AWS, Azure, GCP, serverless, Kubernetes and modern cloud architecture.
My AWS bill for February was $3,417. My expected bill was around $180. Here's exactly what happened, why AWS billing is so hard to predict, and the specific change that fixed it.
Everyone in the cloud community acts like Kubernetes is the obvious default. It isn't. For most projects, K8s adds complexity that doesn't pay for itself until you reach a specific scale you probably haven't hit yet.
I've run production workloads on all three major clouds over the past four years. This is my honest, experience-based comparison — not marketing copy, not benchmark charts.
Our AWS bill was $4,200/month for a workload that should have cost about $1,600. The fix took two days of configuration changes and saved us $31,000 over the next year.
I was a serverless evangelist for two years. Then I ran a real production workload on Lambda and learned some expensive lessons about cold starts, timeout limits, and vendor lock-in.
We decided to migrate from our managed hosting to AWS in Q4. Three months of downtime incidents, one near-catastrophic data access issue, and one extremely uncomfortable conversation with investors later, here's what we learned.
I've been running Kubernetes in production since 2022. Here's what the blog posts don't tell you: the operational surprises, the 2am incidents, and the things I wish I'd known before I started.
Last November our traffic spiked 12x in 90 minutes. We caught a cascade failure in under four minutes and resolved it before 95% of users noticed. Here's the monitoring setup that made that possible.