Cloud NAT charges a per-GiB data processing fee on all traffic routed through the gateway — both inbound responses and outbound requests. For high-throughput workloads such as web crawlers, data pipelines, container image pulls, and API-heavy microservices, these per-GiB charges can become the dominant cost component of the NAT gateway, far exceeding the hourly gateway and IP address fees. In environments processing large volumes of data monthly, data processing fees can represent the vast majority of total Cloud NAT spend, making the managed service significantly more expensive than alternative NAT architectures when comparing direct infrastructure costs alone.

The core issue is that Cloud NAT applies its data processing fee to traffic that would otherwise be free or low-cost — particularly inbound traffic (ingress), which Google Cloud does not normally charge for. When private instances pull large datasets, download container images, or receive high volumes of API responses through Cloud NAT, each GiB incurs the processing fee. Organizations can avoid these per-GiB charges by deploying self-managed NAT instances on Compute Engine — VMs configured with IP forwarding and NAT translation rules — where the only direct cost is the compute instance itself. However, this trade-off introduces substantial operational complexity, ongoing maintenance burden, and availability risk: self-managed NAT requires manual configuration, network expertise, continuous monitoring, security patching, high-availability planning, capacity management, incident response procedures, and troubleshooting capabilities that Cloud NAT handles automatically. The engineering time required for initial implementation, the ongoing operational labor for maintenance, and the business impact of potential service disruptions must all be factored into the total cost of ownership.

This optimization is highly workload-specific and situational rather than universally applicable or recommended. The break-even point depends not only on monthly traffic volume, the number of VMs behind the gateway, and the chosen instance type for self-managed NAT, but also on the fully-loaded cost of engineering time, the organization's operational maturity, the criticality of affected workloads, and the tolerance for increased operational risk. In most cases, the operational overhead, complexity, and risk of self-managed NAT infrastructure outweigh the direct cost savings unless data processing fees are exceptionally high and sustained over time. Organizations should perform a comprehensive total cost of ownership analysis before migrating, accounting for both direct infrastructure costs and indirect costs such as engineering effort, operational burden, monitoring infrastructure, and the business risk of connectivity failures. This is not a straightforward cost optimization — it is a deliberate trade-off between managed service convenience and operational control that only makes sense at very high traffic volumes where the cost differential is substantial enough to justify the additional complexity and risk.

Each Cloud NAT gateway provisioned in GCP incurs hourly charges for each external IP address attached, regardless of whether traffic is flowing through the gateway. In many environments, NAT configurations are created for temporary access (e.g., one-off updates, patching windows, or ephemeral resources) and are never cleaned up. If no traffic is flowing, these NAT gateways remain idle yet continue to generate charges due to reserved IPs and persistent gateway configuration. This is especially common in non-production environments or when legacy configurations are forgotten.