Deploys should be boring
Infrastructure work is invisible when it goes well, which is exactly why it gets deferred until the bill, the outage or the audit forces the issue. We do it before that.
You might be here because
Situations we are brought in for
- Deploys are a manual sequence only one person fully understands.
- Something broke last week and you still cannot say precisely why.
- Your cloud bill grows faster than your usage and nobody can explain the delta.
- A customer wants SOC 2 evidence and your infrastructure cannot produce it.
What you get
Concrete deliverables, not a retainer with a hope attached
Infrastructure as code
Your environment, reproducible from a repository. No more configuration that exists only in one console and one memory.
CI/CD pipelines
Tested, gated, reversible deploys. Shipping on a Friday afternoon stops being a personality trait.
Observability
Metrics, structured logs and traces wired to alerts that mean something — so incidents are diagnosed, not guessed at.
Cost and capacity review
A line-by-line account of where the money goes, and the changes that reduce it without trading away reliability.
How it works
Four phases, each with an exit you control
- 01
Audit
We inventory what actually runs, how it is deployed, and where the single points of failure and single points of knowledge are.
- 02
Prioritise
Findings ranked by risk against effort. You get the list whether or not you continue with us.
- 03
Remediate
We work down the list in production-safe increments, each one shippable and reversible on its own.
- 04
Transfer
Runbooks, dashboards and a working session with your on-call engineers. The goal is that you do not need us next quarter.
Tools we reach for
Chosen per problem, not per fashion
This is what we use most for platform & infrastructure. If your team is already productive in something else, we work in that instead — familiarity in your team beats preference in ours.
- Terraform
- Docker
- Kubernetes
- GitHub Actions
- AWS
- Cloudflare
- OpenTelemetry
- Grafana
Where this usually starts
Technical Audit
Technical Audit
Understanding a system you have inherited, acquired or lost track of
An independent read of a codebase and its infrastructure: what is actually there, what is at risk, and what it will take to fix. Useful before an investment, an acquisition or a rebuild decision.
- Typical duration
- 1–3 weeks
- Commitment
- Fixed scope, fixed fee
Includes
- Codebase, architecture and dependency review
- Infrastructure, deployment and security posture
- Test coverage and release-process assessment
- Key-person and knowledge-concentration risk
- Findings ranked by risk against remediation effort
You keep
- Written audit report
- Risk register with severity ratings
- Remediation roadmap
- Readout session with your team or board
Fee agreed after scoping. No commitment to that conversation.
Common questions
Will you migrate us to Kubernetes?
Only if your problem is actually a Kubernetes-shaped problem, which it often is not. Plenty of teams are better served by a managed platform or a handful of containers on boring hardware. We will recommend the least complex thing that meets your requirements.
Can you do this without downtime?
In almost all cases, yes. Migrations are planned as reversible steps with an explicit rollback at each stage. Where a maintenance window genuinely is required, you will know well in advance and we will keep it as short as possible.
Do you offer ongoing on-call?
We do not replace your on-call rotation, but we can sit behind it as an escalation path during and after an engagement, and help you build a rotation that does not burn people out.
Related reading
The connection pool exhaustion that was not a connection pool problem
A production incident where every symptom pointed at the database, and the actual cause was an HTTP client with no timeout three services away.
Other services
Product engineering
Ship the product your roadmap keeps promising — designed, built and maintained.
Legacy modernisation
Untangle the system nobody fully understands — without stopping the business.
AI & applied ML
Put language models into production without betting the product on a demo.
Custom software
For the process no product on the market actually fits — built once, properly.
SaaS development
Multi-tenancy, billing and onboarding — the unglamorous parts that decide whether it scales.
Web applications
Serious applications in the browser — dashboards, editors, real-time tools that stay fast with real data.
API development
Interfaces other engineers have to live with — versioned, documented and hard to misuse.
Mobile apps
Apps that work on a bad connection, clear store review, and can be shipped weekly.
Next step
Think this is your problem?
Send us the shape of it. We will tell you whether it is a fit, what we would do first, and roughly what that takes.