Phased Cloud Migration: The 5-Layer Tool Stack That Keeps Deploys Fast and Uptime Boring

A phased cloud migration is presented as a wave-based process in which old and new platforms operate in parallel behind a routing layer, allowing teams to shift traffic gradually and roll back through traffic changes rather than redeployments. The approach requires five complementary layers: infrastructure provisioning through tools such as OpenTofu or Terraform, continuous delivery using GitOps tools including Argo CD or Flux, traffic management through weighted routing or canary tools, change-data-capture replication services for databases, and developer self-service to preserve fast deployment workflows. The article argues that migration efforts often protect uptime while overlooking developer velocity, recommending that teams baseline and monitor DORA metrics, service SLOs, costs, and incident rates from the outset. It proposes progressing from foundational infrastructure and internal services to customer-facing workloads, data cutover, and eventual decommissioning, with rehearsed rollback plans and defined exit criteria for each wave. It also advises budgeting for two to four months of parallel operations, managing egress and idle-environment costs, avoiding configuration drift and untested rollbacks, and using internal developer platforms such as Qovery alongside—not instead of—infrastructure, GitOps, and cloud migration tools.

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