Hardware reaching end of life in your own data centre, new requirements from digital and AI projects: there are many triggers for the step into the cloud. How well a cloud migration succeeds, however, is rarely decided only at the destination. The decisive factors are the strategy per application and a network architecture that takes security and performance into account from the start.
What is cloud migration?
Cloud migration refers to the planned relocation of applications and data from your own data centres into cloud environments, for example to AWS, Azure or Google Cloud. The term covers individual relocation projects as well as multi-year transformation programmes. Depending on the target model, systems will in future run on infrastructure services (IaaS), on platform services (PaaS) or be replaced by SaaS offerings. Hybrid architectures also count: parts of the environment remain local or with a regional operator, others move into the public cloud. A migration is thus far more than a server move. It changes operational processes and responsibilities, and it poses anew the question of how network and security are organised. Alongside technology, the drivers are usually economic reasons, such as predictable costs and shorter provisioning times for new environments.
How it works
An approach in clearly separated phases has proven itself:
- Assessment and inventory: At the beginning stands a complete overview of applications and their dependencies. Which systems communicate with each other, where does personal data reside, which services are business-critical? This transparency determines the sequence and risk of the migration.
- Strategy according to the 6R model: For each application, a fundamental decision is made: rehost (move unchanged), replatform (adapt moderately), refactor (rebuild), repurchase (replace with SaaS), retire (shut down) or retain (keep for now). The model prevents blanket decisions across the entire portfolio.
- Target architecture and network: Before the first move, the landing zone, identity concept, network design and security policies are created. A private connection over dedicated lines or a cloud exchange keeps critical traffic away from the public internet and ensures stable latencies; the foundations for this are provided by Cloud Connectivity .
- Pilot migration: A limited, representative workload validates tools and processes, including rollback procedures. Only after that do larger waves begin.
- Migration in waves: Applications move in prioritised groups. Data replication in advance and clearly defined cutover windows keep downtime short.
- Operation and optimisation: After the move, the ongoing task begins: control costs, adjust resources, harden configurations and continuously monitor the environment.
Why it matters
Planned correctly, a migration changes considerably more than the location of servers:
- Scalability: capacity grows with demand, without lead time for hardware procurement. Load peaks can be absorbed, and test environments arise in minutes.
- Cost model: investments become usage-dependent operating costs. This improves allocation to projects, but demands active cost management.
- Security and compliance: cloud platforms come with encryption, logging, hardening guidelines and fine-grained permissions. Responsibility for configuration and data access nonetheless remains with the company.
- Modernisation: managed databases and AI services are available without building your own infrastructure and shorten development cycles.
- Site connectivity: branches and remote sites access central cloud services directly, instead of taking detours via your own data centre. This simplifies the WAN architecture and shortens response times.
- Resilience: distributed availability zones and automated backups improve recovery times in the event of a disruption.
Typical scenarios
The most common case is the data centre exit: the lease expires or the hardware reaches the end of its life, and an entire site relocates. Just as common are hybrid architectures in which production-related systems stay local while web applications and analytics platforms run in the public cloud. After acquisitions, separate IT environments have to grow together; the cloud then serves as a neutral target point for consolidated services. Those who build AI applications deliberately move data stores to where GPU capacity is available. In all cases, connectivity determines the user experience: sites need high-performance, secured paths into the cloud, and remote users need controlled access, for example via a SASE/SSE concept .
Lift-and-shift or modernisation?
The most important fundamental question concerns the depth of migration. Lift-and-shift (rehost) moves systems largely unchanged. This is fast and keeps the project risk small, but legacy burdens move along too: oversized machines and firewall rules that have grown over the years. The hoped-for cost advantages then often fail to materialise. Modernisation (replatform or refactor) adapts applications to cloud models, for example through managed databases or containers. The effort is higher, but in return operating costs fall and scaling improves noticeably. In practice, a mixed approach proves itself: non-critical systems via rehost, business-critical applications with a clear modernisation path. What is decisive is the deliberate choice per application rather than a blanket rule for the entire portfolio.
Working with KAEMI
KAEMI supports migration projects from the network side: with private cloud connectivity to the major platforms and with segmentation concepts for the target environment. Via Professional Services , KAEMI also supports you with assessment, target architecture, implementation and handover to operations. If you are planning a migration or want to secure an ongoing project, get in touch with us via Contact .