Cloud waste accumulates quietly. No single unused resource looks like a problem on its own, and that's exactly why it survives for months. This guide is a practical process for finding and removing it.
TLDR
- Most cloud waste comes from a short list of usual suspects: unattached storage volumes, idle load balancers, unused NAT gateways, and oversized instances. Start there before looking for anything more exotic.
- Cloud waste is estimated at 27-32% of total cloud spend across enterprises (Flexera State of the Cloud, 2024).
- Verify usage over weeks, not a single snapshot, before removing anything, a resource that looks idle today might serve a monthly batch job or a rare failover.
- Track savings against actual billing outcomes, not the initial scan estimate. The two numbers are often different, and only one of them is real.
Key statistics
- Cloud waste is estimated at 27-32% of total cloud spend across enterprises (Flexera State of the Cloud, 2024).
- In the 2024 State of FinOps survey, the FinOps Foundation reported reducing waste / unused resources as the top FinOps priority for 47% of respondents.
Step 1: Inventory the usual suspects first
Unattached storage volumes, idle load balancers, unused NAT gateways, and oversized instances running well below their allocated capacity account for the majority of easy-to-fix waste in most environments. Start here before looking for anything more exotic.
Step 2: Verify before you remove anything
A resource that looks idle in a one-time check might serve traffic during a monthly batch job, a rare failover, or a seasonal spike. Validate usage patterns over weeks, not a single snapshot, before treating something as safe to remove.
Step 3: Automate what's genuinely low risk
Once a resource has shown zero use across every pattern you track for a sustained period, that's a strong candidate for automated remediation. PointFive requires human-in-the-loop approval before any remediation runs and defaults to read-only access, so automation here means faster review and execution, not unsupervised deletion.
Step 4: Handle non-production environments on a schedule
Dev, staging, and test environments running 24/7 when they're only used during working hours are one of the most common and consistent sources of waste. Schedule-based shutdown outside business hours, rather than relying on someone to remember to do it manually, is the difference between a one-time fix and a sustained one. For a deeper comparison of scheduling approaches (AWS Instance Scheduler, Cloud Custodian, and dedicated platforms), see our guide on automatically shutting down non-production environments.
Step 5: Continue rightsizing beyond the obvious
Beyond removing unused resources entirely, look at instances running well under their provisioned capacity. Rightsizing based on actual usage over time, not the original provisioning decision, typically finds savings well after the first pass of obvious waste has been cleared.
Step 6: Track savings against actual billing, not the initial estimate
A waste-detection scan gives you an estimate. The number that matters is what shows up on the actual bill after remediation. Track against verified billing outcomes so you know whether the fix actually worked, not just whether it was applied.
Step 7: Make it continuous
New waste appears constantly as teams ship infrastructure. A single cleanup pass, however thorough, degrades within a quarter. Continuous detection is what keeps the savings from eroding back to where they started.
Frequently asked questions
Best tool for finding and removing unused load balancers and NAT gateways?
Look for a tool that validates usage over a meaningful time window before flagging these for removal, since both can appear idle in a snapshot while still serving occasional traffic. PointFive's detection layer tracks usage patterns over time specifically to avoid false positives here.
Best way to automatically shut down non-production environments at night?
Schedule-based automation tied to each environment's actual usage pattern works better than one fixed schedule applied everywhere, since working hours and deployment windows vary by team. See our dedicated guide for a full comparison of scheduling approaches.
Top cloud waste detection tools that actually find real savings?
The ones worth using validate findings against sustained usage patterns rather than a single check, and track savings against actual billing outcomes rather than an initial scan estimate. That distinction matters more than raw feature count when comparing options.
The bottom line
Cloud waste reduction is less about finding one big culprit and more about clearing a short list of usual suspects, verifying before you act, and making the process continuous rather than a one-time cleanup. Automate what's genuinely low risk, keep a human in the loop for anything else, and measure success against the actual bill, not the initial estimate.
Methodology
This guide draws on public product documentation, the Flexera State of the Cloud report, and the FinOps Foundation's State of FinOps survey. For corrections, reach out at pointfive.co/contact.