The "which cloud" question usually gets answered by inertia. Before a migration is the right time to actually revisit it.
Most teams end up on whichever provider a founding engineer happened to know, not the one that best fits the workload. That's not necessarily wrong — switching later is expensive — but it's worth making the choice deliberately, especially if you're already planning a migration and the cost of re-deciding is close to zero.
The broadest service catalog and the largest market share by a wide margin — if a managed service exists, AWS probably has a version of it.
The deepest and most mature ecosystem: the largest talent pool, the most third-party tooling, the most Stack Overflow answers when something breaks.
The tradeoff is sprawl — with hundreds of services and a genuinely complex pricing model, it's easy to over-provision or misconfigure without disciplined governance.
The strongest fit if your organization already runs on Microsoft — Active Directory, .NET, Office 365 — since integration with those systems is genuinely first-class, not bolted on.
Strong enterprise and compliance tooling, which matters for regulated industries and large organizations with existing Microsoft enterprise agreements.
Less of an advantage if you're not already in the Microsoft ecosystem — the benefit is concentrated for a specific kind of organization.
The strongest data and ML tooling of the three — BigQuery and Vertex AI are frequently the reason teams choose GCP specifically, not incidentally.
Often the most straightforward pricing model of the three, with fewer surprise line items.
The smallest market share of the three, which means a smaller specialist talent pool and somewhat thinner third-party tooling than AWS.
The provider comparison above matters less than how well your workload maps to portable primitives before you move it. Architectures built on containers, standard SQL databases, and provider-agnostic storage migrate — and re-migrate, if you ever need to — far more easily than architectures deeply wired into one provider's proprietary managed services. That's a design decision worth making deliberately during a migration, not something to discover after you're already committed.
Cost comparisons between providers are also less useful in the abstract than they look. None of the three is reliably cheapest across the board — it depends on your specific workload shape, whether you use committed-use discounts, and how disciplined your resource management is day to day. A well-governed setup on the "expensive" provider usually beats a poorly-governed one on the "cheap" provider.
Sometimes, but not by default. Multi-cloud adds real operational complexity — duplicated tooling, more surface area to secure — and it's usually only worth it for specific reasons like regulatory requirements or avoiding a single point of vendor failure for a critical system, not as a general best practice.
None of them is reliably cheapest in general — it depends entirely on your workload shape, committed-use discounts, and how disciplined your resource management is. Sloppy usage costs more on any provider than careful usage does on the "expensive" one.
It depends on how tightly your architecture is coupled to provider-specific services. Workloads built on portable primitives (containers, standard databases) migrate more easily than ones deeply wired into a provider's proprietary managed services — which is a real design tradeoff worth making deliberately, not by accident.
All three support the major compliance frameworks — the difference is usually in your team's existing familiarity and which provider's audit tooling fits your process, not a hard technical gap.
A focused evaluation against your actual workload, cost model, and compliance needs typically takes one to two weeks — longer than that and you're usually optimizing past the point of useful signal.
A cloud migration that felt risky until every step was mapped in advance — no downtime, lower bills, less worry.
Read the case study