Have you ever thought about that we who work with tech can influence the climate impact of the systems we develop? This presentation is about how we can improve the carbon footprint of the services that we build.

1. Two years ago, I received
a new pair of glasses
Hi!
Photo by Bud Helisson on Unsplash

4. Energy consumption
depends on:
● Sending and receiving data
● Client screen usage
● Client and server CPU activity

5. The emissions
from electricity varies a
lot between countries

7. Emissions also come from
the development process
● Travel
● Office
● Test environments
● etc
Photo by Marvin Meyer on Unsplash

8. How much carbon
dioxide emissions do we
cause?

9. Example calculation from
a project at SVT Play

10. Example calculation
● Input
○ Amount of data transferred over networks
○ Screen/device time per type
○ Server running time
○ Location of clients

11. 10g carbon dioxide per
hour of streaming

12. Source: max.se

14. 4 329 tonnes CO2e/year
=
9 620 x ✈ Sthlm - NY
Source: flysas.com

15. Then what?

16. Stop autoplaying
recommendations
=
saved 200 tonnes of
carbon dioxide per year

17. AVIF encoded images
=
saved 2 tonnes of carbon
dioxide per year

18. What can we do to
minimize the carbon
footprint?

19. Reduce waisted data

20. Optimize encoding
of video content
4K: 17Mb
1080p: 9Mb
720p: 4Mb

21. Use responsive
images 169Kb
63Kb
37Kb
1920x1920
1024x1024
720x720
<img srcset="sprout-480w.jpg 480w,
sprout-800w.jpg 800w"
sizes="(max-width: 600px) 480px,
800px"
src="sprout-800w.jpg"
alt="Green sprout">

22. Use modern image
formats such
as AVIF or WebP
AVIF: 50Kb
WEBP: 100Kb
JPG: 169Kb
<picture>
<source type="image/avif" srcset="sprout.avif">
<source type="image/webp"
srcset="sprout.webp">
<img src="sprout.jpeg" alt="Green sprout">
</picture>

23. Use reasonable
image quality levels
Q=70: 169Kb
Q=90: 221Kb
Q=100: 478Kb

24. Source httparchive.org

25. Minimize JavaScript, avoid
bloated libraries, use
treeshaking etc

26. Use gzip compression for
html, json, css etc

27. Check your Cache-Control
headers

28. Block bots

29. Reduce waisted servers

30. Choose serverless or
autoscaling if you can
● With serverless, the machines can be more
efficiently utilized
● Autoscaling to zero means no energy
consumption when it's not need

31. Stop unused test
environments
● Serverless
● Autoscale to zero
● Or schedule them to stop when not needed
Photo by John Smit on Unsplash

32. Optimize CPU utilization
● Performance tuning
● Minimize CPU allocation
● Tune garbage collection settings
● etc

33. Machine learning
● Choose simple models instead of deep learning
when possible
● Train iteratively instead of retraining from
scratch periodically
● Use transfer learning

34. Check your partners
Check energy
efficiency of your
data center
Check energy
efficiency of any
SaaS/PaaS/IaaS used
Check energy
efficiency of your
CDN provider

35. In general, hyper
scale data centers
are much more
efficient than
small local data
centers
This Photo by Unknown author is licensed under CC BY.

36. Reduce waisted screen time

37. Good UX design can make a big
difference

38. Design efficient workflows to
minimize waisted screen time

39. Some features can reduce waist

42. Dark mode

43. Make climate impact a factor in
your decisions and priorities

44. Summary
1. Many small savings can make a big
difference
2. Reduce waisted data
3. Reduce waisted servers
4. Reduce waisted screen time
5. Make climate impact a factor
in your decisions and priorities
Photo by Bud Helisson on Unsplash

45. Attributions & sources
● https://unsplash.com/photos/kqguzgvYrtM
● https://unsplash.com/photos/8BNO4HUQYRw
● https://unsplash.com/photos/SYTO3xs06fU
● https://unsplash.com/photos/hRI8f-2WyDw
● https://app.electricitymap.org/map
● https://www.flysas.com/en/sustainability/emissio
n-calculator/
● https://www.max.se/maten/meny/maltider/
Photo by Михаил Павленко on
Unsplash