Moving to Google Cloud: a business owner's guide

Google Cloud is the smallest of the big three, and the usual question is blunt: why pick #3? The honest answer is that for a specific set of companies, data-heavy, ML-driven, or Kubernetes-first, GCP isn’t the third choice at all. Here’s how to tell if that’s you.

What Google Cloud is, in one minute

Google Cloud Platform holds roughly 11-13% of the global cloud market (AWS ~30%, Azure ~25%) and runs on the same planet-scale infrastructure as Search, YouTube, and Gmail. Like its rivals, it rents IaaS primitives, VMs, managed databases, storage, networking, plus managed services above them.

Where AWS differentiates on breadth and Azure on the Microsoft estate, GCP differentiates on engineering pedigree in three domains:

Data. BigQuery, a serverless data warehouse where you pay per query or per compute slot and never manage servers, remains the product competitors are measured against.
Kubernetes. Google invented Kubernetes; GKE is the reference-quality managed version, with real autopilot modes that reduce cluster babysitting.
Networking. A private global fiber backbone; features like global (not per-region) load balancers with a single anycast IP are unique among the three.

The trade: a service catalog maybe half AWS’s size, a noticeably smaller pool of engineers and partners, and enterprise sales/support motions that are still younger than Microsoft’s or Amazon’s.

The core services you’ll actually use

The primitives map cleanly to what you’d use elsewhere:

Service	What it is	AWS equivalent	Rough cost anchor
Compute Engine	Virtual servers; custom machine sizes (pick exact vCPU/RAM)	EC2	~$25-30/mo for 2 vCPU / 4 GB (e2-medium) before discounts
Cloud SQL	Managed PostgreSQL, MySQL, SQL Server	RDS	~$50-120/mo small tier; ~2× with high availability
Cloud Storage	Object storage with one API across hot→archive tiers	S3	~$0.020-0.023/GB-month standard
VPC	Your private network, notably global by default, spanning regions	VPC	Free itself; NAT and egress metered
IAM / Cloud Identity	Access control for people and services; pairs with Google Workspace	IAM	Free
GKE	Managed Kubernetes, standard or hands-off Autopilot mode	EKS	~$73/mo per cluster fee + nodes; Autopilot bills per pod

Two structural niceties worth knowing: GCP’s VPC is global (one network across regions, no peering gymnastics for multi-region setups), and projects give you clean per-app/per-environment isolation with their own billing, a tidy foundation for a landing zone. BigQuery is the add-on that most often justifies the whole platform: analysts querying terabytes with SQL, paying ~$6.25/TB scanned, zero infrastructure to run.

How GCP pricing actually behaves

Same model as the others, per-second compute, per-GB storage and transfer, with the same core gotchas: egress (~$0.085-0.12/GB to the internet), steady workloads left at on-demand rates, and forgotten resources. See avoiding bill shock for the discipline; the three-way comparison for numbers.

GCP-specific behavior worth knowing:

Sustained-use discounts are automatic. Run a VM most of the month and up to ~30% comes off with no commitment and no planning. The other clouds make you pre-commit for any discount; on GCP the lazy path is cheaper by default.
Committed-use discounts (1 or 3 years) reach 55-70% off, comparable to AWS/Azure commitments.
Custom machine types cut the “next size up” tax: need 6 vCPU / 20 GB? Build exactly that instead of paying for an 8/32 shape.
BigQuery bills per query. Powerful and dangerous: an analyst’s careless SELECT * over a large table costs real money. Set per-user and per-project quotas on day one.

Worked example, the same small stack we price on AWS:

Item	Spec	Monthly
2 × app servers	e2-medium, sustained-use	~$50
Database	Cloud SQL PostgreSQL, 2 vCPU HA	~$120
Storage	250 GB objects + 200 GB disks	~$27
Load balancer	Global HTTPS LB	~$22
NAT + egress	500 GB/mo	~$75
Total		≈ $294/mo

Within a rounding error of the AWS figure (~$316), which is the point. Between the big three, cost is rarely the deciding factor; fit is.

When Google Cloud is the right pick, and when it isn’t

GCP is the strong pick when:

Data/analytics is the business. If the roadmap says “warehouse, pipelines, ML on our data,” BigQuery + Vertex AI is the strongest integrated stack, and teams report shipping analytics with less platform babysitting than anywhere else.
You’re Kubernetes-first. If you’ve containerized (or plan to), GKE is the most polished managed Kubernetes, Autopilot mode gets you clusters without a platform team.
You’re a Google Workspace shop wanting one identity plane, the way Microsoft shops lean Azure.
Multi-region serving matters early. The global VPC and global load balancing make “serve users on three continents” architecturally simpler.

Look elsewhere first when:

You’re a Microsoft estate. Windows Server / SQL Server licensing math and Entra ID integration favor Azure decisively; GCP has no answer to Hybrid Benefit.
You need maximum hiring depth and ecosystem. AWS has several times the engineers, consultancies, and third-party integrations. For a plain web-app estate with no data/K8s angle, AWS’s ecosystem is the safer generic default.
You need niche managed services. The long tail of “AWS has a managed service for that” is real; on GCP you’ll self-manage more edge cases.

The lock-in note applies to GCP like everyone: BigQuery and Spanner are excellent and proprietary. Keep the portable layers (Postgres, Kubernetes, object storage) portable, and adopt proprietary services deliberately, where they pay.

How a migration to Google Cloud actually goes

The method is provider-agnostic, full detail in the migration roadmap:

Discovery (1-2 weeks). Inventory apps, servers, databases, dependencies; classify each workload per the 6 Rs. GCP’s Migration Center provides discovery and cost estimation against your on-prem inventory.
Landing zone (about a week). Organization → folders → projects hierarchy, global VPC design, IAM roles, org policies, centralized logging. GCP’s project model makes clean isolation easier than anywhere, use it.
Replicate and test (2-4 weeks per wave). Migrate to Virtual Machines streams running VMs from VMware/other clouds with minimal downtime; Database Migration Service handles PostgreSQL/MySQL moves with continuous replication, free for most homogeneous migrations.
Cutover. DNS or load-balancer switch in a rehearsed window with a tested rollback, the zero-downtime patterns apply unchanged.
Optimize. Right-size (GCP literally emails you recommendations), commit where usage is proven, quota BigQuery, review monthly.

Timelines match the other clouds: 4-8 weeks for one application, 4-9 months for a modest portfolio. The provider changes the tooling, not the physics.

FAQ

Is Google Cloud cheaper than AWS or Azure?

For comparable machines, list prices are within roughly ±15% across all three. GCP’s practical edge is sustained-use discounts, up to ~30% off compute applied automatically when a VM runs most of the month, with no upfront commitment, plus committed-use discounts of up to 55-70% if you do commit. You give some of that back in a smaller third-party and support ecosystem.

Is Google Cloud too small to bet on?

No. It’s a ~$50B+ annual run-rate business, profitable since 2023, running on the same global infrastructure as Google Search and YouTube. The fair concerns are a smaller talent and partner ecosystem than AWS/Azure and Google’s history of retiring consumer products, though cloud infrastructure carries deprecation policies measured in years, and core services have been stable for a decade.

When is GCP clearly the right choice?

When analytics or ML is core to the business (BigQuery is the strongest managed data warehouse), when your platform is Kubernetes-first (GKE is the reference implementation), or when you’re already deep in Google Workspace and want one identity plane. If none of those apply, evaluate AWS or Azure first.

How long does a migration to Google Cloud take?

The same as the other clouds: 4-8 weeks for one application (discovery, landing zone, replication via Migrate to Virtual Machines or Database Migration Service, cutover), 4-9 months for a 10-20 application portfolio. The provider changes the tooling, not the physics.

Trying to decide whether your data or Kubernetes story is strong enough to justify GCP over the default picks? Talk to a Webisoft cloud engineer, we’ll look at your actual workloads and tell you which cloud they favor, with the reasoning shown.