How to cut AWS spend by 30–50% without breaking production

No magic, no generic rightsizing. It is the specific order of levers we pull with clients paying inflated bills out of habit, not need.

The AWS bill of most mid-sized companies in LATAM has 30–50% of pure fat. That is not an exaggeration. It is what we see when we run a serious FinOps analysis. What follows is the exact order we apply — not because it is trendy, but because it is the order that avoids breaking production.

Step 1: visibility before action

Without consistent tags (Environment, Owner, Project, CostCenter) you cannot allocate costs. Without allocating costs you cannot negotiate with internal teams. Week one: massive tag patch + enable Cost Allocation Tags in Billing. Then dashboards with cost per project.

Step 2: turn off what nobody uses

Orphan EBS snapshots, unassigned elastic IPs, QA environments running 24/7 when used only during business hours, RDS running with no traffic. This is the easiest one and no one does it — because nobody wants to be the person who turns something off and breaks another team. The simple rule: 30 days without traffic, it gets turned off after notice.

Step 3: Reserved Instances and Savings Plans, the right way

The trap: companies buy three-year RIs on specific instance types and end up locked to hardware that will be obsolete. Recommendation: Compute Savings Plans (not EC2-specific), one year, covering 60–70% of baseline. The rest stays on-demand for flexibility.

Step 4: rightsizing with data, not intuition

AWS Compute Optimizer and Trusted Advisor tell you exactly which instances are oversized. Caveat: dropping from m5.2xlarge to m5.large needs 7 days of observation under real load, not a Friday at 5pm. Do it with maintenance windows and automatic rollback.

Step 5: Spot and autoscaling for tolerant workloads

Processing workers, builds, batch jobs, ML training — all of that should run on Spot. Karpenter on Kubernetes automates it elegantly. Typical reduction: 60–80% on that portion of the bill.

Step 6: the uncomfortable conversation — architecture

Sometimes the bill is inflated because the architecture is wrong. Lambda invoking itself in a loop due to a misfiltered event, RDS oversized because someone enabled Multi-AZ "just in case", cross-region data egress because services are placed poorly. This requires refactor — but the ROI is brutal.

How we help at Athrun Data Intelligence

Free initial FinOps audit: in a 30-minute call we show you what percentage of your bill is likely recoverable and where to start. If it fits, we execute by sprints with weekly metrics.