The 30-Day Cloud Cost Cleanup
Cloud bills compound. By year two of any AWS account, 20-40% of the monthly spend is on resources nobody remembers naming. A structured 30-day cleanup pulls it back without touching application code.
Weekly cost-cleanup checklist
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Frequently asked questions
How much can a 30-day cloud cost cleanup actually save?
In environments that haven't been cleaned, a focused four-week cleanup typically recovers 20-40% of monthly spend — roughly 5-15% from eliminating idle resources, 10-20% from right-sizing, and the rest from commitment discounts. None of it requires changing application code.
Do I need to change application code to cut my cloud bill?
No. The entire 30-day plan — deleting idle resources, right-sizing instances, migrating storage, and buying commitments — operates on infrastructure, not code. That is the point: it recovers 20-40% without touching a single application code path.
What's the fastest cloud waste to eliminate first?
Idle EBS volumes sitting in the `available` state, unattached Elastic IPs, orphaned snapshots, and load balancers with zero traffic for 30 days. These are resources you can simply turn off, and week 2 handles them before you touch any running infrastructure.
Should I migrate from gp2 to gp3 EBS volumes?
Yes. gp3 is faster, lets you provision IOPS independently of size, and is roughly 20% cheaper at the same provisioned size. The article's stance is blunt: there is no legitimate reason to launch a new gp2 volume.
How much of my baseline should Savings Plans cover?
Cover 70-80% of your steady-state spend on EC2, Fargate, and Lambda with a Compute Savings Plan, leaving the remaining 20-30% flexible for growth or migration. For RDS, which has no Savings Plans, use one-year no-upfront Reserved Instances for about 30% off list.
How often should I run a cloud cost cleanup?
Quarterly, not once. Environments accumulate waste and teams forget which knobs they turned, so a cleanup every Q1 and Q3 keeps the bill close to its true workload cost. Document each round's before/after numbers to build the institutional memory that speeds up the next one.
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