DevOps
CI pipelines, infrastructure as code, containers, and monitoring, so deploys are boring and incidents are short. For teams shipping by hand, paying for cloud they cannot see, or finding out about outages from customers.
Who this is for
- A team where one person knows how to deploy and everyone waits for them.
- A cloud bill that grew without anyone deciding it should.
- An application with no alerts, or so many that nobody reads them.
- A compliance requirement that needs audited, reproducible infrastructure.
What is included. Tick what you need.
Artefacts, not adjectives. Each is something you can point to at the end. Tick the ones your project needs and send the list with your enquiry; we reply with a written scope.
Technologies we use for this
The relevant slice of our technology matrix. Nothing here that we cannot staff today.
- AWS
- Google Cloud
- Azure
- Cloudflare
- Docker
- Kubernetes
- Terraform
- GitHub Actions
- GitLab CI
- Nginx
- Grafana
- Sentry
How we deliver it
The five steps every engagement goes through, in the form they take for this service.
Scope
A call with an engineer, then a written scope: what is in, what is out, and what it costs.
Architecture
Data model, API contract, and infrastructure plan, approved before code is written.
Build
Infrastructure changes land through pull requests with plans attached, so every change is reviewed before it applies.
Harden
Tests on the paths that matter, error tracking, a performance pass, and a security review.
Launch and hand over
Production deployment, monitoring, documentation, and every repository transferred to you.
From the blog
- LLM security: prompt injection, data leakage, and what actually stops themMost LLM security advice is 'write a better system prompt.' The actual defenses are architectural: what the model can see, what it can do, and what never returns to a user unchecked.
- LLM observability: what to log, and what it actually catchesTraditional APM tells you a request was slow. LLM observability has to answer a different question: was the answer right, and why did the model say that?
- How we reduced LLM costs in a multi-tenant AI platformOne customer's heavy usage was inflating everyone's bill. The per-tenant budgeting, routing, and caching changes that cut the platform's running cost by 58%.
Questions we get asked
Do we need Kubernetes?
Most teams do not. Managed containers or a platform service cover a lot of ground with far less to operate. We recommend Kubernetes when the workload genuinely needs it.
Can you work in our existing cloud account?
Yes, and we prefer it. We import what exists into Terraform first so nothing is rebuilt that does not need to be.
How do you reduce cloud cost without risk?
Measure first, then rightsize idle capacity, add lifecycle rules to storage, and commit to reserved capacity only for stable workloads. Each change is reversible.
What about security?
Least-privilege IAM, secrets in a vault, dependency scanning in CI, and network rules written down. Where you need a formal audit, we prepare the evidence.
Who is on call afterwards?
Your team, with runbooks and alerts tuned so pages are rare and actionable. A retainer is available if you would rather we carry it.
Tell us what you are building.
We reply within one business day with how we would build it, what it would cost, and which engagement model fits.
- 01Tell us what you are building
A short form or an email. No deck required, and "not sure yet" is a fine answer.
- 02A call with an engineer
Within one business day. Technical questions get technical answers, from the person who would build it.
- 03A written scope and quote
Fixed price where the scope is defined. The document is yours whether or not you go ahead.