Data & Cloud
Cloud architecture, data platforms, DevOps, managed support, and security engineering — the invisible layer that decides whether everything else scales or stalls.
See related work- Availability target, agreed against what the system needs
- Per engagementAvailability target, agreed against what the system needs
- Every migration, twice, before it runs
- RehearsedEvery migration, twice, before it runs
- On-call held by the team that built it
- 24×7On-call held by the team that built it
Every platform we build stands on this layer, so we engineer it like it matters — because it does. Cloud bills that stop surprising you, data that arrives clean and on time, deployments that are boring, and security that's designed in rather than audited in.
Infrastructure decisions are business decisions wearing technical costumes. We present them that way: cost curves, risk profiles, and growth headroom in language a CFO can challenge.
What this practice owns.
Not a scope of works — the things that stay our problem for as long as the engagement runs.
The migration plan and its rollback, rehearsed before the weekend it runs.
Cost: an architecture sized to your actual load, with the bill modelled before commitment.
Observability — so an incident is diagnosed from dashboards rather than from guesswork.
The security posture, including the review pack your client's auditor will ask for.
5 services in this practice
Each one is a full capability with its own page — the method, what you are handed, the stack, and who it is not for.
How this practice usually starts.
We do not publish prices — scope drives them, and a number without scope is a guess. Everything else about the shape, here.
- Starts with
- An assessment of what you run now and what it costs
- Time to production
- 6–14 weeks for a migration; managed operations are ongoing
- Who you get
- A cloud architect and SREs, sized to the estate
- Commercial model
- Fixed-scope assessment, then project or retained operations
What drives the number is on how we price.
- AWS / Azure / GCP
- Terraform
- Kubernetes
- VPC & zero-trust networking
- FinOps tooling
- PostgreSQL / ClickHouse / BigQuery
- dbt
- Airflow/Dagster
- Metabase/Superset/Power BI
- Streaming (Kafka)
- GitHub Actions / GitLab CI
- Terraform & Ansible
- Prometheus/Grafana
- OpenTelemetry
- PM2/Kubernetes
- Grafana/Prometheus
- PagerDuty-class alerting
- Automated patching
- Backup verification
- Runbooks
- Threat modelling
- SAST/DAST tooling
- Vault-class secrets
- SIEM-lite stacks
- Zero-trust patterns
Where this practice has shipped.
Live control tower for a national fleet
Real-time visibility over 3,000+ vehicles with exception-first alerts — detention hours cut 41%, and customers now track shipments without calling.
41%Reduction in detention hours
Headless replatform for a D2C brand
Rebuilt a buckling storefront into a headless commerce platform — 99.98% uptime through festival sales and a 28% lift in conversion from speed alone.
99.98%Sale-day uptime
Custom ERP for a steel processing group
Replaced five disconnected systems and a wall of spreadsheets with a single custom ERP — order-to-dispatch in one flow, month-end closing down from 9 days to 2.
9→2 daysMonth-end closing time
Where data & cloud comes up most.
Questions we hear about data & cloud
Every service above runs the same five-phase method. To work out which of them your situation actually needs, discuss this practice.