Infrastructure you can rebuild from scratch
We set up cloud environments, deployment pipelines and monitoring so that shipping is routine, capacity follows demand, and the answer to "what is running in production" is a file rather than a person.
What good infrastructure feels like
Key benefits
What this changes for your business.
Deployments become routine
A pipeline that tests, builds and ships on every merge takes the ceremony — and the fear — out of releasing.
Environments you can recreate
Infrastructure in version control means staging can be rebuilt to match production exactly, on demand.
Capacity follows demand
Autoscaling and sensible resource limits, so a busy week costs more for a week rather than requiring a purchase decision.
You hear about it first
Alerting on the symptoms customers would notice — errors, latency, queue depth — rather than on CPU graphs nobody reads.
Backups that have been restored
A restore drill on a schedule, because the first time you test a backup should not be during an incident.
What we deliver
The things you actually receive.
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Cloud architecture design
Network, compute, storage and database layout sized for what you run, with the cost written down.
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Containerisation
Dockerised applications and a local environment that matches production closely enough to be useful.
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CI/CD pipelines
Automated tests, static analysis, build and deploy, with an approval gate where you want one.
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Infrastructure as code
Terraform modules for every environment, reviewed like application code.
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Monitoring and log aggregation
Metrics, structured logs, error tracking and alerts routed to somebody who can act on them.
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Backup and disaster recovery
A written recovery objective, automated backups and a documented restore that has been rehearsed.
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Cost review
Right-sizing, reserved capacity and the unused resources every account accumulates.
Core capabilities
The engineering disciplines this service draws on.
Technologies we use
The stack we would reach for, and what each part is for.
Docker
Containers, so the application a developer runs locally and the one running in production are the same artefact.
Kubernetes
Container orchestration: it decides where services run, restarts what fails and scales what is busy, without somebody watching a dashboard.
Terraform
Infrastructure described in files and kept in version control, so an environment can be rebuilt rather than remembered.
AWS
Cloud infrastructure with managed databases, storage and networking, so capacity follows demand instead of a purchase order.
GitHub Actions
The pipeline that runs the tests, builds the artefact and deploys it — on every commit, in the same order, every time.
Redis
An in-memory store used for caching, queues and rate limiting — the difference between a page that waits on the database and one that does not.
PostgreSQL
A relational database with strong support for JSON, full-text search and geospatial data, for models that outgrow plain tables.
Technology adoption
Technologies in this stack are publicly documented as being used by organisations including those below.
These organisations are named as documented users of the technologies listed. They are not clients of Vertex Arc, and their inclusion does not imply any relationship with or endorsement of Vertex Arc.
Industries we serve
Sectors where this service tends to fit well.
- SaaS
- FinTech
- E-Commerce
- Media & Publishing
- Logistics
Our delivery process
How an engagement runs, from first conversation to ongoing support.
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Discovery
We work out what the software has to do, who uses it, and which constraints are real. The output is a written scope, not a proposal.
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Architecture
Data model, boundaries, integrations and infrastructure decided and agreed before anybody writes application code.
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Design
Flows and interface, including the empty, error and permission states that decide how the product actually feels.
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Development
Built in reviewable increments against a conventional structure, with tests around the parts that would be expensive to break.
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QA & security
Functional testing, performance checks, and a review of authentication, authorisation and dependency risk before launch.
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Launch
Deployment, monitoring, and a period of close attention while real traffic finds what staging did not.
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Continuous improvement
Patches, upgrades and new work through the support system, so the product keeps being maintained rather than quietly ageing.
Use cases
What this looks like as a finished product.
From manual deploys to a pipeline
Replacing an SSH-and-remember-the-order release with a tested pipeline anybody on the team can run.
Surviving a traffic spike
A campaign, a launch or a season that multiplies load, handled by autoscaling and caching rather than by staying up all night.
Proving you can recover
A documented, rehearsed restore, so the recovery objective in the contract is something you have actually done.
Why Vertex Arc
We work on infrastructure we did not build
Most of this work starts with an existing environment and a team that inherited it. That is normal, not a disqualifier.
Sized for you, not for a conference talk
Most businesses do not need a service mesh. We recommend the simplest architecture that meets the requirement.
Runbooks, not tribal knowledge
What to do when the queue backs up, written down, so the answer does not depend on who is awake.
Cost is part of the design
An architecture you cannot afford in month six is not a good architecture. We put the number on the page.
Frequently asked questions
Do we need Kubernetes?
Can you work with our existing cloud account?
How long does a migration to the cloud take?
Who gets the alerts at 3am?
Have a project in mind?
Book a 30-minute call with the engineers who would do the work, or send us the details and we will come back to you.