Why multi-cloud is no longer optional for growing SaaS

Three years ago, the standard advice was simple: pick one cloud, go deep, and resist the urge to spread your complexity. That advice made sense when hyperscalers were largely interchangeable. Today, it doesn't.

AWS dominates in raw service breadth. GCP leads in data and ML infrastructure — BigQuery, Vertex AI, and TPU access are genuinely differentiated. Azure is the default choice for enterprises already embedded in Microsoft's ecosystem. If your product touches all three user segments, you're already operating in a multi-cloud world whether you planned for it or not.

The hidden cost of lock-in

The danger isn't that AWS will disappear. It's subtler: pricing changes, SLA downgrades, service discontinuation, and — most often — a competitor building on a cloud that has a 30% cost advantage for your specific workload. When your entire infrastructure is a single provider, your negotiating position is zero.

We've seen clients come to us after an egress-driven cloud bill tripled in a year. Migrating under pressure is the worst time to migrate. The teams that avoid this pain designed for portability from day one.

What multi-cloud actually means in practice

Multi-cloud doesn't mean running everything everywhere. That's a fast path to operational chaos. What it means in practice:

• Run your primary workload on your preferred provider
• Use best-in-class managed services where the specialisation justifies it (e.g., GCP for ML pipelines, AWS for Lambda-heavy event processing)
• Design your data layer to be portable — avoid proprietary storage formats where possible
• Use a cloud-agnostic orchestration layer: Kubernetes, Terraform, or Pulumi

The architecture decisions that matter

The key leverage points are at the boundaries: how you store data, how you move it, and how you invoke compute. Standardise on open formats (Parquet, Avro, Arrow) for analytical data. Use a message queue abstraction (Kafka, Pub/Sub, or SQS behind an interface) so your producers and consumers don't care which cloud they're on. And containerise everything — not just for Kubernetes, but so your workloads can run anywhere a container runtime exists.

The goal isn't to avoid a preferred cloud. It's to ensure that switching — or running a workload elsewhere — is a week of work, not a six-month project.

A practical starting point

For most teams, the right first step is an infrastructure audit. Map every managed service you use to its equivalent on one other provider. If there's no equivalent, that's a lock-in risk worth noting. You don't have to act on it immediately — but you should price the risk.

Multi-cloud is not about running two of everything. It's about building systems that earn you options. And in a market where cloud economics shift year to year, options are worth more than engineers often account for.