AI chatbots, WhatsApp automation and workflow agents — See the reference architectures we deploy.
See our AI solutionsReleasing should be the least interesting part of the week. When it is not — when deployments happen late at night, need a specific person, or are followed by a nervous hour of checking — the cost is paid in delayed releases and in the changes teams avoid making at all.
We set up and run cloud infrastructure on AWS, Google Cloud, Azure and DigitalOcean: environments defined as code, pipelines that build and deploy on merge, backups that are actually restored as a test, and monitoring that pages a human for the things that matter and stays quiet about the things that do not.
Cost is treated as an engineering concern. Cloud bills grow through instances nobody turned off, logs retained forever and databases provisioned for a peak that never arrived. Reviewing that is part of running the platform.
The problem
Infrastructure built by hand cannot be reproduced. When the person who configured it leaves, or the region goes down, or a second environment is needed, the knowledge required to rebuild it does not exist in any form that can be read.
Untested backups are the same problem with a worse ending. Almost everyone takes them; far fewer have restored one recently, which is the only way to know whether they work.
Environments built by hand
Nothing is reproducible, and the configuration exists only in one person's memory.
Releases that need a specific person
Deployment is a ritual rather than a command, so it happens rarely and at bad times.
Backups nobody has restored
A backup that has never been tested is an assumption, not a recovery plan.
Alerts everyone ignores
Noisy monitoring trains the team to dismiss the one alert that mattered.
Our approach
Everything is defined in code and kept in version control, so an environment can be recreated from a clean account and a change to it is a reviewable diff rather than a memory of what someone clicked.
Pipelines run the test suite, build the artefact once and promote that same artefact through environments, so what you tested is what you shipped. Deployments are zero-downtime where the application allows it, and every one is reversible — a rollback should be a routine action, not an incident.
Monitoring is set up around symptoms users would notice: error rates, latency, queue depth, disk and certificate expiry. Alerts that fire without needing action get removed, because an alert channel people have learned to ignore is worse than no alerting at all. Backups are scheduled, encrypted, and restored on a schedule to prove they work.
Capabilities
CI/CD pipeline design and automation
Docker containerisation
AWS architecture and cost review
Zero-downtime deployment strategies
Monitoring, logging and alerting
Backup, restore and disaster recovery testing
Outcomes
Reproducible environments
Infrastructure as code, so staging matches production and a rebuild is a command rather than a project.
Deploy on merge
Tested, built once, promoted through environments, and reversible without drama.
Restores that are proven
Backups are encrypted, scheduled and periodically restored, so recovery time is known rather than hoped for.
Costs that get reviewed
Right-sizing, retention policies and idle resources looked at deliberately instead of discovered on an invoice.
Common questions about cloud & devops.
If the honest answer is "we are not sure", that is the thing worth fixing first.
Get in touch
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Delivering Smart Technology Solutions
Tell us what you are trying to build. We will come back with an honest assessment — including if we are not the right fit.
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