Cloud work done properly leaves a platform defined in code, environments that match, routine releases and a bill you can attribute to something. We build on AWS and Microsoft Azure in your own accounts, sized to the load you carry.
Cloud projects go wrong when infrastructure is designed before the workload is understood. We measure first and build the deployment path early.
We measure what the platform does: request volume and shape, batch windows, storage growth and peak concurrency. Where a system is being moved, this includes observation rather than a snapshot.
The design is recorded as a diagram and a rationale: which managed services are used, why, what they cost at current load, and where the failure modes sit.
Accounts, networks, identity, secrets, logging and the code modules that produce them come first. This foundation is the part most often skipped and most expensive to retrofit.
Before the first feature ships there is a pipeline that builds, tests, deploys to staging and promotes to production behind an approval step.
After launch we review spend against tagged owners monthly and architecture against usage quarterly. Right-sizing recurs, because workloads and managed-service pricing both move.
Cloud engagements take three forms — new workloads, migrations and correction. The engineering is similar; the sequencing differs.
Greenfield applications designed for AWS or Azure: managed databases, object storage, containerised services and a network layout that assumes growth.
Platform detail →Staged relocation of applications and databases, with parallel running, reconciliation and a rehearsed cutover in AWST. The old environment stays available until the new one is proven.
See an example →Reviewing an account for idle capacity, oversized instances and orphaned storage, then applying changes with a measured before-and-after.
Read our view →Bringing a manually assembled environment under code control: reconstructing it as Terraform, closing unmanaged access paths and creating the missing environments.
Delivery practice →The technology is rarely the difficulty. What brings clients to us is an environment nobody can describe, a bill nobody can explain, or a release process requiring nerve.
Resources were created through a console over several years. Nobody can rebuild the environment from scratch, and nobody is confident that staging resembles production.
Monthly spend has climbed with no corresponding increase in usage. Without cost tagging by owner, the increase cannot be attributed.
Deployments happen quarterly because each requires manual steps and an untested rollback. Each release then carries more change, which makes the next release more frightening.
One machine remains because the application on it was never migrated. It is not backed up to a tested standard, its operating system is out of support, and the risk is unaddressed.
The platform is described as resilient because the provider is. That covers infrastructure failure, not an accidental deletion, and no recovery objective has been tested.
These mechanisms turn a hosted application into a platform you can operate confidently. Each is implemented during the engagement and explained at handover.
Described by sector only.
A mid-market professional services group ran a matter management and billing application on two physical servers in its Perth office. The servers were out of vendor support, the backup destination was a second disk in the same cabinet, and no recovery expectation had been written down. We assessed two months of usage before designing anything, then moved the platform to AWS in four stages: database with replication, then read traffic, then write traffic, then decommissioning. Each stage had a rehearsed rollback and a signed reconciliation report.
Cloud work is quoted in two parts: a fixed platform engagement and a monthly operating fee if you want us to run it. Infrastructure is billed by the provider into your account.
Indicative only, based on engagements since 2021. A single workload on an existing foundation sits at the lower end; a multi-application migration at the upper end.
The account, the code and the documentation belong to you from the first commit. The handover pack is written so another provider could take over without a rebuild.
Usually on what you already hold: licences, internal skills, data residency and the managed services your workload needs. Where there is no prior position we compare both and show the cost difference.
Discuss your case →Often, but not automatically. Replacing ageing servers with well-sized managed services usually reduces total cost once refresh, power and maintenance are counted. We model expected spend before you commit.
On cost governance →We provision in Australian regions by default and state the region in the architecture record. Where personal information is involved we recommend keeping storage and backups in-country.
Security approach →Yes. We begin by reconstructing what exists as code, which is also the fastest way to find undocumented resources and stale access.
Support options →Assessment produces a written design, an expected monthly spend and a staged plan. You can take it elsewhere if you wish.
