AWS vs Azure vs GCP for Cloud Migration: How to Actually Choose in 2026
Blog post from Qovery
Choosing among AWS, Azure, and Google Cloud for a 2026 migration depends primarily on an organization’s existing licences, technical skills, data location, network-egress needs, and regional compliance requirements rather than market share or basic infrastructure capabilities. Azure is presented as the strongest fit for Microsoft-centric estates because Entra ID integration and Azure Hybrid Benefit can substantially reduce Windows Server and SQL Server costs, while Google Cloud is positioned for Kubernetes-native, analytics, and AI-focused environments through GKE Autopilot, BigQuery, per-second billing, and automatic sustained-use discounts; AWS is suited to organizations seeking the broadest managed-service catalog, partner ecosystem, and hiring pool. All three providers offer free migration tools and now waive egress charges for customers leaving their platforms, but migration budgets remain driven by engineering labor, parallel operations, licensing, ongoing egress, and post-migration operating models. For container workloads, EKS, AKS, and GKE are considered production-capable, with differences centered more on automation and ecosystem fit than control-plane costs. The discussion argues that the most consequential forms of vendor lock-in are data dependencies and proprietary deployment workflows, recommending containers, Kubernetes, infrastructure as code, portable interfaces, and deliberate use of managed services to preserve flexibility. It also promotes Qovery as a bring-your-own-cloud developer platform intended to provide a consistent deployment workflow across multiple clouds while retaining customer ownership of cloud accounts, billing, and negotiated discounts.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Kubernetes | 30 | 4,363 | 405 | 103 | +23% |
| Developer Experience | 6 | 641 | 275 | 91 | +30% |
| Secrets Management | 4 | 2,046 | 504 | 139 | -11% |
| Platform Engineering | 2 | 1,691 | 347 | 96 | +40% |
| Serverless | 2 | 1,224 | 281 | 103 | +39% |
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