“I very much respect the knowledge that you have. You have a lot of things, just in our few communications, that no one else has mentioned. No one else has even made me think about them.”
DevOps & Cloud Engineering
Infrastructure your team can prove, repeat, and recover
Cloud infrastructure, CI/CD, observability, and recovery engineered so your team can release often, diagnose quickly, and control spend.
Why choose us for DevOps and cloud engineering?
Platform work is judged on the day something goes wrong, so everything we put in is versioned, reviewed, exercised and handed to the people who will own it.
CI/CD pipelines
Automated tests, policy checks, staged deployments, database migration controls, preview environments and reliable rollback mean a release is a routine event rather than a held breath.
Infrastructure as code
Terraform, AWS CDK or Pulumi definitions are reviewed like application code and reproducible across environments, so an environment can be rebuilt from the repository instead of from memory.
Observability + incident response
Structured logs, metrics, traces, service-level indicators, actionable alerts and runbooks tied to likely failures, so the first sign of a problem is a page that says what to do, not a customer email.
Cloud cost control
Right-sizing, commitment planning, storage lifecycle policies, workload scheduling and spend ownership are worked from service-level utilisation data, without false savings that weaken reliability.
Cloud security hardening
Least-privilege IAM, network boundaries, secrets, encryption, audit logging, patching and evidence-ready controls go in as part of the platform, so a later audit reads what exists rather than asking for a retrofit.
Backup + disaster recovery
Tested restore procedures, recovery objectives, dependency mapping and multi-region patterns only where justified, so a recovery plan is something you have rehearsed rather than something you hope works.
What we build in DevOps and cloud engineering
The platform underneath a product: how it is built, shipped, watched, paid for and moved.
CI/CD pipelines
Every change tested, staged and released through the same reviewed path.
- Test, policy and migration checks on every pull request
- Preview environments spun up per branch
- Staged deployments with a rollback path that has been used
Infrastructure as code
Every environment defined in Terraform, AWS CDK or Pulumi and reviewed like application code.
- Dev, staging and production from one definition
- Changes planned, reviewed and applied through the pipeline
- Drift detected and reconciled rather than patched by hand
Container platforms
Docker builds on ECS Fargate, Cloud Run or Kubernetes, chosen by operating cost.
- Reproducible images built once and promoted through environments
- Autoscaling, health checks and zero-downtime deploys
- Secrets, networking and IAM scoped per service
Observability
Logs, metrics and traces wired to alerts that page on likely failures.
- Structured logging with request IDs across every service
- Service-level indicators and error budgets per system
- A runbook attached to every alert that pages
Cost optimisation
Cloud spend cut from utilisation data and owned by a named team.
- Right-sizing, savings plans and spot capacity applied
- Lifecycle rules and scheduling for idle resources
- Spend tagged and reported per team and environment
Cloud migrations
Phased moves to AWS, GCP or Azure with an explicit cutover plan.
- Dependency mapping before anything moves
- Dual-running and data transfer with validation
- Cutover rehearsed, with a way back if needed
Recent products we shipped
Our most recent case studies. Each result is the one its own case study reports, in its own words.
30+ SKUs scanned into one Shopify draft order; the old version choked on large ones.
Draft Deputy
Shopify · Micro-SaaS
1,000+ skincare formulas resolved from a 60-second phone scan in 55+ San Pablo pharmacies, before the customer leaves the store.
2250
A.I · Custom Web App

3.5K students stayed online while a Lovable-built front end was mapped onto the live LMS.
Squid Academy LMS
SaaS · Custom Web App

Non-marketers launch Meta and TikTok campaigns from one plain form, and read both platforms’ results in one view instead of two ad managers.
AI Agent for Meta and TikTok Ads
MVP · SaaS
How we build DevOps and cloud engineering
Four stages, from a baseline of what runs today to a handover where your team has exercised the rollback and restore paths themselves.
Baseline the platform
We inventory environments, deployment flow, incidents, spend, access, dependencies, recovery posture, and current bottlenecks.
Prioritise by exposure
Production risks, release friction, security gaps, and waste are ranked so the engagement fixes material problems first.
Change through code
Infrastructure, pipelines, policies, dashboards, and alerts are versioned, reviewed, tested, and rolled out incrementally.
Exercise + hand over
We prove rollback and restore paths, tune alerts against real behaviour, document runbooks, and transfer ownership to your team.
- See our full process
What clients say after the build
Real client reviews, every one checkable at source.
DevOps and cloud questions
We favour managed services and boring, supportable infrastructure until a real constraint demands more complexity.
AWS is our primary platform, with substantial work on GCP and occasional Azure engagements. We choose from your workload, existing capability, compliance constraints, and commercial commitments: not a blanket preference.

