Kubernetes migration, without the downtime.
Move monoliths, virtual machines, ECS and legacy PaaS onto Kubernetes in planned waves, with GitOps, infrastructure-as-code and a tested rollback at every step. One committed leap to a platform your team owns, no big-bang risk, no legacy left behind.
Built for scale-ups and established engineering teams.
Kubernetes migration earns its place when the platform you have is slowing the business down. These are the situations where a move pays for itself, whether you are a fast-growing product company or an established business modernising off older infrastructure.
Outgrowing single VMs or PaaS
Deploys are manual, scaling is vertical, and one noisy service takes the whole box with it. You need isolation, horizontal scaling and repeatable deploys.
Escaping ECS or bespoke orchestration
ECS, hand-rolled scripts or a snowflake VM fleet have hit their ceiling, and hiring for them is getting harder than hiring for Kubernetes.
Breaking up a monolith
You are carving services out of a monolith and want a platform that supports independent deploys, autoscaling and clear ownership boundaries.
Standardising a fragmented estate
Different teams deploy in different ways. A single Kubernetes platform with golden paths replaces tribal knowledge with a paved road.
Preparing for AI and GPU workloads
You are heading towards model serving and GPU scheduling, and want the substrate ready before the AI roadmap lands on it.
Reliability and cost under pressure
The cloud bill and the incident count are both climbing. Kubernetes with autoscaling and observability gives you a platform you can defend on both.
Incremental waves, never a big-bang switch.
The riskiest way to move to Kubernetes is all at once. We migrate in waves: the new cluster runs alongside the old platform, workloads move a few at a time, and traffic shifts gradually behind a blue-green or canary strategy. Every wave is reversible until you are confident, so the migration can pause, roll back or resume without drama.
Principles we hold to on every migration.
- Stateless workloads move first to prove the platform; stateful services are planned separately with backups and restore drills.
- Everything is code in your repositories: infrastructure-as-code, manifests, pipelines and GitOps definitions, reviewed like any other change.
- Rollback is tested, not assumed. If a wave misbehaves, traffic returns to the previous platform in minutes.
- Security and network policy are designed in from the first namespace, not bolted on after cutover.
- Your engineers work alongside us the whole way, so the platform is understood, not just delivered.
What a Kubernetes migration covers.
Discovery & wave plan
Workload inventory, dependency mapping, statefulness and compliance constraints, turned into a ranked, scheduled migration plan.
Containerisation
Dockerfiles, base-image hardening, multi-stage builds and a registry strategy for services that are not yet containerised.
Cluster foundations
Managed Kubernetes on EKS or GKE, or hybrid, with networking, ingress, secrets, RBAC and namespace design as code.
GitOps delivery
Argo CD or Flux, Helm or Kustomize, and CI wiring so deploys become boring, auditable and self-service.
Cutover & rollback
Blue-green or canary traffic shifting, health gates, error-budget checks and a rehearsed rollback for each wave.
Handover or managed run
Runbooks, observability and team pairing for a clean handover, or an agreed managed operating model. You own the code either way.
Migration is one engagement within our Kubernetes consulting practice, and usually part of a broader cloud transformation. Once the platform is live, teams tighten spend with Kubernetes cost optimization and build self-service on top with platform engineering.
Our Kubernetes migration process.
Four phases, planned backwards from a safe cutover. The architecture review confirms exact scope and timeline before anything moves.
Discovery
Workload inventory, dependencies, statefulness, traffic patterns and compliance constraints, ending in a concrete wave plan.
Containerise & build
Images, manifests, secrets strategy and CI wiring, with the cluster foundations stood up as infrastructure-as-code.
Cutover in waves
Blue-green or canary migration, one wave at a time, with health gates and a tested rollback at every step.
Operate & own
Handover with runbooks and GitOps, or an agreed managed operating model. Everything lives in your repositories.
The tools we actually use.
No reseller agreements and no partner quota. Recommendations follow your workloads. Typical building blocks on a migration:
Clusters
Amazon EKS, Google Kubernetes Engine (GKE), and hybrid or on-prem Kubernetes where data residency or existing hardware requires it.
Infrastructure as code
Terraform or OpenTofu for cloud and cluster provisioning, with modular, reviewed, version-controlled definitions.
GitOps & packaging
Argo CD or Flux for continuous delivery, Helm or Kustomize for packaging, and progressive delivery for safe rollouts.
Autoscaling
Horizontal Pod Autoscaler, Cluster Autoscaler or Karpenter, and right-sized requests and limits so scaling is predictable.
Observability
Prometheus, Grafana and OpenTelemetry for metrics, logs and traces, with SLOs and alerts wired before cutover.
Security baseline
Network policies, RBAC, secrets management, image scanning and CIS-benchmark-aligned hardening from day one.
Kubernetes migration FAQ.
How do you migrate to Kubernetes without downtime?
We migrate workload by workload behind a blue-green or canary strategy. Traffic shifts gradually from the old platform to the new cluster, health and error budgets are watched at each step, and every wave has a tested rollback. Because we cut over in increments rather than a single big-bang switch, most services move with no user-visible downtime, and the few that need a maintenance window get a short, scheduled one agreed in advance.
Can you migrate from ECS, VMs or a monolith to Kubernetes?
Yes. The common starting points are Amazon ECS, plain EC2 or GCE virtual machines, Heroku or legacy PaaS, and monoliths that need to be containerised first. We inventory the workloads, containerise what is not already, and move them onto managed Kubernetes (EKS, GKE) or a hybrid cluster, keeping stateful services and data stores handled explicitly rather than lifted blindly.
How long does a Kubernetes migration take?
A typical mid-size migration runs six to twelve weeks from discovery to final cutover, depending on the number of workloads, how much statefulness is involved, and compliance constraints. The initial architecture review returns a concrete, ranked wave plan with a timeline for your specific estate rather than a generic estimate.
Will we be locked into your team after the migration?
No. Everything ships as code in your repositories: Terraform or OpenTofu, Helm or Kustomize manifests, GitOps definitions and runbooks. You can take full ownership at handover, or keep us on for managed operations. Both paths are first-class, and neither depends on a proprietary tool only we can run.
How do you handle databases and stateful workloads during migration?
Stateful services are planned separately from stateless ones. We decide per data store whether to run it on managed cloud services, migrate it with replication and a cutover window, or run it in-cluster with operators and persistent volumes. Backups, restore drills and a rollback path are agreed before any data moves, so a migration never puts your data in a position it cannot return from.
Planning a move to Kubernetes?
Start with the readiness scorecard, or book a free 30-minute architecture call. A senior engineer reviews your workloads and returns a ranked, wave-by-wave migration plan.