For enterprises
Digital Transformation
Modernising the processes and platforms a business runs on — sequenced so value arrives early and the organisation can absorb it.
Service detailAI, Data & Engineering
Cloud & Infrastructure
Cloud programmes go wrong in two predictable ways: lifting workloads unchanged and being surprised by the bill, or rebuilding everything at once and never finishing. We assess each workload on its merits, migrate in waves, and treat cost as an engineering constraint from the first design session.
Start a conversationFor enterprises
- Platforms
- AWS, Azure, GCP
- Approach
- Wave-based migration
- Everything
- Infrastructure as code
- Cost modelling
- Before and after, per workload
What's included
What this engagement covers
Migration assessment
Workload-by-workload analysis producing a disposition for each — rehost, replatform, refactor, retain or retire — with cost modelling behind every call.
Cloud migration
Wave-based execution with rollback plans, parallel running where risk demands it, and cutover runbooks rehearsed before the night they matter.
Platform engineering
Internal platforms that give product teams paved paths — provisioning, deployment, secrets and observability available by default rather than by ticket.
Infrastructure as code
Every environment reproducible from version control. No configuration that exists only in a console and only in one person’s memory.
Cost optimisation (FinOps)
Rightsizing, commitment planning, storage tiering, and per-team cost attribution so spend becomes a number people can act on.
Reliability and observability
SLOs tied to user-visible behaviour, structured logging, distributed tracing, and alerting that pages a human only when a human is needed.
Process
How migrations run
Written down so you can hold us to it.
Discovery and dependency mapping
Inventory every workload and map the dependencies between them — including the ones nobody documented. This is where most migration surprises are found or missed.
Disposition and business case
A disposition per workload with modelled cost, effort and risk. Some workloads should not move at all, and the analysis says so.
Landing zone
Accounts, networking, identity, guardrails and baseline observability built as code before the first workload moves.
Wave migration
Workloads move in waves grouped by dependency, starting with low-risk candidates to prove the runbook. Each wave has a tested rollback path.
Optimise and operate
Post-migration rightsizing, commitment purchasing and reliability tuning, then handover to your team with runbooks and paired on-call.
Outcomes
What good looks like
- Every environment reproducible from version control
- Cost attributed per team and per service, reviewed monthly
- SLOs defined against user-visible behaviour, with error budgets
- Deployment frequency up and change failure rate down, measured
- Disaster recovery tested rather than documented
- Your team operating the platform without us
Detail
Technologies
Cloud platforms
- AWS
- Microsoft Azure
- Google Cloud
- Hybrid and co-location
- Multi-region design
Provisioning
- Terraform
- OpenTofu
- Bicep
- CloudFormation
- Ansible
- Crossplane
Runtime
- Kubernetes
- ECS & Fargate
- Serverless
- Service mesh
- Container registries
Operations
- Prometheus & Grafana
- OpenTelemetry
- Datadog
- PagerDuty
- Chaos testing
Questions
What people ask about this service
Including the ones with answers you might not want.
Will moving to cloud reduce our costs?
Not automatically, and anyone promising it will should be treated with suspicion. A lift-and-shift with no rightsizing usually costs more than the data centre it replaced. Savings come from rightsizing, commitment planning, retiring workloads and elasticity — all of which take deliberate engineering. Our assessments model both outcomes so you can see the difference.
Should we be multi-cloud?
Usually no. Multi-cloud roughly doubles platform complexity and rarely delivers the leverage people expect. Good reasons exist — regulatory requirements, acquisition history, a specific service only one provider offers — but "avoiding lock-in" on its own generally is not one.
Do we need Kubernetes?
Often not. Kubernetes is excellent when you have many services and a team to operate it. For a handful of services, managed container platforms or serverless deliver the same outcome at a fraction of the operational cost. We size the platform to your team, not to the industry conversation.
Can you work with our existing cloud team?
Yes, and it is the preferred arrangement. We frequently work as an embedded capability alongside an internal platform team, focusing on the areas where they lack depth or bandwidth rather than replacing them.
Still unresolved? Ask us directly.
Related
Services that usually accompany this one
For enterprises
Enterprise Software Development
Custom platforms and applications built to be maintained — tested, documented and handed over to your team.
Service detailFor enterprises
IT Consulting
Technology strategy, architecture review and delivery assurance from senior practitioners who still build systems.
Service detail
Next step
Get a migration assessment
A workload-level disposition and cost model, typically four to six weeks, delivered as a decision document.