Serverless vs VMs: What Irish Teams Should Pick in 2026
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The serverless versus VMs debate is really a cost debate, and it has a clean answer: VMs charge for time, serverless charges for use. An Irish business paying for servers that sit idle at 3am, on weekends, and between bursts is paying for absence. This guide is the decision, workload by workload.
How the two models actually bill
- VMs (Compute Engine): a rented computer, on all the time, billed all the time, with discounts for committed use. Right for steady, predictable, always-on load.
- Serverless (Cloud Run, Cloud Functions): your code runs on demand and scales to zero when idle; you pay per request and per compute second. Right for spiky, event-driven, or lightly used workloads.
New Google Cloud accounts start with $300 in free credits and 20+ always free products, which is a free way to test both models on your own workload.
The decision table
| Workload | Pick | Why |
|---|---|---|
| Website or API with variable traffic | Serverless | Scales to zero; burst-proof |
| Nightly reports and scheduled jobs | Serverless | Bills only while running |
| Event handling: uploads, webhooks, queues | Serverless | Per-event billing |
| Steady 24/7 database or app server | VM with committed use | Predictable load, lower unit cost |
| Legacy app with OS dependencies | VM | Refactor later, run now |
The migration pattern
Move one service at a time, prove feature parity, then cut over. Our VM to serverless case study shows the standard outcome: the same application, meaningfully lower cost, zero performance loss. Our event-driven functions case study shows the same discipline for the jobs and webhooks every business accumulates.
The honest caveats
Serverless needs a small mindset shift: stateless design, per-request thinking, and attention to cold starts for latency-sensitive paths. None of it is exotic, and the cloud cost guide covers the governance that keeps either choice honest on the bill.
How we decide it for clients
We model both options on your actual usage data before recommending one, and we run the migration end to end under our infrastructure service. If you want the two-model comparison for your workload, book a call.
Next: Data centres in Ireland: how the boom affects your business
Frequently asked questions
What is the difference between serverless and VMs?
A VM is a rented computer that runs all the time and bills all the time. Serverless runs your code on demand and scales to zero when idle, billing only for actual usage.
Is serverless always cheaper?
For spiky or lightly used workloads, yes, often dramatically, because idle costs nothing. For steady 24/7 high load, committed-use VMs are usually cheaper. Match the model to the workload.
Which Google Cloud services are serverless?
Cloud Run for containerized apps, Cloud Functions for event-driven code, and the managed data services. They all scale to zero or to managed tiers, and new accounts start with $300 in credits.
What should stay on VMs?
Workloads with steady predictable load, specific OS or kernel requirements, licensed software, and legacy applications that are not worth refactoring yet.
Is migrating from VMs to serverless risky?
Not with a staged approach: one service at a time, feature parity first, then cutover. Our VM to serverless case study shows the typical outcome: lower cost, no performance loss.
What does a serverless migration cost?
It is a scoped project: a small app migrates in weeks. The ongoing savings usually pay for the migration quickly, and the cost guide covers the numbers.