Questions related to cloud cost optimization can begin with some very straightforward concerns:
- Are the instances too big?
- Is the workload running efficiently?
- Are the proper storage classes being used?
- Is the architecture scalable?
Those questions matter. But some of the fastest savings are often hidden in a less visible category: resources that are no longer used, but still exist.
A virtual machine is removed, but its attached disk stays behind. A test environment is shut down, but the load balancer remains active. Snapshots are created for safety, but no one defines how long they should be retained. Logs lose operational value, but continue to sit in expensive storage classes.
These are phantom cloud costs.
They rarely create incidents. They do not affect application performance. They do not block deployments. In many cases, they are not visible to product teams at all. But they continue to appear in the monthly cloud bill as fixed, recurring expenses.
Why Phantom Costs Appear
Phantom costs are typically generated by gaps in the lifecycle of infrastructure.
In fast-paced engineering contexts, assets are continuously being generated, altered, and destroyed. People will provision virtual machines for testing purposes, set up temporary environments for developing certain features, make backups prior to deploying something, and even configure load balancers for conducting experiments.
The problem is that deletion is often incomplete.
When a compute instance is terminated, the storage volume attached to it may remain active. In AWS, for example, EBS volumes can continue to generate charges even after the EC2 instance they support is gone. The same pattern appears with snapshots, disks, IP addresses, load balancers, and old storage buckets.
The application may no longer depend on the resource. The team may no longer remember why it was created. But the billing system still sees an active asset.
This is why phantom costs are difficult to detect manually. They are not always technically “unused” from the cloud provider’s perspective. They are simply disconnected from current business value.
Common Sources of Hidden Infrastructure Waste
Unattached volumes are probably the most common example. A VM can be deleted while cleaning up, but the volume itself is still there. These kinds of orphaned volumes pile up over time.
Old snapshots are another frequent source of waste. Backups are important, but without retention rules, they can grow indefinitely. A snapshot created for a migration, release, or emergency rollback can remain for months or years after it is no longer needed.
Idle load balancers also create recurring charges. Teams often remove the application environment, but leave networking components behind. Since load balancers do not always look expensive in isolation, they are easy to ignore until they appear across many environments.
Logs and archival data can become expensive when they stay in the wrong storage class. Operational logs may need to be highly available for a short period, but after that, they should usually move into cheaper archive tiers. Without lifecycle automation, storage costs continue to grow quietly.
The same applies to unused public IPs, abandoned storage buckets, old container images, outdated artifacts, and temporary environments that were never fully decommissioned.
None of these problems requires a broken architecture. They require missing ownership and missing cleanup logic.
Why This Matters for FinOps
FinOps goes beyond big decisions regarding architecture and complicated forecast models. FinOps also involves hygiene operations.
A business can have an excellent cloud strategy but still end up losing money from uncontrolled leftovers. Such costs are particularly dangerous since they come off as negligible when looked at individually. An orphaned volume will not affect your budget. A neglected snapshot will not raise any alarm bells. An unused load balancer will make no difference.
But at scale, these fixed costs compound.
In large cloud environments, phantom resources can represent a meaningful share of monthly spend. They also make reporting less accurate because money is being spent on infrastructure that is no longer connected to a product, customer, team, or workload.
This creates two problems.
First, the company pays for resources that do not create value.
Second, teams lose trust in cloud cost data because the bill includes items no one can explain.
That is why phantom cost management should be part of any mature FinOps practice.
How to Reduce Phantom Cloud Costs
The solution does not usually require redesigning the application architecture.
It starts with visibility and automation.
The first step is to detect unattached and orphaned resources on a recurring basis. This can be done through cloud-native tooling, scheduled scripts, or FinOps platforms that identify disks, snapshots, IPs, load balancers, and storage assets without active ownership.
The second step is to define lifecycle policies. For example, S3 Lifecycle Policies can automatically move old logs into cheaper storage classes or delete data after a defined retention period. Similar lifecycle rules should exist for snapshots, backups, artifacts, and temporary environments.
Ownership is the next step. Each storage asset, backup, load balancer, and environment must be tagged so that they can identify which team owns them, which product or application uses them, what kind of environment they are in, and their current lifecycle state.
Governance during engineering processes is the final component. Infrastructure as Code will mandate tagging along with the default setting for the lifecycle. CI/CD pipelines can set up the environments with a deadline set. Monitoring can alert the team to their idleness or orphans.
Cleanup then becomes an operational activity.
The Business Impact
The value of removing phantom costs is that savings are often immediate and low-risk.
Unlike deeper architectural optimization, deleting unused disks, old snapshots, idle load balancers, or outdated logs does not change application behavior. It does not require refactoring services. It does not affect customer-facing features.
It simply removes fixed costs that should not exist anymore.
For CFOs and business leaders, this means cloud spend becomes cleaner and easier to explain. For engineering teams, it means cost optimization does not have to start with painful trade-offs. For platform teams, it creates a foundation for stronger governance and better resource ownership.In many organizations, phantom cost cleanup is one of the first FinOps wins because it proves that cloud cost management can create measurable savings without slowing delivery.
Conclusion
Phantom cloud costs are the infrastructure leftovers no one uses, but the company still pays for.
These orphaned resources crop up whenever the resources have outlived their usefulness to the workload, team, or environment they were designed for. They lurk inside orphaned volumes, old snapshots, idle load balancers, orphaned IPs, orphaned logs, orphaned buckets, and orphaned environments.
The solution is not only about cleanup; it is about lifecycle management.
Scan for orphaned resources regularly. Define retention rules. Automate storage transition strategies. Tag all resources with ownership and lifecycle data. Make cleanup an inherent part of CI/CD and IaC workflows.
Before you overhaul your architecture or slash your engineering budgets, just consider asking a simple question:
What are we still paying for but do not use anymore?
Elizaveta Sokolova
