#finops

Is your company's data center consumption contributing to carbon emissions? Europe and other regions have experienced several extreme heatwaves due to climate change and other factors. Data centers have been also an ongoing discussion due to their environmental impact. #cybersecurity #datacenters #climate #finops #cloud #aws #sustainability #climatechange

Today's #Devops Challenge: hit the #Finops button, turn a bunch of shit off, and then watch Devs scramble and cry because their "untagged" Cloud resources got turned off, and they dont know why..... (because untagged dev resources shouldnt run 24/7). Side Quest achieved: found a #bitcoin mining instance in ap-southeast-2 that no one thought anyone would see. Turned it off & the dev complained ALMOST immediately. "Alright, well Ill dredge the configs on that server to see what it does, ok?"

So my engineer (who is my problem child), admitted today that he can only work in #azure environments, and refuses to work in #aws and #gcp environments. Because he doesnt understand them, how they work, or how to build stuff in them. Despite his constant use of #claude to build #IaC #terragrunt. So console and env awareness shouldnt matter right? #Devops #Cloudops #Revops #FinOps #WhatTheFuckEverOps As everyone can guess (I am the at the bottom of the list in the pic).

What is everyone doing today? and how? #trans #queer #lgbtqia #geek #nerd #devops #cloudops #finops

I accidentally built a control plane for coding agents. It started as a simple goal: GitHub AI Credits arrived, CopeLimit started watching the meter, and being a Scot I was suddenly very much doing Invoice Avoidance Driven Development. Make AI coding agents produce smaller PRs, follow boundaries, validate properly, and stop treating “add JSON output” as permission to invent a new architectural religion. That forced the real question: Are we governing AI-assisted engineering, or just writing better prompts and hoping? My answer: prompting is not the control plane. AADLC became the lifecycle. cARL became the repo-native governance layer. CopeLimit made the cost visible. Headroom points toward the optimization layer. cARRIE is the future resource-insights engine. The benchmark runs made the pattern clearer: Same repo. Same workflow. Same acceptance criteria. No human steering. Sonnet 4.6: 441 credits, 34m58s, 7/7 accepted. GPT-5.4: 708 credits, 58m48s, 7/7 accepted. Sonnet plan + GPT execute: 581 credits, 48m18s, 7/7 accepted. The interesting question was not “which model is best?” It was: What shape of delegation does this work need? Because the model matters. The delegation system matters more. https://cirriustech.co.uk/blog/prompting-was-never-the-control-plane/ #AI #SoftwareEngineering #DevSecOps #GitHubCopilot #AgenticAI #FinOps