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Neocloud

Migrating to Neocloud: A Practical Strategy for Regulated Enterprises

Moving workloads from hyperscalers to neoclouds requires careful planning. Here's the migration strategy that minimizes risk while maximizing cost savings and sovereignty benefits.

Luca Berton7 min read

You won't migrate everything to a neocloud overnight. You shouldn't. The right strategy is selective migration: identify workloads where neoclouds deliver clear advantages (cost, sovereignty, simplicity) and migrate those first. Keep workloads on hyperscalers where the ecosystem value justifies the cost.

Migration Candidate Assessment

Good Neocloud Candidates

  • Kubernetes workloads with standard APIs (no proprietary service dependencies)
  • GPU training and inference jobs
  • Stateless applications with container-based deployment
  • Development and staging environments
  • Workloads requiring EU data sovereignty
  • High-compute, low-integration workloads

Keep on Hyperscaler

  • Workloads deeply integrated with managed services (RDS, DynamoDB, BigQuery)
  • Applications using serverless (Lambda, Cloud Functions)
  • Workloads requiring specific compliance certifications only hyperscalers have
  • Applications with global edge requirements

Migration Phases

Phase 1: Non-Production (Month 1-2)

Migrate development and staging environments first. Low risk, high learning value. Validate networking, storage, monitoring, and deployment pipelines on the neocloud platform. Build team familiarity.

Phase 2: Stateless Production Workloads (Month 3-4)

Migrate stateless applications that can be deployed in parallel. Run on both platforms briefly. Validate performance, reliability, and monitoring. Cut over when confident.

Phase 3: Stateful and Sensitive Workloads (Month 5-8)

Migrate databases, persistent storage workloads, and sovereignty-sensitive data. Requires careful data migration planning, replication setup, and validation. Run parallel for extended period.

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Infrastructure-as-Code as Migration Enabler

If your infrastructure is defined as code (Terraform, Kubernetes manifests, Helm charts), migration is dramatically easier. Refactor cloud-specific modules to use neocloud equivalents. Keep the application layer unchanged. GitOps ensures consistency across environments.

Cost Tracking

Track cost savings continuously: document hyperscaler cost baseline per workload, measure neocloud cost for equivalent workload, account for migration effort and parallel running costs. Typical outcome: 30-50% reduction for suitable workloads, with sovereignty benefits as a bonus.

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neocloud
cloud migration
multi-cloud
cost optimization
infrastructure strategy

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18+ years experience · Ex-Red Hat & Dell · Speaker at KubeCon EU 2026

Luca Berton

Written by

Luca Berton

CEO at Open Empower. 18+ years building enterprise infrastructure at JPMorgan Chase, Red Hat & Dell. Author of 9 technical books. Speaker at Red Hat Summit and KubeCon EU 2026. Instructor on Coursera, Pluralsight & Udemy.

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