Multi-Cloud Strategy
Deciding whether to run across providers at all, and for which workloads — a decision with ongoing cost, not a hedge that comes free.
Run across providers and on-premise where there is a reason to — without paying for it twice.
Multi-cloud is often an accident rather than a strategy: an acquisition, a team that chose differently, a workload that could not move. It carries real cost in skills, tooling and complexity. Nextherrion helps you decide where that cost is worth paying, and makes the estate coherent where it is.
Strategy, workload placement, connectivity, identity and consistent operations across providers and on-premise estates.
Deciding whether to run across providers at all, and for which workloads — a decision with ongoing cost, not a hedge that comes free.
Matching workloads to environments on data residency, latency, cost and the capabilities each provider actually does well.
Designing estates that span on-premise and cloud, where regulation, latency or existing investment mean some things stay put.
Connectivity between environments with the latency, egress cost and failure behaviour understood before workloads depend on it.
One identity model across environments, so access is granted and revoked once rather than per provider.
Common deployment, monitoring and alerting across providers, so operating two environments does not mean two operational practices.
Keeping workloads movable where portability is genuinely worth its cost — which is less often than it is claimed.
One view of spend across providers, since separate bills make it easy to lose track of what the estate actually costs.
Multi-cloud that was chosen behaves differently from multi-cloud that was inherited. The aim is for the split to be deliberate and the operations to be single.
Only with a reason — regulation, residency, acquisition, or a capability one provider does markedly better. As insurance against lock-in it usually costs more than the risk it covers.
Less than expected. Most outages are regional, and running across regions with one provider is simpler and cheaper than running across two.
Mostly in skills and tooling — two environments to operate, secure and monitor. Worth quantifying rather than treating as free flexibility.
Up to a point, and it means avoiding the managed services that make a provider worth using. That trade should be made explicitly.
Residency and egress cost usually decide placement. Moving data between providers repeatedly is expensive and slow, so the design tries not to.
A common position. The work is deciding what stays where, then consolidating operations so it is one estate rather than several.
AI and Generative AI, agent frameworks, cloud platforms, data tooling and modern application stacks — chosen per problem rather than per preference.















Start with a placement review — what should sit where, and why.