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We migrated to the cloud and it costs more than the servers did

Lift-and-shift moves fixed hardware costs into variable cloud pricing without changing the shape of the workload. The savings come from architecture, not from the migration itself.

By Marcus Hale
We migrated to the cloud and it costs more than the servers did

The migration finished, the data centre contract ended, and the monthly bill exceeds what the hardware cost. This is a normal outcome of lift-and-shift, and it is not evidence the migration was wrong. It reflects a straightforward mismatch: cloud pricing rewards workloads that scale with demand, and a copied on-premise architecture does not.

01Owned hardware and rented capacity price differently

A purchased server has an up-front cost and then runs at any utilisation for no additional charge. Idle capacity is already paid for, so nobody optimises it. In the cloud that same idle capacity is billed hourly, and the habits formed around owned hardware become directly expensive.

On-premise sizing also assumes peak plus headroom, because adding capacity took weeks. Cloud instances sized the same way run at low average utilisation permanently, paying peak prices around the clock for capacity used a few hours a day.

Habit from on-premiseCloud consequence
Size for peak plus headroomPaying peak capacity continuously
Environments left runningBilled hourly regardless of use
Local storage assumed freeStorage, IOPS and snapshots all billed
Internal network freeCross-zone transfer charged
Backups to local diskSnapshot storage accumulates
No per-team cost visibilityNobody sees what they provision
Why the bill exceeds expectations

02Right-size against measured usage

Instances copied from on-premise specifications are typically far larger than needed. Measure actual CPU and memory utilisation over a representative fortnight and resize to fit observed peaks with sensible headroom rather than to match the previous hardware.

This is normally the largest single saving available and carries low risk, because it is reversible in minutes. Teams routinely find average utilisation in the low teens across their fleet, which means most of the spend produces nothing.

03Turn off what nobody uses

Non-production environments commonly run continuously while being used during working hours on weekdays - roughly a quarter of the week. Scheduling them off outside those hours removes most of their cost with no risk to production.

Orphaned resources are the other half: unattached volumes, idle load balancers, unassociated addresses and old snapshots. These accumulate through normal work and are invisible unless someone looks for them deliberately.

ActionEffortTypical return
Delete orphaned resourcesLowSmall but immediate
Schedule non-production off-hoursLowLarge on those environments
Right-size instancesLowLarge
Storage lifecycle policiesLowGrows over time
Commitments after stabilisingMediumSignificant on steady baseline
Re-architect for elasticityHighLargest, but slowest
Optimisation by effort and return

04Commit only after usage is stable

Reserved capacity and savings plans offer meaningful discounts in exchange for committing to a level of usage over one or three years. Committing before right-sizing locks in the oversized footprint you were about to reduce, which is a common and expensive sequencing error.

Right-size first, observe the stable baseline, then commit to that baseline while leaving variable load on demand. Committing to peak rather than baseline removes the flexibility the commitment was meant to complement.

05The structural fix is visibility

Cost grows when no team sees the consequence of what it provisions. Tagging by team and service, with a monthly figure each team can see, changes provisioning behaviour more reliably than any centralised optimisation effort.

Without that, a cleanup buys perhaps six months before the same accumulation recurs, because the mechanism that produced it is untouched. The organisational change is what makes the technical work durable.

Topics

cloud migration cost morelift and shift expensivecloud cost optimisation after migrationreserved instances savings plansrightsizing cloud instances

Marcus Hale

Lead Architect · SyncTrix

Writes about the engineering decisions behind production systems - architecture, delivery and the trade-offs that only show up at scale.

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