Offrampcloud exit calculator

Worked example · Google Cloud

A Google Cloud project on Compute Engine and Cloud SQL.

Core and memory hours pooled per machine family, a regional Cloud SQL instance, Cloud Storage and internet egress, with credits and tax set aside. Read through the way the calculator reads it: the bill, what it becomes on Hetzner, the verdict, and what would change it.

The bill

$2,406 a month across 9 services after setting aside support plan, tax, credit. The six largest lines:

ServiceGradeTodayOn HetznerChange
Compute EngineEasy$1,270$428saves $842
Cloud StorageEasy$400$69saves $331
Cloud SQLModerate$251$64saves $187
MemorystoreModerate$141~$49saves $92
BigQueryHard$120~$42saves $78
Cloud LoggingModerate$90~$18saves $72

~ marks a rule-of-thumb ratio; the rest is priced from usage in the file.

What it becomes on Hetzner

  • 3 servers: 1× AX102-1, 1× CX43, 1× CX53
  • $717/mo for servers, storage and traffic
  • 52 h/mo of engineer time, $3,863
  • $25,560 one-off, no payback at this net

Extra cost per year

$26,083

Not worth moving at this size. Hetzner costs more once someone is paid 52 hours a month to run it.

Grow first: at this size the hours decide, not the hardware. 3 of your 9 services move easily; 1 is hard. 78% of the Hetzner figure is priced from your usage; the rest is ratio-priced services and engineer time, which is where the range comes from.

Likely range $98 to $6,197 more a month. Hetzner list prices of 17 Oct 2026, default assumptions.

The same file on nine destinations

Net per year after engineer time, best first. No destination pays for this account; Hetzner loses least.

Hetzner−$26,083 over
Hetzner (US)−$32,858 over
OVHcloud−$33,704 over
Scaleway−$33,795 over
Vultr−$35,636 over
Akamai (Linode)−$36,462 over
UpCloud−$37,416 over
DigitalOcean−$40,188 over
Exoscale−$49,535 over

What would change the answer

  • Engineer time. 52 hours a month at $75/h is $3,863, 84% of the destination figure. Halve the rate or fold the work into an existing team and the verdict moves first.
  • Scale. Engineer time grows slowly with the number of servers; hardware grows with the bill. The same mix at three times the size usually flips a marginal answer.
  • Moving only part of it. The first wave (foundation: storage, traffic, edge) is Cloud Storage, Cloud Load Balancing: $344/mo for about 1 engineer days, with the databases left where they are.
  • The hard services. BigQuery has no equivalent at the destination; keeping them on Google Cloud removes their engineer time and their risk from the plan.

Every one of these is a setting in the report. Open the example and change them.