Cloud Platforms: AWS vs Azure vs GCP

Selecting a cloud provider is a strategic product decision, not only an infrastructure choice. The right platform should match your team skills, growth targets, compliance needs, and cost model.

AWS is often preferred for broad service coverage and global maturity. It offers strong flexibility for startups that need many deployment options, large-scale elasticity, and a deep ecosystem of tools and partners.

Azure is usually a strong fit for enterprises and B2B products that already rely on Microsoft systems. Identity integration, security tooling, and hybrid-cloud options are common reasons teams choose Azure.

GCP is frequently selected for analytics-heavy products and data engineering workloads. Its strengths in data pipelines, machine learning tooling, and developer-friendly interfaces can be attractive for product teams focused on insights.

Cost planning should include more than compute pricing. Teams should evaluate storage patterns, network egress, observability tooling, and long-term operational overhead. A cheaper instance type can still become expensive if architecture is inefficient.

A practical selection framework is to score each cloud against your top priorities: speed to launch, reliability, governance, data capabilities, and total cost of ownership. This avoids emotionally driven decisions.

Many SaaS companies also adopt a phased approach: start with one provider to move quickly, then reassess architecture and portability as scale and complexity increase.