@brianhhough: The EC2 instance kept running. The AI agents kept thinking. And the cloud bill kept climbing. 😭 At the @amazonwebservices AWS Hero Summit, I asked AWS Machine Learning Hero Vivek Raja about the biggest cloud nightmares of his career. He had two: 1. An EC2 instance that stayed running far longer than it should have—and left a serious dent in the bill. 2. Testing an agent platform across different models, prompts, and configurations… only to realize how quickly experimentation costs can add up. The bigger lesson? Cloud resources don’t know when your experiment is over. You have to give them boundaries. Before your next cloud or AI experiment: ✅ Set budgets and billing alerts first ✅ Automatically stop idle development resources ✅ Give temporary infrastructure an expiration date ✅ Cap model retries, tokens, and concurrency ✅ Test on a smaller evaluation set before scaling up ✅ Track the cost of each experiment—not just the monthly bill The goal isn’t to experiment less. It’s to make every experiment measurable, intentional, and bounded. Because “I’ll remember to shut it down later” might be the most expensive sentence in cloud computing 📈💸😭 What resource or experiment has surprised you the most on your cloud bill? Tell us below! 👇 Follow us for more real-world cloud nightmares and lessons 👋 #AWS #CloudComputing #MachineLearning #AIAgents #FinOps #TechStackPlaybook
