AI & Cloud Integration
Cloud infrastructure that scales cleanly and costs what it should.
Cloud migrations fail in predictable ways: undocumented dependencies surface mid-migration, licensing issues only appear at scale, 'lift and shift' produces cloud infrastructure with the same architectural problems as the on-premise setup it replaced, and nobody has calculated the post-migration running cost against the on-premise alternative. We've run enough migrations to have seen all of these — and we design the architecture to avoid them. Our approach: document everything before touching anything, migrate workloads in priority order with rollback at each phase, and target a cloud architecture that's meaningfully better than what you had — not just the same thing running on someone else's hardware.
What's included
- AWS, Azure & GCP architecture design
- On-premise to cloud migration planning
- Infrastructure as Code (Terraform & CDK)
- Multi-region & high-availability design
- Containerisation & Kubernetes migration
- Networking, VPC design & security groups
How we deliver
- 1Current state infrastructure audit
- 2Cloud architecture blueprint with cost estimate
- 3Terraform / CDK infrastructure codebase
- 4Phased migration plan with rollback strategy
- 5Network & security configuration
- 6Go-live support & post-migration review
40%
avg cloud cost reduction vs equivalent on-premise running costs
99.99%
availability SLA on multi-AZ cloud architectures
100%
infrastructure delivered as code (Terraform / CDK)
0
production outages during phased migrations
Technologies we use
- AWS
- Azure
- GCP
- Terraform
- AWS CDK
- Kubernetes
- Docker
- Helm
- AWS EKS
- Azure AKS
- CloudFormation
- Pulumi
Why Origin for Cloud Architecture & Migration
Every resource in Terraform from the first commit
No click-ops, no undocumented resources, no 'I think someone created that manually'. Every cloud resource is in version-controlled Infrastructure as Code from day one.
Dependency mapping before the first migration step
We map every dependency — documented and undocumented — before touching the source environment. Surprises during cutover are a planning failure.
Rollback plan at every migration phase
Each phase of the migration has a defined rollback procedure. We don't cut over and hope. We cut over knowing exactly how to reverse it if something surfaces post-go-live.
Industries we serve
SaaS & Tech
Startup infrastructure scaling, multi-region expansion, Kubernetes migration
Financial Services
Regulated cloud adoption, data residency compliance, hybrid cloud
Healthcare
HIPAA-compliant cloud architecture, PHI data handling, HL7 integration
Manufacturing
On-premise ERP cloud lift, IoT data ingestion, hybrid connectivity
Retail & E-Commerce
Peak traffic handling, CDN architecture, database scaling
Government
Sovereign cloud deployment, data localisation, compliance frameworks
“We'd been told our migration would take three months. The previous agency got six months in and we were still on-premise. Origin spent the first two weeks doing a proper dependency audit, then migrated in phases over four months without a single production incident.”
Frequently asked questions
- Should we lift-and-shift or re-architect for the cloud?
- Lift-and-shift (moving existing workloads as-is) is faster but preserves the architectural problems of the original setup and often costs more to run than optimised cloud-native alternatives. Re-architecting for cloud-native patterns (managed services, autoscaling, serverless where appropriate) delivers better economics and reliability but takes longer. We recommend a phased approach: lift-and-shift for workloads where the current architecture is sound, re-architect for workloads where the current design has known problems. We give you a clear recommendation per workload, not a blanket policy.
- How do you handle the undocumented dependencies that always surface during migrations?
- By assuming they exist and mapping them before migration starts. We run network traffic analysis, dependency mapping tools, and application-level tracing on the source environment before touching anything. This surfaces the unexpected connections between services — the backup server that's also the DNS resolver, the development tool that's hitting production endpoints, the scheduled job nobody documented. Finding these before migration is annoying. Finding them after cutover is a production incident.
- How do you design for high availability on AWS or Azure?
- Multi-AZ deployment as the baseline: application, database, and cache layers all deployed across at least two availability zones with automatic failover. For critical workloads, multi-region with active-active or active-passive routing via Route 53 or Azure Traffic Manager. Load balancers with health checks that detect unhealthy instances and route traffic away before the user experiences failure. RTO and RPO targets defined upfront and architecture validated against those targets before go-live.
- What does 'Infrastructure as Code' mean and why does it matter?
- Every cloud resource — VPCs, subnets, security groups, EC2 instances, RDS databases, S3 buckets, IAM roles — is defined in code (Terraform or AWS CDK) rather than created manually in the console. This means your infrastructure is version-controlled (you can see what changed and when), reproducible (staging environments match production exactly), auditable (every change goes through a pull request review), and recoverable (disaster recovery is a Terraform apply, not a manual reconstruction from memory). Manual click-ops infrastructure is the leading cause of 'it worked in staging but not in prod'.
- How long does a cloud migration typically take?
- For a small organisation with fewer than 20 workloads: 2–4 months. For a mid-market company with complex interdependencies: 4–9 months. For enterprise migrations with regulatory requirements, legacy systems, and hundreds of workloads: 12+ months in phases. The timeline is primarily determined by the complexity of current dependencies and how well-documented the existing environment is. Migrations from well-documented, modern on-premise setups take a fraction of the time of migrations from undocumented legacy environments.