Speaker: Joel Lord @joel__lord

For more, see the table of contents

Code impact

• data centers 2% global electricity demand and 3% greenhouse gasses
• equivalent to irline ndustry
• planet has SLO – limit to what we can put in it
• Car 192g/km
• Domestic fight 255g/km
• SMS .014g
• Email 3g [I googled why high. It can be. .3 to 26 depending on how long to read/write]
• Tweet .2g
• Googe search .2g
• Fart – .2g

Factors

• CPU/GPU – GPU use more energy, but can perform for consistently – 12.4/38.2
• RAM – always used so more RAM you have, the more energy used – .3 per GB hour
• DIsk storage – .002 – per GB hour
• Network Transfer .027 – per GB
• Other (cooling, lighting, etc)

Formula includes

• Time
• PUE (power usage efficiency) – AWS 1.2, GCP 1.1, Azure (1.125). Only GCP publishes number. Others found somewhere. By contast, average is 1.67 including private data farms
• CI (carbon intensity) – region specific depending on source of power. NY 200g/kWh, Australlia (lots of coal) 880g/kWH, Quebec 14g/kWh
• Server tier – CPU, RAM, hard drive
• Utilization – ex: Atlas CLI/management API
• M30 on US East 1 for 24 hours – 401g CO2e (72K farts)
• https://github.com/joellord/atlas-co2

Notes

• GCP has a carbon footprint dashboard to get bar charts with info for your services
• Reduce energy using
• Return only top results
• Llower default quality
• Don’t autoplay video
• Use dark mode – less energy for dark pixels
• Package size matters – use JAM (JavaScript, APIs and markup) stack
• Derver rendered pages
• Reduce complexity – data access together should be stored together
• Green programming language – C, Rust, C++, Java, C#, JS best. TypeScript, PHP, Ruby, Python worse
• Migrate to the public cloud – they try to reduce costs by saving energy
• Serverless or autoscaling
• Cloud region matters – 80x differences
• Latency may be ok and then can use smaller nodes
• Pause servers when not in use – ex: weekend
• Better monitoring – can go to lower tier if needed
• Leerage XaaS solutions – (anything as a service)
• Use right tool – ex: do you need a database

My take

A lot of the beginning was about the impacts of climate change. I feel like the audience knew this part and would have liked to get to the part sooner. The comparisons were good and number of farts were fun. I would have liked more examples of the numbers. The end on things you can do was good.