Post-mortems. Benchmarks. The kind of FinOps detail you actually need before you run the migration. One post a week, no fluff.
Terraform, OpenTofu, or Pulumi, the tool matters less than how you use it. Here's what actually works in production: state management, module design, testing layers, secrets hygiene, and drift detection in 2026.
5% of Azure VMs run at under 15% CPU, and you're paying for 100% of them. Here's how to right-size using p95 metrics, stack Reserved Instances with Hybrid Benefit, and cut non-prod VM costs by 73% with scheduling.
Your non-prod environments ran all weekend and were billed for every hour. Here's the case for automated scheduling, how it works in Kubernetes, what breaks, and how teams recover 60%+ of idle cloud spend
On-demand compute costs are nearly identical across AWS, Azure, and GCP. The real differences are in egress, block storage, Kubernetes control plane fees, and commitment flexibility. Here's the 2026 breakdown before it shows up on your invoice.
Most Kubernetes clusters run at 35% CPU utilization, and nobody revisits node sizing after launch. Here's the measurement process, blue-green rotation pattern, and 72-hour soak checklist to right-size safely without production incidents.
Per-pod pricing turns maxReplicas into a cost dial and punishes autoscaling. Here's why fixed per-environment pricing lets Kubernetes work the way it was designed and what that means for reliability.
Cloud spend is heading to $1 trillion in 2026, but 27% of it, $182 billion, is wasted. Here's what the latest data from Flexera, Gartner, and FinOps Foundation says about where the money goes and what actually works to recover it.
Surprise cloud bills don't announce themselves. Learn how to set up cost anomaly detection on AWS, GCP, and Azure to catch spikes in hours, not 30 days later when the invoice arrives.
Monitoring tells you something is wrong. Observability tells you why. Learn the difference between logs, metrics, and traces and how to layer observability on top of your existing monitoring stack without starting over.
PU is the wrong scaling signal for queue workers, batch jobs, and async services. Learn how KEDA scales on queue depth, Kafka lag, Prometheus metrics, and cron schedules to cut idle compute costs by up to 73%.
GKE Autopilot isn't always cheaper than Standard. Learn exactly when each mode wins, how Autopilot's minimum pod billing surprises teams, and which workload profiles justify the switch.
SOC 2 audits fail on missing evidence, not missing controls. Here's the exact checklist cloud engineering teams need to pass CC6, CC7, and CC8 without surprises during fieldwork.
One post a week. Sundays. No "10 ways to think about cloud" listicles, just the engineering and FinOps notes we'd want to read.
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