Cloud bills tend to grow quietly: an oversized database here, an idle environment there, logs retained forever. The good news is that most waste can be removed without touching reliability at all.
Make cost visible
Tag every resource by team, service and environment. Publish cost dashboards alongside performance dashboards. Teams optimize what they can see.
Rightsize with data
Use utilization metrics to rightsize compute and databases. Enable autoscaling with sensible floors. Schedule non-production environments to shut down outside working hours.
Commit where usage is stable
Savings plans and reserved capacity make sense for predictable baseline load. Use spot or preemptible instances for fault-tolerant workloads like batch processing and CI runners.
Fix architecture hotspots
- Cross-zone and egress data transfer
- Chatty service-to-service calls
- Unbounded log and metric retention
- Over-provisioned Kubernetes requests
- Storage tiers that never move cold data
Protect reliability with SLOs
Define service level objectives before optimizing. Every cost change is then evaluated against error budgets, so savings never come at the expense of the customer experience.
The cheapest system is the one designed to use exactly what it needs.