Cloud Architecture Review
An assessment of the estate as it stands — cost, resilience, security posture and the decisions that are constraining it.
Architecture that uses the cloud, rather than merely running in it.
Most estates arrive in the cloud shaped by the datacentre they left. Nextherrion reshapes them: managed services where they remove operational burden, elasticity where load actually varies, and resilience designed around what the business can tolerate losing rather than around a default.
Architecture review and design, cloud-native modernization, resilience and scalability engineering, and the security posture underneath it.
An assessment of the estate as it stands — cost, resilience, security posture and the decisions that are constraining it.
Designing around managed services, elasticity and failure isolation, so the platform does work you would otherwise operate yourself.
Changing applications so they can actually use what cloud offers — statelessness, horizontal scale, externalized configuration.
Containerized workloads and orchestration where the estate justifies the operational cost. Where it does not, we say so.
Event-driven and serverless designs for workloads whose shape suits them — spiky, intermittent, or bound to events rather than uptime.
Recovery objectives agreed with the business first, then architecture to meet them — and tested, because untested recovery is a plan, not a capability.
Designing for the load you expect and the load you would rather survive, including how the system degrades when it exceeds both.
Identity, network boundaries, secrets and least-privilege access designed in, since cloud misconfiguration is a more common cause of exposure than intrusion.
Sometimes. It suits estates with many services and the team to operate it, and is considerable overhead otherwise. It should be a decision with a reason attached.
Workload shape decides it. Spiky and event-driven work suits serverless; long-running or latency-sensitive work often does not.
As much as the business can justify paying for. That starts as a conversation about acceptable downtime and data loss, not as a technical choice.
Usually not wrong, just shaped by earlier constraints that no longer apply. Review identifies which of those are now costing you.
Largely, with phased change and parallel running. Some cutovers need a window, and those are identified and scheduled rather than discovered.
Architecture decides most of it — the right service, the right size, and switching things off. Monitoring catches the rest before the bill does.
AI and Generative AI, agent frameworks, cloud platforms, data tooling and modern application stacks — chosen per problem rather than per preference.















Start with an architecture review.