Make shipping boring
Deployment should be the least interesting part of your week. Most teams are a long way from that: releases are batched up for a Friday night, the pipeline is a script one person understands, and nobody can say how long a change takes to reach a customer. We fix the path from commit to production — automated, observable, reproducible — and we measure the result in deployment frequency, lead time, change failure rate and time to restore rather than in tools installed.
What we bring to DevOps
We measure the four numbers that matter
Deployment frequency, lead time for changes, change failure rate and time to restore service. We baseline them in week one and report against them throughout, because a DevOps engagement with no numbers attached is just a tooling purchase.
Platform, not a pile of tools
Golden paths a developer can follow without filing a ticket: a templated service that arrives with a pipeline, a dashboard, an alert route and an environment already attached. Self-service is the point — every manual step you leave in place becomes a queue in front of your platform team.
Supply chain treated as production risk
Signed builds, generated SBOMs, pinned and provenance-checked dependencies, and short-lived credentials instead of long-lived keys in CI. The compromise route into most companies now runs through a build system, not a firewall.
Infrastructure that matches the code that describes it
Everything in Terraform, drift detected automatically, and console changes treated as an incident rather than a shortcut. An IaC repository that no longer reflects reality is worse than no IaC at all, because people still trust it.
We hand over the pager, not just the repo
Runbooks, alert routing that distinguishes urgent from interesting, and blameless incident reviews run with your team until they run them without us. Reliability is a practice, and practices do not transfer through documentation alone.
What our devops covers
CI/CD pipelines
Build, test and release automation on GitHub Actions, GitLab CI or Jenkins where it already runs the estate. Every merge produces a versioned, tested artefact; promotion between environments is a decision, not a rebuild.
Infrastructure as code
Terraform modules for your accounts, networks, clusters and data services, with Ansible for configuration where machines still matter. Reviewed in pull requests, planned before apply, and checked continuously for drift against what is actually running.
Containers & orchestration
Docker images built small and rebuilt reproducibly, running on Kubernetes or a managed container service. We size the platform to your team — plenty of companies get more from ECS or Cloud Run than from a cluster nobody wants to operate.
Internal developer platform
Service templates, GitOps delivery with ArgoCD, environment provisioning on request, and a catalogue of what exists and who owns it. The measure of success is how much a new engineer can do on their first day without asking anyone.
Observability & incident response
OpenTelemetry instrumentation feeding Prometheus and Grafana, service level objectives agreed with the business, and alerts tied to those objectives rather than to CPU graphs. Plus the on-call rota, escalation policy and review cadence around them.
Pipeline security & compliance
Secret scanning, dependency and container scanning, policy as code on infrastructure changes, SBOMs and signed artefacts, and audit evidence produced by the pipeline instead of assembled by hand the week before an assessment.
The engagement, step by step
- 01
Assessment & baseline
One to two weeks reviewing your pipelines, environments, release process and incident history. You get the current DORA baseline, the three constraints actually slowing delivery, and a costed plan — often shorter than clients expect, because the bottleneck is rarely everywhere.
- 02
Foundations
Source control conventions, environment topology, secret management and infrastructure brought under code. Unglamorous, and the reason later work does not have to be redone.
- 03
Pipeline build-out
One service goes end to end first — build, test, scan, sign, deploy, roll back — and becomes the template. We prove the path on something real before rolling it across the estate.
- 04
Observability & reliability
Instrumentation, dashboards, SLOs and alert routing, followed by a game day where we break something on purpose in a controlled environment to find out what your alerts and runbooks actually do.
- 05
Rollout & enablement
Remaining services migrated onto the golden path, with your engineers doing the migrations and us reviewing. Working sessions rather than slide decks, because adoption fails when the platform is something done to a team.
- 06
Handover & improvement
You own the platform, the pipelines and the on-call practice. We stay on a light cadence to review metrics, tune alerts and pick off the next constraint for as long as that is useful.
DevOps technology stack
CI/CD
Infrastructure as code
Containers
Observability
Security
Why teams choose us for devops
Engineers who have carried the pager
The people designing your alerting have been woken by bad alerting. It shows in what they choose not to page you about.
Incremental by default
You do not need to change your entire development process, and we will not ask you to. We start where the delay is worst, ship that, then move to the next constraint — so value arrives in weeks rather than at the end of a transformation programme.
Cost is part of the platform
Spend tagged by team and service, waste surfaced on a dashboard your engineers actually see, and right-sizing treated as routine work. Cloud bills grow when nobody who can change them can see them.
We will not sell you Kubernetes
If your workload runs happily on managed containers or a handful of well-configured instances, that is the recommendation. A cluster you cannot staff is a liability dressed as a strategy.
DevOps questions, answered
Last updated: August 31, 2026
Changes reach production more often and in smaller batches, which is what makes them safer. Teams typically see lead time drop from weeks to days, failed changes fall because each release carries less risk, and recovery time shorten because rollback is rehearsed rather than improvised. The secondary effect matters just as much: developers stop queueing for environments, access and deployments, and get several hours a week back.
How long does a one-line change take to reach production?
If the honest answer is measured in days, or nobody is sure, that is the conversation worth having. A short assessment gets you a baseline and the two or three changes that would move it most.
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