The problem
The client ran 40+ services on hand-configured EC2 instances. Deploys were manual, slow and risky, scaling was painful, and there was no consistent way to ship. Engineering velocity was bottlenecked on infrastructure.
What CloudForge built
- 1Designed a multi-account AWS landing zone with isolated prod and staging boundaries.
- 2Built a production-grade EKS platform with Terraform, including autoscaling, spot capacity, and network policies.
- 3Implemented GitOps delivery with ArgoCD and a reusable Helm chart library for golden paths.
- 4Introduced a service mesh (Istio) for mTLS, traffic shifting and progressive canary rollouts.
- 5Migrated services incrementally behind weighted DNS, validating each cutover before proceeding.
The outcome
Every service moved with zero customer-facing downtime. Deploy time dropped 85%, infra spend fell 31% through right-sizing and spot, and the team now self-serves new services via golden paths.
Why migration sequencing mattered
A Kubernetes migration is an operating-model change as much as an infrastructure change. The target cluster needs a repeatable application contract, observable deployment behavior and a recovery path before production traffic moves. Incremental cutovers preserve evidence and keep rollback decisions available while the new platform earns trust.
Cost reduction is evaluated beside placement, disruption and service health. Lower node spend is not a successful outcome if the platform cannot absorb a failed zone, a deployment surge or an interruption of discounted capacity.
Related CloudForge guidance
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