Cut your cloud bill in half: practical cost optimization strategies
Real techniques we've used to reduce cloud infrastructure costs by 40–60% for growing companies, without sacrificing reliability or performance.
Cloud cost overruns are one of the most common engineering problems we encounter with growing companies. The pattern is consistent: infrastructure is provisioned quickly to meet demand, optimized slowly if ever, and costs compound as the business scales.
The fastest win in most environments is right-sizing compute. The default is to over-provision — teams choose large instance types to avoid performance problems. In practice, most services run at 20–40% CPU utilization. Right-sizing to match actual utilization typically saves 30–40% immediately.
Reserved instances and savings plans are the next lever. Committing to one or three-year terms for stable workloads can cut compute costs by 30–60% versus on-demand pricing. The key is to separate stable baseline capacity (reserve it) from variable burst capacity (keep on-demand).
Database optimization often yields the largest single savings. Many teams run large database instances for workloads that could be served by a fraction of the capacity, or pay for multi-AZ deployments for development and staging environments that don't need that availability.
Data transfer costs are frequently underestimated. Moving data between regions, from cloud to on-premise, or out to the internet can represent 15–25% of total cloud spend. Architectural changes that minimize cross-region data movement often have an outsized impact.