Software that cannot be deployed safely is software that stops improving. Teams without a pipeline batch up changes, deploy on Friday, and spend the weekend recovering — so they deploy less, batches grow, and risk compounds. We set up the infrastructure and automation that makes releasing a routine, boring event.

Who this is for

Teams deploying by hand, over FTP, or by SSH-ing into a server. Companies whose cloud bill has grown faster than their traffic. Products that were fine at launch and now fall over at peak. Anyone who has discovered an outage from a customer rather than from a monitor.

Problems we solve

Manual deploys. Undocumented, unrepeatable, and dependent on one person being available.
No way back. A bad release with no rollback path means fixing forward under pressure.
Environment drift. Code that works locally and fails in production for reasons nobody can reproduce.
Cloud bills nobody can explain. Over-provisioned instances, forgotten resources, and no cost attribution.
Blind production. No metrics, no log aggregation, no alerting — so problems are discovered by users.

What we build

Containerised environments with Docker, so local, staging and production actually match
CI/CD pipelines that run tests, build images and deploy on merge — with a one-command rollback
Infrastructure as code, so servers are reproducible rather than hand-tuned
Monitoring, log aggregation, uptime checks and alerting that reaches a human
Automated backups with tested restores, because an untested backup is a hope
Cost review: right-sizing, caching, and removing what nobody is using

How we work

We start by making deployment repeatable, because everything else depends on it. Then observability, so we can see what is actually happening before optimising it. Then scaling and cost, informed by real measurements rather than assumptions. We prefer boring, well-understood infrastructure over novel architecture — an operations burden is a recurring cost, and most systems do not need Kubernetes.

Technologies we use

Docker and Docker Compose, GitHub Actions for CI/CD, AWS and comparable cloud platforms, Nginx, Redis, MySQL and PostgreSQL, with monitoring and log aggregation appropriate to the scale. We size the tooling to the team that has to run it after we leave.

Business benefits

Releases become routine, so fixes and features reach users sooner
Rollback in minutes turns a bad deploy into an inconvenience rather than an incident
Problems surface on a dashboard before they surface in your inbox
Infrastructure spend matched to actual usage
Recovery from failure is a tested procedure, not an improvisation

Where it pays off

Moving off manual deployment onto an automated pipeline
Preparing a product for a launch, campaign or seasonal peak
Cutting a cloud bill that has drifted well past its value
Adding monitoring to a system currently running unobserved
Ongoing maintenance, patching and dependency updates after launch

Common questions

Do we need Kubernetes?

Almost certainly not. Most products we see are served well by containers on managed infrastructure, and adopting Kubernetes early buys complexity that a small team then has to carry. We recommend it when the scale genuinely justifies it and not before.

Can you work with our existing cloud account?

Yes. We work in your account, under your billing, with access we hand back. We do not resell hosting or put ourselves between you and your infrastructure provider.

What does maintenance actually cover?

Dependency and security patching, monitoring and responding to alerts, backup verification, performance review, and a defined response path when something breaks. Scoped to an agreed level rather than open-ended.

Deploying by hand or flying blind in production? We will start with the pipeline and the monitoring.

Cloud & DevOps