Cloud Readiness Assessment
Which workloads should move, which should change first and which should stay — judged per workload rather than as one decision about the estate.
Move to cloud for reasons you can state, on a path you can stop.
Cloud migrations disappoint most often when the reason was never specific — lifting servers unchanged onto rented hardware costs more and delivers less. Nextherrion starts with what you actually want from the move, assesses each workload on its own terms, and sequences the migration so it can be paused, reversed or stopped without leaving the estate half-moved.
Assessment, workload analysis, migration planning and execution, with the landing zone and cost model settled before anything moves.
Which workloads should move, which should change first and which should stay — judged per workload rather than as one decision about the estate.
Deciding what the move is for — cost, elasticity, resilience, reach — because the answer changes the target architecture substantially.
Sequencing by dependency and risk, with rollback defined for each stage, so a problem halts one workload rather than the programme.
Executing the move — rehost, replatform or refactor per workload, chosen on merit rather than applied uniformly.
Accounts, networking, identity and guardrails set up before workloads arrive, rather than retrofitted once the estate is already sprawling.
Moving data with its consistency requirements respected, including the cutover window and what happens if it has to be abandoned.
Modelling what the estate will cost to run before committing, since cloud converts capital expense into a monthly bill that grows quietly.
The stage most often skipped: right-sizing and cleaning up once real usage is visible, which is where most of the savings actually are.
The gains come from changing how workloads run, not from where they run. A lift-and-shift with no follow-up usually costs more than the datacentre it left.
Only if workloads change to use it — elastic scaling, right-sizing, managed services. Moved unchanged, cloud is usually more expensive than the hardware it replaced.
Rarely. Some workloads have no case for moving, and a few have regulatory or latency reasons not to. That is assessed per workload.
It depends on sequencing more than on scale. Phased migration with parallel running keeps disruption to a cutover window per workload.
Then you should be able to. Sequencing assumes it — each stage is designed to be a viable resting point rather than a commitment to the next.
Driven by your workloads, existing commitments and the skills you have. Multi-cloud has real cost and is worth choosing deliberately, not by accident.
Optimization, which is where most savings appear. It is also the stage most often skipped once the project is declared finished.
AI and Generative AI, agent frameworks, cloud platforms, data tooling and modern application stacks — chosen per problem rather than per preference.















Start with an assessment. Knowing which workloads should move is most of the decision.