When we finally split our bill by environment, development, staging and preview environments were 38 percent of total cloud spend. Most of it ran 24 hours a day for people who work 8. This guide covers schedules, ephemeral environments, right-sizing, data copies and guardrails.
A one-off data backfill filled our Postgres RDS instance, storage autoscaling grew it from 400 GB to 2 TB, and after we deleted the temporary tables the bill stayed. RDS allocated storage cannot be reduced in place. We shrank it with a blue/green switchover and capped autoscaling.
Our LLM bill tripled in one month and nobody could say which feature caused it. This guide covers what we built since: per-feature token accounting, prompt and response caching, model routing, output limits, batch processing and budgets with alerts.
Our GPU node pool stayed at eight nodes from Friday night to Monday morning with almost no GPU usage. The cluster autoscaler refused to remove them: notebook pods with local storage, a bare debug pod and a kube-system pod without a PDB. Fixing each blocker cut GPU spend by 38 percent.
A new operations dashboard refreshed every 15 minutes and our BigQuery bill jumped by 9,000 USD in a month. Each tile ran SELECT star over a 40 TB events table without a partition filter. Column pruning, required partition filters and a bytes billed cap fixed it.
Our app said the media bucket held 4 TB, while S3 billed us for 31 TB. Versioning kept every overwritten and deleted object as a noncurrent version, and failed multipart uploads left invisible parts behind. Lifecycle rules brought billed storage down to 5.2 TB.
A VPC line item we had never paid attention to reached 2,400 USD a month. Since February 2024, AWS charges for every public IPv4 address, in use or idle. Our EKS nodes, idle Elastic IPs and load balancers in many subnets added up. Inventory and cleanup cut it by 70 percent.
Our CloudWatch line went from 2,100 to 6,900 USD in a month without new services. Debug logging enabled during an incident was never turned off, and every load balancer health check produced a log line. Finding the top log groups and fixing levels cut ingestion by 81 percent.