Green Software Foundation on June 5 2023. As…

We Answer Your Questions!Green Software Foundation

Further exploration

Now, I mention a lot of things here. Most of it comes from the excellent material from the Green Software Foundation. On the link below, you can find more about carbon awareness. This lesson is part of the material for the Green Software Practitioner certification. The whole certification process is free. It can help you understand sustainability in IT and principles of green software.

Carbon Awareness | Learn Green Software

Do more when the electricity is cleaner and do less when the electricity is dirtier.

Green Software Practitioner

The second link is an interesting talk from Hot Carbon conference from this year. The title is Bringing Carbon Awareness to Multi-cloud Application Delivery (Maji et al.). They discuss how carbon awareness of the Load Balancer on VMWare, decreased overall carbon intensity. The data available was from the research, not live environments. All applications were only stateless. If you'd like to find out more, check out this link.

Congrats! You've reached the end of this carbon awareness article. Thank you for the focus and attention throughout the article.

Let me know in the comments below your opinion on the topic. I'm interested in your feedback and if you found something interesting or not. Feel free to share this article as well, so it can reach more people interested in the topic. Your feedback helps me stay motivated for the future!

Thank you!

First, we'll answer some of the questions related to the numbers that we're going to see later in the article.

The thing that we'll cover first is the Power Usage Effectiveness, or PUE for short. What does it mean? How is it measured? After that, we'll go on to analyse the data available from the GCP. What do they publish, and what are the greenest regions available there? How long did it take me to find this information?

What is Power Usage Effectiveness?

Power usage effectiveness or PUE is a standard efficiency metric for power consumption in data centres. A simple definition of PUE is the ratio of total facility energy to IT equipment energy used in a data centre.

PUE  = Total facility energy usage / IT equipment energy usage

Total facility energy includes the power dedicated to the data centre, measured at the meter. All loads, including IT equipment, cooling systems, lighting systems, and power delivery components.

Total IT equipment includes all energy fed to compute, storage, and networking equipment. As well as, other control equipment like KVM switches, workstations, monitors, and laptops.

Calculating PUE is not as straightforward as the formula seems. Despite the simple ratio and the acceptance as a standard performance metric.

PUE is not a one-time metric. It changes from time to time. It depends on the time of the day, load on the servers, where energy is coming from, location, and so on.

PUE values closer to 1 are better. That means that the data centre is using most of its energy (if not all) for the IT equipment operation. I'm wondering if the PUE can actually be 1? Maybe not, but one can hope...

To find out more about Power usage effectiveness in general, follow the link below. The blog post explains the basics of PUE and what we need to understand about the numbers.

What Is PUE (Power Usage Effectiveness) and What Does It Measure?

Power usage effectiveness or PUE is a standard efficiency metric for power consumption in data centers.

Albér™

On the graph below, you can see average PUE in Google Data Centres from 2008 until nowadays. We can see that the trend is decreasing. This means that the efficiency of the Google Data Centres is getting better and better.

To find more information on the topic of PUE in Google Data Centres, follow the link below. There you can find how PUE values are calculated and PUE throughout the year. Reports for each quarter for each data centre across the globe are also available. Pretty cool!

Efficiency – Data Centers – Google

We’ve worked hard to minimize the environmental impact of these services so that when you use our products, you’re also being good to the environment.

Google Data Centers

Is PUE relevant to the greenness of a region?

Not exactly. PUE shows how efficient are data centres in their energy consumption. It doesn't show from which sources that energy is taken. Still, it's better for data centres to be the most efficient as possible.

Regardless of the energy sources, the efficient usage of energy is vital. We should strive to use the least amount of energy. That's why I wanted to give a brief intro about PUE.

What are the greenest regions in GCP?

Google, being all Google - information at your fingertips, made the search for this info quite easy. There is info all over the places about the regions being Low CO2. Well, not all over the places, only two. But never mind that.

What it means for a region to be Low CO2? In Google's terms, they are taking three metrics into account:

• Google CFE% - an interesting metric about which I'll write below.
• Grid carbon intensity in gCO2eq/kWh - I've covered this in How much carbon does my server emit? article.
• Google Cloud GHG emissions - in short - Scope 2 market-based emissions. Not perfect, but at least it's something. We also covered this in the greenest regions in Azure article.

Google CFE%

This is the percentage of the carbon free energy consumed in a particular region, on an hourly basis. Plus the investments Google has made in carbon-free energy in that region. Besides renewable energy coming from the grid, Google also includes carbon-free energy it produces in that region.

In other words - the average percentage of time application will run on carbon-free energy. More in this case is better.

To find out more about the Google CFE% and carbon-free energy, follow the link below. This article explains how they Google CFE% is calculated. Besides, it also provides some considerations in choosing the right Google cloud region.

Carbon free energy for Google Cloud regions

Google Cloud

Finally, the greenest regions in GCP are:

• Europe:
  • europe-north1 in Finland,
  • europe-west1 in Belgium,
  • europe-west2 in London,
  • europe-west3 in Frankfurt,
  • europe-west6 in Zurich
  • europe-west9 in Paris
• North America:
  • northamerica-northeast1 in Montréal
  • northamerica-northeast2 in Toronto
  • us-central1 in Iowa
  • us-west1 in Oregon
• South America:
  • southamerica-east1 in São Paulo
  • southamerica-west1 in Santiago

The table below shows a preview of which services are available in which region. The greenest regions have Low CO2 mark below its name.

For the complete list of services, and regions, follow the link below.

Global Locations - Regions & Zones | Google Cloud

Google Cloud offers regions across the world to provide customers with global coverage, low cost, low latency, and application availability.

Google Cloud

Useful Information

There is a plethora of information I found during my quest for the greenest regions in the GCP. Some of it is boilerplate, but some of it is rather interesting. Below, I'm going to share the links about the latter.

Google published their 2023 Environmental Report. It's quite an interesting read, and you can find all the numbers in the accompanying PDF. To find out more, follow the link below.

Sustainable Innovation & Technology - Google Sustainability

Sustainability

To find out interesting facts about Google's take on sustainability, go to the link below. It's also a starting point to other Google sustainability-relevant sources.

Sustainability | Google Cloud

Google Cloud reduces the environmental impact of cloud computing through innovative renewable energy purchasing and commitment

Google Cloud

Last, but not least, map showing climate impact by area! This, I found the most interesting. It is a map showing the amount of produced and consumed electricity. And, it's open source! Below is a preview of it.

To find out more, and explore by yourself, check out the link below.

Live 24/7 CO₂ emissions of electricity consumption

Electricity Maps is a live 24/7 visualization of where your electricity comes from and how much CO2 was emitted to produce it.

Live 24/7 CO₂ emissions of electricity consumption

Key Takeaways

Google publishes the data in an open manner, and it's quite easy to find what the regions are the greenest. If that is what you are looking for. I like that part. I also like their strive to be carbon-free 24/7 by 2030. Following, are some of the key takeaways from this article:

• Power Usage Effectiveness - how energy efficient are data centres.
• PUE isn't directly related to the region being green, but the less energy we use, the better.
• Google CFE% a percentage of carbon-free energy used in a region, calculated by Google.

When deciding where to host your application, regardless of the provider, consider the following:

• Latency to end users can be different from region to region.
• Prices differ from region to region.
• Some regions can have higher carbon-intensity than others, choose them wisely.

This is it! I hope you found the information above interesting and useful. In the following weeks, I'll wrap everything up in a short(er) summary. I will go through and compare the information from the major cloud providers I covered here.

My plan is to continue to publish sustainability-related articles. To learn and raise awareness. Stay tuned and see you in the next article!

First, we'll have a look at the emission scopes and their importance. Then we'll talk about methods used in calculating emissions on Azure (and AWS for that matter). Last but not least, we'll see the greenest regions in Azure and available reports.

What are emission scopes?

There is something called the Greenhouse Gas protocol. This protocol is the most used standard companies use to publish emissions of Carbon. It divides the emissions into 3 scopes.

• Scope 1 - Direct emissions from operations owned or controlled by the organization. For example, on-site fuel combustion or fleet vehicles.
• Scope 2 - Indirect emissions related to emission generation of purchased energy. For example, heat and electricity.
• Scope 3 - Other indirect emissions from all the other activities companies engage in. For example, emissions from an organization's supply chain. Business travel for employees. The electricity customers may consume when using your product. And so on.

The one that is the most significant and the most difficult to calculate is, you guessed it - scope 3. It is often referred to as value chain emissions. It represents a full range of activities needed to create a product or a service. From the initial idea to the end distribution.

For example, every raw material used in the production of your laptop emits carbon. Emission resulting from material extraction and processing is part of Scope 3. This scope also includes emissions from the use of the laptop after you buy it.

You can find more information about emission scopes on the link below.

Measurement | Learn Green Software

What you can’t measure, you can’t improve.

Green Software Practitioner

Azure publishes scope 3 emissions, unlike AWS. It (AWS) includes only Scope 2 emissions. This is the reason why I saw 0 emissions on Customer Carbon Footprint Tool on AWS.

Is this what they call greenwashing? #askingforafriend

Methods to calculate emissions

It is a complex process. Adding to that complexity, we need to take into account two methods per GHG Protocol scope 2 reporting guidance. These two methods are:

1. Location-based method. Emission intensity of the power grids from which companies consume electricity. The energy you use.
2. Market-based method. Reflects emissions from the electricity that companies have bought. The energy you pay.

Both these methods are ways of calculating carbon emissions from Scope 2. Now, the report above recommends using both of them in calculating emissions. This is dual reporting. According to the reports, AWS only uses a market-based calculation method. Azure (Microsoft) uses both location-based and market-based methods.

To be honest, I don't quite understand the need for a market-based method. Other than the following.

We bought electricity from renewable sources, thus our emissions are 0. We don't care from which sources we actually get it.

To me, the more logical solution is location-based, or a combo of these two.

What are the greenest regions in Azure?

Now to the exact numbers. For starters, Azure wasn't as straightforward as AWS. You need to dig deep to see what percent of renewables power their regions. Or, I wasn't able to find that out as I did for the AWS.

Microsoft pledges to shift to 100 percent renewable energy supply by 2025. That probably means they are close to it, so let's check.

The table above is from the 2022 Environment Sustainability Report - Data Fact Sheet.

To calculate the percent of renewable energy used, we will use the above marked numbers. If we divide the two, and multiply by 100, we can see that ~2.5% of consumed energy comes from non-renewables. That means that the other 97.5% are from renewables. Which is great! That is, if the values they are reporting are correct.

Continuing on my quest to find the greenest regions, I found this.

This screenshot shows the location of Microsoft's sustainability projects. They spread all over the US, Northern Europe, and a couple of those projects in the rest of the world. Then I went and applied some extra filters, shown in the image below.

I selected the Microsoft Circular Center sustainability feature. To translate this - the equipment from those data centres is going to be re-used when they reach the end of life. Or EOL, as one might call it. On the video below, you can find more about this feature.

Microsoft Circular Centers

Overview of the Microsoft Circular Centers and how they are helping to achieve Microsoft’s goals to be zero waste and carbon negative by 2030.

Microsoft Learnmarkdefalco

Selecting this feature produced an output below. Blue dots are regions, and yellow symbols are sustainable projects.

This leads me to assume that the greenest regions on Azure are:

• North Central US
• East US 2
• North Europe
• West Europe
• Southeast Asia

If you want to check this out on your own, go ahead and visit the below web page.

Explore | Azure global infrastructure experience

Explore the 3D interactive globe to learn more about the physical locations of the Azure global footprint.

The above is my assumption. And knowing that I'm not a fan of assumptions, I tried to find a bit more. And I found the below quote.

We’ve also built one of our most sustainable cloud regions in Sweden that launched in November 2021. This will enable us to use 100 percent renewable energy for each hour of consumption. Sweden will be the first Microsoft region to use lower-carbon renewable fuel for backup power. source

Finally! We have a winner - it's the region in Sweden!

The following link leads you to the 2022 Environmental Sustainability Report. There you can see everything described in more detail.

How to calculate your emissions?

There is a tool for that on Azure, and it's called - Emissions Impact Dashboard. It is a Power BI template that helps you calculate the emissions of your workloads running on Azure.

There is a catch, however. This tool is only available for Power BI Pro users, so if you are one of them, congrats! If not, I guess a demo would be nice to have a look at and play around. Like it did for me. And at least this one doesn't show 0 MTCO2e emissions.

To find out how to use and configure the tool, check out the link below.

Connect to the Emissions Impact Dashboard for Azure - Power BI

The Emissions Impact Dashboard for Azure enables you to calculate your cloud-based emissions generated by your usage of Azure and Microsoft Dynamics. This document shows you how to connect to the Emissions Impact Dashboard.

Microsoft Learnandreabichsel

Since I don't have any workloads running on Azure, I haven't had a chance to check out this tool on proper terms. Have you had a chance to do so? What are your findings, learnings, and experience from using it? You can write your impressions in the comments below.

Key Takeaways

Researching for this article took me down the rabbit hole. I doubted if I will be able to find the exact numbers. I still doubt I found them. On the other hand, it helped me understand things. I saw how big sustainability is for Microsoft. And that gives me hope.

Below are some of the key takeaways throughout my journey in writing this article.

• There are 3 scopes of emissions. Direct, indirect via power consumption, and indirect emissions from all other activities.
• When looking at the reported emissions, we need to have in mind the methods used in calculating them. Those methods are: market-based, location-based, or both.
• Emissions calculated only by market-based method could lead in the wrong direction. For example, emission numbers are smaller than it actually is.
• I got the impression that Microsoft cares about sustainability and the way they report it. They are also the ones behind the Green Software Foundation. Kudos! Even though information is a bit harder to find, it seemed more concrete to me when I did the research.
• You can use Emission Impact Dashboard to calculate emissions of Azure workloads.

To go down the rabbit hole yourself, visit the below page.

Azure Sustainability—Sustainable Technologies | Microsoft Azure

Learn about sustainable cloud infrastructure with Azure and explore sustainable technologies for lowering the carbon footprint of your business.

Read the study on sustainability and cloud computing

See you in the next article!

In future articles I plan to concentrate on two other main cloud providers - Azure, and GCP. If you find this list is incomplete, let me know, so I can have a look into others as well.

In this article, I'll answer the above question - what are the greenest regions in the AWS? We will dig a bit deeper in the information AWS has available. We will look for some insights where you can find useful sustainability-related stuff.

What do I mean by green region?

The green region would be the region that is powered by renewable energy - wind, solar, geothermal... Below is the official definition of Renewable energy from the US Environment Protection Agency.

Renewable energy includes resources that rely on fuel sources that restore themselves over short periods of time and do not diminish. Such fuel sources include the sun, wind, moving water, organic plant and waste material (eligible biomass), and the earth’s heat (geothermal).

What is the carbon footprint?

To answer this, here is a quote from Britannica.

The carbon footprint, amount of carbon dioxide (CO2) emissions associated with all the activities of a person or other entity (e.g., building, corporation, country, etc.). It includes direct emissions, such as those that result from fossil-fuel combustion in manufacturing, heating, and transportation, as well as emissions required to produce the electricity associated with goods and services consumed. In addition, the carbon footprint concept also often includes the emissions of other greenhouse gases, such as methane, nitrous oxide, or chlorofluorocarbons (CFCs).

In short - it is your or any other entity's carbon emissions. And, it's not as easy to measure it.

How to measure carbon footprint on AWS?

AWS has a tool which helps you with the carbon emissions generated from AWS usage. It presents the data in MTCO2e - metric ton of CO2 equivalent.

If you need a reminder on what CO2 equivalent is, check out my previous article.

On the link below, you can have a look at the Carbon Footprint tool from AWS.

Carbon Footprint Reporting – Customer Carbon Footprint Tool – Amazon Web Services

The customer carbon footprint tool is a dashboard that provides an overview of the estimated carbon emissions associated with your AWS workloads. Use easy-to understand data visualizations to measure, report, track, and forecast your emissions to help meet your sustainability goals.

Amazon Web Services, Inc.

This is neat! But, is it working? I wasn't able to confirm that on my account(s). Even though I had some machines running for more than a few weeks, my carbon footprint was still zero. I'm curious to see if this is working for you, or you also receive the same numbers?

There might be a reason behind the value being zero. Spoiler alert - all my workloads were running in Europe. Is it region-related?

What are the greenest regions?

Well, I thought it was going to be a hard thing to find out, and actually it wasn't. It was quite easy, which bummed me a bit, to be honest. I was looking forward to checking things out and trying to calculate the numbers.

But, the information about the greenest regions is available on the page below.

The Cloud

AWS is the world’s most comprehensive and broadly adopted cloud offering, with millions of global users depending on it every day. To build a sustainable business for our customers and for the world we all share, we’re designing data centers that provide the efficient, resilient service our…

Sustainability (US)

Below, you'll see a map from that page, with the number of solar and wind farms owned by Amazon. The numbers are quite amazing! I was quite surprised about the amount of data being available.

Based on that information, the greenest regions in 2022 are the following:

• U.S. East (Northern Virginia)
• GovCloud (U.S. East)
• U.S. East (Ohio)
• U.S. West (Oregon)
• GovCloud (U.S. West)
• U.S. West (Northern California)
• Canada (Central)
• Europe (Ireland)
• Europe (Frankfurt)
• Europe (London)
• Europe (Milan)
• Europe (Paris)
• Europe (Stockholm)
• Europe (Spain)
• Europe (Zurich)
• Asia-Pacific (Mumbai)
• Asia-Pacific (Hyderabad)
• China (Beijing)
• China (Ningxia)

This is awesome. Nineteen of the AWS regions are 100% powered by renewables.

Extra reports

The reporting on the consumed energy is quite good as well. Based on my limited knowledge and more than a couple of hours of research. Now, to the specific reports.

The Renewable Energy Methodology report. It summarizes a plan to reach net-zero carbon by 2040. Some of the commitments from the report:

1. Powering the whole operations from renewables by 2025.
2. Produce enough renewable energy to match the electricity used by all active Echo devices.

This report also mentions the strategies to achieving those commitments. How they measure the amount of renewable energy, and so on. It is a 3-pages-long report, and available to the public.

Next one is the Carbon Methodology report. This paper summarizes what goes in the Amazon's carbon footprint. It is a bit longer - 7-pages read, also available to public.

Last, but not least, there is the Sustainability Report from 2022. This is a complete report of all things related to sustainability that Amazon is doing. It shows the numbers for carbon emissions, renewable energy, packaging emissions, water, diversity, equity, and inclusion, training, community impact.

Below is a screenshot of an Amazon's 2022 Year in Review.

You can find all these sustainability-relevant reports on the page below.

Reporting and Downloads

Amazon’s 2022 Sustainability Report builds on our sustainability progress over the last decade—particularly since 2019 when we co-founded The Climate Pledge and announced our commitment to achieve net-zero carbon emissions across our business by 2040.

Sustainability (US)

How can we use this?

Well, for starters, we can check in which region(s) we run our AWS workloads. If possible, consider migrating to the green ones mentioned above. One small step for us, but kind of impactful for the Planet.

Consult the Carbon Footprint tool and see what is the amount of MTCO2e your workloads emit. It's not working for me, but then again, I may be doing something wrong?

Check out the Sustainability Pillar of AWS Well-Architected Framework. It contains the design principles, operational guidance, best-practices, potential trade-offs, and improvement plans. We can use all that to meet sustainability targets for our AWS workloads. Prerequisite for this - have sustainability targets in the first place!

Sustainability Pillar - AWS Well-Architected Framework - Sustainability Pillar

This whitepaper focuses on the sustainability pillar of the Amazon Web Services (AWS) Well-Architected Framework. It provides design principles, operational guidance, best-practices, potential trade-offs, and improvement plans you can use to meet sustainability targets for your AWS workloads.

Sustainability Pillar

Another thing we can do, and this applies to all the Cloud providers, is to check for Cloud Zombies. All those things we don't use on the Cloud but costs us money, energy, time... Check out the link below to find out how to do this.

Why Cloud Zombies Are Destroying the Planet and How You Can Stop Them

At QCon London, Holly Cummins, Quarkus senior principal software engineer at RedHat, talked about how utilization and elasticity relate to sustainability. In addition, she introduced a range of practical zombie-hunting techniques, including absurdly simple automation, LightSwitchOps, and FinOps.

InfoQSteef-Jan Wiggers

Let me know if the information shared above is helpful or if I missed something. Write down in the comments below your take on this.

In following weeks, I'll do the same coverage for Azure and Google Cloud providers. See you in the next article!

It's been a while since I last wrote. The latest article should have been in your inbox last week. I missed the schedule. I apologize for that. I'll make an effort to stick to the current one of once every two weeks. Although, I'm considering posting articles in a more regular manner. We'll see how things unfold. For now, I'm returning to the every other Monday newsletter. It might be too much to change it.

With this and future articles, I want to scratch the surface of a topic that I find very interesting. It's a topic that is of great importance to us and our planet. I'm referring to the topic of green (sustainable) software. Some of the questions I am going to answer are - How can we contribute to reducing global warming? How can software engineers help the Earth? What do certain terms mean, and why are they important? These are some of the things and questions I want to explore through this and future articles.

We'll start with small things. We are going to answer a simple question: How much carbon does my server emit?

Why is this important?

By now, you should know a thing or two about global warming. If not, it would be a good idea to educate yourself further.

Here's a summary (a TL;DR one might call it). Earth is getting warmer and warmer due to emission of certain gasses. This is the greenhouse effect. And those gasses are, you guessed it, greenhouse gasses (or GHGs for short). Now, the warming by itself, shouldn't be a problem, right?

Nope, it is a problem. A big problem. The increase in Earth's temperature has a negative impact on us all. Both flora and fauna. And while there are many debates about who caused it, the main contributors to global warming are us - humans. I have written about global warming before, check out the link below to find out more.

Is global warming a known system behavior?

We all know, or at least should, the scientific explanation of climate change - global warming - an increase in Earth’s air and ocean temperature. And this is bad because global warming is causing ice sheets and glaciers to melt. The melting ice is causing sea levels to rise at

Wondering ChimpMarjan Bugarinović

Some studies show that the IT sector's contribution to global warming is between 1.8% and 2.8%. The belief is that this figure is much higher. This is because the entire life cycle and supply chain of equipment were not taken into account. Things like equipment, infrastructure, energy consumption during production... One of the sources for these figures is on the link below.

Emissions from computing and ICT could be worse than previously thought

Researchers claim that previous calculations of ICT’s share of global greenhouse emissions, estimated at 1.8-2.8%, likely fall short of the sector’s real climate impact as they only show a partial picture. The researchers point out that some of these prior estimates do not account for the full life-…

ScienceDaily

Although the above percentage seems insignificant, it is definitely much higher. That's one of the reasons for this article. I want to focus on carbon emissions into the atmosphere from the equipment we use. I want to educate myself and you, the reader, about something new. With the hope of contributing to sustainability and a greener future.

Why carbon?

Carbon is often used as a term to denote the impact of all types of emissions and activities on global warming. Other types of emissions include, for example, methane emissions. The term carbon often refers to all greenhouse gases (GHGs).

To determine the degree of impact of gases on global warming, we use carbon equivalent. Or CO2eq/CO2-eq/CO2e for short. In simple terms - one ton of methane has the same warming effect as 80 tons of carbon dioxide. We normalize that value to 80 tons of CO2eq.

How do we measure carbon emissions?

With the help of carbon intensity. This metric shows the emission of carbon per kilowatt-hour (KWh) of electricity consumed. The standard unit of measurement is grams of carbon per kilowatt-hour - gCO2eq/KWh.

To give you an example. Imagine you live near a wind farm. And your power grid connects directly to it. If you plug in your laptop to the outlet, the electricity used by it would have a carbon intensity value of 0 gCO2eq/kWh. This is because the wind farm does not emit carbon to generate electricity. Again, this is a simplified example.

Of course, in real life, this is not the case. Often, we do not have direct control over the grid and the sources from which we get electricity. This means that our carbon intensity is a mix of all the current sources of electricity on the grid. These sources can be higher-carbon or lower-carbon. The latter is what we want - lower carbon. In Serbia, unfortunately, the higher-carbon sources are dominant.

How to calculate the carbon intensity?

In short, this process is not that simple. There are many calculation methods mentioned on Wikipedia. Not wanting to recycle the content from other sources, I won't go into detail about those methods here. You can learn about them at the link below.

Emission intensity - Wikipedia

Wikimedia Foundation, Inc.Contributors to Wikimedia projects

For our example, let's consider the carbon emissions during actual equipment usage. To be exact, the well-to-wheels (WTW) method. I need to emphasize that this is an estimate. We cannot determine the exact carbon intensity of our machine in an easy way. The value depends on many variables.

For this example, I will use a simple Raspberry Pi 3 model B as the server. The first reason - it's because I have it laying in my apartment for some time. The second - it's because I want to save you some time. I don't want to go into details of many resources on different cloud providers. Whether they are Version A, Generation X, or whatever comes to mind, it's not important for this article. They exist only to confuse you.

Below are the most important specs of the Raspberry Pi I'm using.

• Quad Core 1.2GHz Broadcom BCM2837 64bit CPU
• 1 GB RAM
• BCM43438 wireless LAN and Bluetooth Low Energy (BLE) on board
• Micro SD port for loading your operating system and storing data
• Upgraded switched Micro USB power source up to 2.5A

So, we have 1.2GHz quad-core CPU, and 1 GB of RAM. That should be enough for this example. For full specs, check out the link below.

Buy a Raspberry Pi 3 Model B – Raspberry Pi

Single-board computer with wireless LAN and Bluetooth connectivity

Raspberry PiRaspberry Pi Ltd

I admit, the term server is rather loose in this article. But, I do consider Raspberry Pi a type of server. It is compact, and enough for some operations. It often comes without a graphical interface (as it should). Last, but not least - it's running the Linux operating system.

Now, how much power does the Raspberry Pi consume? Searching the internet, I came across a figure of 3.6 Watts. That is, if the Pi is not working in idle mode. The energy consumption for a whole day would be approximately 86.4 Watts per hour (Wh). In kilowatt-hours, that is 0.0864 kWh. The link below provides more information.

How much energy does the Raspberry Pi consume in a day?

My searching efforts have failed when trying to find this. On average, how much energy does the Raspberry Pi consume in 24 hours (minimal usage vs. max usage in a day and USB vs. Micro-USB powered)?

Raspberry Pi Stack ExchangeZero

Next, a bit more complex part of the calculation - the source of electricity. Each source of electricity carries a certain gCO2eq emission into the atmosphere. We need to make sure we take all into account. The image below shows the estimated emissions for different energy sources.

Based on the report from 2022, the electricity production in Serbia varies a bit. The most dominant is the production from thermal power stations. The second is from hydroelectric power stations.

You can find the reports linked below. Sorry for the Serbian version, I wasn't able to find the English one.

Technical reports – Elektromreža Srbije

The graph below shows the electricity production in 2022 per month. The blue line shows the hydroelectric and the brown is from thermal power stations.

So, roughly 2/3 of the consumption emits around 1000 gCO2eq/kWh, and 1/3 of the consumption emits around 11 gCO2eq/kWh.

The calculation would look like this:

(0.0864 kWh x 2/3) * 1000 gCO2eq/kWh + (0.0864 kWh x 1/3) * 11 gCO2eq/kWh = 57.9168 gCO2eq

If I let the Raspberry Pi run for the whole day, it would have emissions of around 58 grams of CO2 equivalent. Not bad, you might think?

Well, I wouldn't exactly say so. Consider the size and power of the device itself. The weight of the Raspberry Pi is ~300g, and its power is 3.6 Watts. Even though the consumption is low, the amount of carbon it produces is not negligible. In other words - during its full-day operation, it emits almost 1/5 of its weight in CO2eq. Thanks to electricity sources in Serbia.

A simple calculation, right? Well, sort of. Some information wasn't easy to find, though... These values might not be exact, and for sure may vary. This number could be higher. Since I live in Belgrade, where the main source of electricity is a thermal power station. But, I wanted to stay as unbiased as I could, based on the values I found.

Key takeaways

As I mentioned above - these calculations are approximate estimates. Based on the information I gathered from the internet. They are not exact. They might be worse, but one can hope.

Some of the key takeaways from this article, for both you - the reader and me - the author, are the following:

• Carbon - a term often used to encompass all Greenhouse Gasses (GHGs).
• Carbon equivalent - the warming effect of a GHG expressed in a warming effect of carbon.
• Carbon intensity - a metric that shows emission of carbon per kilowatt-hour (KWh) of power consumed. The measurement unit is gCO2eq.
• Carbon intensity depends on energy sources.
• Transparent data about energy production is necessary to calculate carbon intensity.

That's it for now. I hope you found this article informative.

Let me know in the comments below what you found the most interesting. Is there any information you'd want to share? Do you find the numbers and calculations I presented above wrong?

If you received this article by e-mail, forward it to somebody who will find this topic interesting. Also, feel free to share the article, it would mean a lot!

See you in the next issue!

However, when progress is lacking, the majority of us begin to doubt our abilities. We think that everything is pointless and that every attempt we make is futile. Often, the lack of progress leads to a lack of motivation for that activity. Ultimately, the same lack of progress can also lead to quitting that activity altogether.

What we need to realize deep within ourselves is that the main reason for the absence of progress is the absence of activity. As long as we are working on something, even if there is no obvious progress to us, it is still there. It may be invisible, but it does not mean it doesn't exist.

In this article, I will focus on progress - why it is important and how to track it. I will look at it through the lens of the sport I engage in, the perspective of sport climbing. However, you don't have to stop there; you can take the practices I mention here and apply them to other activities and aspects of what interests you.

Why is progress important?

As I mentioned earlier, the desire for progress is what fundamentally drives us. To run faster, jump higher, be better than our opponents, know more about a specific topic... The examples are countless. When that desire for progress is fulfilled, and we are aware of the progress we have made, an even greater desire for improvement and advancement emerges. This leads us into an endless loop of desiring progress, which leads to progress, which further fuels the desire for that activity. And so the cycle continues.

Until that endless loop is interrupted by the absence of progress. Or at least the absence from our perspective.

Let me give you an example (whether it's personal or not is not that important). Let's say we want to start climbing (it doesn't matter if it's from personal experience or not 😅). We tried it and enjoyed it, but we don't know how to proceed. What is the first step? First, we might feel despair because we are so weak while everyone around us is incredibly strong. Just kidding, of course. We look at things from a different perspective, maybe start training more actively with a coach or on our own. And so, after some time, we realize that what seemed difficult for us at the beginning is now too easy.

However, as you can imagine, we don't want to stop there. We continue climbing and getting stronger. This time, the progress is even better, and we feel even more powerful. That's it, let's keep going! Determined, we set ourselves a goal to climb something that we didn't even consider when we started. We try the route day after day, but without success. We think that we are not strong enough, so we increase our training. Over time, we realize that we are nowhere near the top of the route. That might shake us a little, or maybe not, but we don't give up. Now, as time goes on, we notice that the progress is becoming weaker and weaker... Instead of completing the route we set out to conquer in a very short time, like we did at the beginning - none of that happens.

At that moment, as well-known Serbian actor Petar Božović would say - things start to fall apart. We begin to doubt our strength and dedication. Unaware that before this route we can't climb now, we've already climbed a vast majority of very difficult routes for beginners! All we have in our minds is the thought that there has been no progress in the past few weeks. We slowly start losing motivation to continue. We stop setting aside time for climbing. Not only that, but we gradually weaken and eventually completely stop training and climbing.

Whether this example is trivial or not, it shows us that the desire for progress is what drives us forward. And progress, as a result, is merely a trigger for further advancement and improvement. What is important to remember is that regardless of what climbing represents in your context, progress is always there. When we stop completely, progress also ceases.

How to prevent activity from stopping?

The answer to this question can be quite simple - by tracking that activity. When we start tracking the activity we're engaged in, we create a mechanism that reminds us of our progress. We create a place where we can see it in black and white, whether we have or haven't made progress.

The progress curve is always ascending, regardless of the current feeling. As long as the activity is present, the trend is always upward. When we look at things from the very beginning up to this moment, we have made a lot of progress. Despite feeling like we're not progressing at the moment, that feeling is incorrect. Although physically immeasurable and invisible, progress can manifest as improved concentration, thinking patterns, new perspectives... Choose for yourself...

How do I track my progress?

I have been involved in the story of sport climbing for a long time. I remember my beginnings and the days when I progressed rapidly in a short period of time. Then the progress became smaller and smaller. It became less visible. My desire for climbing remained, and fortunately, despite various events, it is still there.

What keeps me engaged in the whole story is the fact that I have learned to see my progress even when I haven't tracked it in black and white. However, as the years go by, I increasingly have to remind myself how I felt during training sessions last week or a month ago.

That's why I turned to tracking my training sessions and performance.

There are many ways to do it, and the simplest one is to use a notebook or a computer program (such as LibreOffice Calc or Excel) where we record our plans and results. That's the simplest way. However, me being a geek who often spends more time following and researching ways to do something instead of actually doing it, I also wasted several hours looking for the best way to track training sessions. The way that suits me.

After watching numerous videos by various gym bros on the topic of how to best manage training sessions, I came across the simplest and cheapest method - the Notion application!

A small note - this is not an advertisement for Notion, claiming it's an ultra, mega, super cool application that will solve all your problems. It's not that kind of advertisement, and I don't think Notion is such an application. This is just one way of using the Notion that I found suitable for myself. I still think that the application itself is too complex, for example, if you want to create a simple note on your phone. For now, I only use it as a tool to help me track my training sessions.

It looks simple, consisting of two tabs. One is a calendar, and the other is a table. In the calendar, I enter my training plan for the upcoming week. Those same training sessions are automatically projected into the table in the next tab. When I complete or don't complete a training session, I simply enter the results (or reasons why I didn't finish), how I felt, etc. And that's it!

Below are the screenshots of my Notion document.

Now, since I'm still not proficient in the Notion ecosystem, and I'm not sure how to share a page template, if you want to learn more about it, feel free to reach out to me in the comments, and I can send you the document template. You can then use it for your own needs, modify it, whatever works for you.

Conclusions

To keep it short, I believe I've talked more than enough about progress. To give you an idea of how much I emphasized it, just think that I've mentioned the word "progress" or its root a total of 38 times in this text! Now, let me highlight only the most important points. Or, as they say, TL;DR (too long; didn't read).

• The only reason for the absence of progress is the absence of activity.
• Progress is present even when we can't see it with the naked eye, in the form of thoughts, understanding, comprehension...
• Understanding that progress always exists makes things easier and keeps us more motivated.
• Tracking progress is a mechanism that can further motivate us and provide a clear insight that we are actually progressing.

That's all for now. If you have any further questions or if I've said something incorrectly, please leave a comment below or contact me directly.

Jokes aside, this article will not be about the Go programming language. This article will be about the game of Go, one of the most popular strategic games in Asia, a game that few people here in the West know anything about.

Just like in everything I do, I'm not an expert in this either. This is the story of a beginner who became fascinated by the patterns, connections, and symbolism of the game, and the process of overcoming oneself through the game. This is the story of how I accidentally discovered and became interested in a game called Go (Igo).

The Beginning

The homepage of my YouTube profile is filled with climbing videos. Thanks to some strange setting in some algorithm, one of the recommendations was a documentary film from 2016 - AlphaGo. I didn't know what it was about, and since I was relatively idle at that moment and craving the dopamine that the information age provides us with - I clicked on the link.

After about ten minutes, I understood what it was about. It was a documentary about how a computer succeeded in defeating a human in Go for the first time. Hmm, didn't a computer beat the world's best chess player a long time ago? What does Go have to do with it now? These were some of the questions that, truth be told, I didn't ask myself during the film. Instead, I kept watching, completely unaware of the story behind it all. As the story unfolded, I learned more.

I found out that the computer defeated a human in chess thanks to the technique of brute-force search^[1] - a technique that a computer uses to solve a specific problem by trying every possible alternative before providing its final answer. But as I further learned, that's not possible in Go! Why? Because with every move in Go, it opens up over 200+ moves, then another 200+ moves. This eventually leads to an inconceivable number of possibilities. And the computer cannot find a solution using this method. A different approach must be applied. The approach of artificial intelligence.

Without going into too much detail about the film, which I highly recommend watching, I just want to briefly mention the feeling that the film evoked in me. I was fascinated. The world that was revealed to me, the culture of the game that the Far East nurtures and develops. And since I had previously been influenced by the Far East in my interests (origami, manga, anime movies, Korean cinema), it was a natural course of events for me to become interested in the game of Go.

Short History

Now a little about the history of the game (or how I copied and paraphrased everything from Wikipedia).^[2]

In brief, Go is an abstract strategic board game in which two players compete for territory. The oldest written record of the game dates back to the fourth century BCE in the Chronicles of the Zuo. Later, this game was also described in Confucius's books. It was called Yi in China, and today it is known as Weiqi, which roughly translates to "encirclement board game."

According to legend, the mythical Chinese Emperor Yao (2337-2258 BCE) told his advisor Shun to design a game that would teach his son Danzhu wisdom and good behavior. Some other theories suggest that this game actually originated from Chinese tribal rulers and generals who marked positions on a map with stones to plan their attacks.

Later, this game spread to Korea (where it is called Baduk) and Japan (Igo or Go). Today, these three countries are referred to as the Three Kingdoms of Go, because in those cultures, Go is nurtured like football in England (justifiably) and football in Serbia (unjustifiably). In the Far East, it was considered one of the Four Noble Arts, alongside calligraphy, playing the lute, and painting.

"Basic" Rules

Let's compare Go with the popular game in the West - chess. Unlike chess, where each player has 16 different pieces with different movements and 6 pieces with unique movements, Go has two types of pieces called stones, which are black and white. They have the same shape. However, there are many more of these stones - 181 black and 180 white. Once a stone is placed on the board, it cannot be moved. Stones are placed on intersections, not in squares like chess pieces. The ways they move are simple - a stone is placed on an intersection and remains there. What is more complex than chess is how these stones can be combined to achieve the goal.

The goal in chess is to defeat the opponent, while in Go, the goal is to capture more territory. And that's what attracted me the most to the game - that pacifistic aspect. It's not necessarily about fighting against others (although that is also an option), but simply playing. As it often turns out, this is a game against oneself. Knowing oneself and one's only opponent, I realized that this is a good game for me.

In summary, apart from the turn order where moves are made alternately and the black player goes first, and the scoring rules, there are only two rules in Go:

1. Rule of liberty - This rule states that every stone remaining on the board must have at least one open point (liberty) directly orthogonally adjacent (above, below, left, or right) or must be part of a group that has at least one liberty beside it. Stones or groups of stones that lose their last liberty are removed from the board.
2. The Ko rule - It prohibits repeating a previous board position by placing stones. Such a move is forbidden for a simple reason - it would result in endless loop.

In the GIF (or /dʒɪf/, as some would say) below, there is a graphical representation of how the board and the course of the game look like.

If you want to learn more about the game and its rules, visit this YouTube channel; it's full of excellent videos and tutorials for beginners.

What next?

That's how I, thanks to the YouTube algorithm, delved into the world of Go. Whether it was accidental or not, I don't want to get into that, but I'm grateful for it. Besides the reasons I mentioned earlier, the beauty of the game itself is what kept me interested. To be honest, I still don't fully understand that beauty, and I don't know if I ever will. But I enjoy what it evokes in me and how it makes me see things from a different perspective.

If you watched and enjoyed the documentary above, here are a few more links to interesting content about the game of Go:

• An interesting and useful video about the history of the game, available on this link.
• Another documentary about the game of Go and human dedication to it.
• Lastly, but not least, there are anime and manga with Go as their main theme - Hikaru no Go.

Enjoy!

Footnotes