DevOps consulting
From infrastructure management to SRE, MLOps and full CI/CD delivery. We build the pipelines, platforms and controls that let your team ship quickly without taking on avoidable risk.
Service catalogue
Eight practice areas covering the full path from commit to production, and the platform underneath it.
Day-to-day operation of your cloud estate, defined as code and kept in a known state.
Pipelines that build, test, scan and deploy automatically, with rollback built in.
Account structure, networking, cost control and governance across your cloud provider.
Security controls and compliance evidence integrated into the delivery path itself.
Reliability targets, SLOs, on-call design and the engineering work to actually hit them.
Reproducible model training, versioning and deployment alongside the rest of your stack.
Internal developer platforms, golden paths and self-service that remove ticket queues.
Independent assessment and a prioritised roadmap you can execute without us.
01 · CI/CD
The point of a pipeline is that deploying becomes an unremarkable event. We build pipelines where every change is built, tested, scanned and gated automatically, so the only decision left is whether the code is good, not whether the process works.
We start by measuring where time actually goes between commit and production, then remove the slowest parts first. That usually means fixing pipeline design and test feedback loops long before anyone needs a new tool.
02 · Infrastructure
Infrastructure that was clicked together by hand is infrastructure nobody can safely change. Everything we touch ends up in version control, reviewable like application code, and reproducible from a clean account.
Alongside that sits the operational work: patching, capacity, backups, and the unglamorous maintenance that decides whether a platform is a foundation or a liability.
03 · DevSecOps
Security bolted on after a release is expensive and always incomplete. We put controls where the work already happens, so scanning, policy enforcement and evidence collection happen automatically every time something ships.
Where compliance is the driver, the goal is to make the evidence a by-product of normal engineering rather than a separate project competing for the same weeks.
04 · SRE
Reliability is an engineering discipline with numbers attached, not a personality trait. We define service-level objectives, instrument the services that matter, and design on-call rotations that people can survive.
Where reliability genuinely requires it, we introduce controlled failure testing to find out where the system actually breaks, rather than assuming.
05 · Cloud
Cloud spend grows quietly and infrastructure sprawl compounds. We help you get a structure you can reason about, with costs that are visible and attributable rather than a single surprising invoice.
We work with the major providers, and we will tell you when the honest answer is that you are on the wrong service or the wrong size entirely.
06 · MLOps
A model that cannot be reproduced is not in production, it is a rumour. We build the pipeline around versioned data, versioned code, tracked experiments and a deployment path for models that behaves like any other artefact.
07 · Platform
Platform teams exist to absorb work that every product team would otherwise repeat. We design internal platforms with a real support model and a real SLA, because an undocumented platform nobody is on call for is just another outage waiting to happen.
08 · Advisory
Sometimes the most valuable thing is an independent read on what you already have. We assess the real system, not the diagram, and hand you findings and a roadmap ordered by risk and effort.
We are explicit when the answer is that you do not need something yet. A roadmap nobody can resource is worse than no roadmap, because it looks like progress.
Tooling
We are tool-agnostic in principle and pragmatic in practice. These are what we reach for most often, chosen to fit the team you already have.
Ways to work together
Most engagements start with an assessment and settle into one of these shapes. All of them keep your code, accounts and documentation under your control.
An independent review of what you have, with written findings and a prioritised roadmap.
Build something specific: a pipeline, a landing zone, a migration, a platform.
We build and operate the platform, transferring to your team with documentation as we go.
Ongoing operational ownership of the platform, with an agreed scope and service level.
Experienced engineers working inside your team, your tools, your process, your standups.
A dedicated, small senior team owning a platform domain on a multi-year basis.
Sectors
Most platform problems are not industry-specific, but the constraints and the cost of getting them wrong are.
In practice
The situations we are most often brought into. These describe recurring problem shapes rather than client case studies — the specifics of your system are what matter, but the shape of the problem is often recognisable.
The pipeline takes hours, there is a manual approval chain nobody fully understands, and the last deployment of the week is the one that causes problems. The team batches changes to reduce exposure, which makes each deploy bigger and riskier.
Measure where the time actually goes before changing anything. Usually most of it is queueing rather than work: review waits, environment contention, and a single serial test suite. Then split the pipeline into stages that block at different points, so a formatting issue does not hold up a security scan.
Deploys get smaller and more frequent because the cost of each one drops. The batching behaviour disappears on its own, because it was a response to the old constraints rather than a preference.
A cluster was stood up during a period of enthusiasm, a couple of workloads moved onto it, and nobody owns it. It is now on an out-of-support version, running workloads nobody understands, with the only record of the deployment process being a document in someone's drive.
Inventory before anything else. Find out what is actually running, what depends on what, and what the stateful components are. Then decide, workload by workload, whether each belongs on Kubernetes, on a managed container service, or somewhere simpler. Migrating off a platform is a real project and should be scoped as one.
Whatever we choose, the outcome is a system someone actually owns, on a supported version, with a documented deployment path. That is worth more than any particular platform.
Spend has grown faster than the business, cost is reported as a single number, and the first instinct is a blunt cost-cutting exercise that quietly breaks something. Development environments are left running. Storage grows without bound. Nobody owns the number.
Attribution first, reduction second. Without tagging and visibility, any saving is a guess and the same cost reappears next quarter. We get cost attributable to teams and environments, then address the largest categories: idle non-production capacity, storage with no lifecycle policy, and over-provisioned instance types.
A number that is understood rather than merely smaller. That is what makes the saving hold, and it is usually the part the obvious approach skips.
A certification deadline approaches. Evidence that should be automatic is being assembled by hand into spreadsheets, taking weeks of somebody’s time, and is out of date the moment it is submitted. Everyone dreads the follow-up audit more than the first one.
Most of the required evidence is a by-product of work you already do: every deploy produces a version, an approver, a timestamp, a test result and an artefact. We wire the pipeline to collect and store it continuously, then close the genuine technical gaps that the audit will otherwise find.
The audit stops being a project and becomes a query. That is the whole objective, and it is a build exercise rather than a process exercise.
Monitoring was set up by adding anything that looked interesting. The result is hundreds of alerts, most of which are not actionable, so the on-call engineer has muted most of them. Meanwhile a genuine user-facing problem can be invisible because the alert that would have caught it was muted along with everything else.
Rebuild from user-visible symptoms downwards. Start with what customers actually experience, alert on that, then work backwards to the infrastructure signals that predict it. Delete everything that does not lead to a decision. Then test it by deliberately causing a problem and seeing whether the right person is told.
Fewer alerts, and the ones that remain are worth waking someone for. The important change is that alert fatigue stops masking real incidents.
Getting a change into production needs access to eleven systems, knowledge held by two people, and a sequence of steps that exists only in someone's head. Every new hire is a month of shadowing, and every departure takes that knowledge with it.
Fix the path of least resistance rather than documenting the maze. Automate access provisioning, make the deploy path identical for every service, and put a service template in place so a new service is created rather than assembled. Then write the documentation that automation does not cover.
Onboarding time, and the number of people who can deploy. Both are measurable, which makes the improvement easy to demonstrate to the people funding it.
None of these are really tool problems. Every one has an ownership or visibility problem underneath it — the Kubernetes nobody owns, the bill nobody is accountable for, the alerts nobody trusts, the knowledge held by a single person.
Tools are the visible symptom, and buying a new one is the most satisfying response because it is the only option that does not require anyone to change how they work. It is also the option most likely to leave the underlying problem exactly where it was. That is why our assessments start with what actually exists and who is actually accountable, before recommending anything.
FAQ
The things people ask on a first call, answered without the sales pitch.
Consulting is advisory: we assess what you have, design the approach, select tooling and help you decide what to build. Managed services are operational: ongoing responsibility for running the platform, maintaining pipelines, handling incidents and continuously improving it. Most engagements start as consulting and move to managed once the foundation is stable.
It depends entirely on what exists already, and anyone quoting a fixed timeline before understanding your environment is guessing. A single pipeline or landing zone is often weeks. A full platform transformation across multiple teams and environments is typically months, and is better delivered in phases than as one big-bang programme.
Often no. Kubernetes is a significant operational commitment, and for a lot of workloads managed platforms, serverless or plain infrastructure as code are the better answer. We will tell you if that is the case for your system, even though it is not always the more profitable recommendation for us.
Yes, and we prefer to. Replacing a toolchain that already works is rarely worth the disruption. We start with what you have, and only introduce something new where there is a concrete reason.
You do, without exception. Work lands in your repositories, under your cloud accounts, with your licences. We do not hold anything behind our own access, and we do not depend on ongoing fees for you to keep operating what we built.
Yes. We build the technical controls and automate the evidence collection these frameworks require, working alongside whoever runs your formal audit. Be aware of the distinction: we engineer the controls and the evidence, we are not the body that certifies you.
Assessments are typically a fixed fee with a defined scope. Delivery work is scoped and priced against a defined outcome, and ongoing managed work is priced monthly. We will give you a real number after understanding the environment, rather than a range designed to win the call.
Stabilisation comes before improvement. If a system is down or degrading, we address that first and discuss the root cause afterwards. For clients on a managed agreement we operate an on-call rotation; for project work we agree response expectations up front.
Yes. We work remotely as standard and collaborate in your repositories, your chat and your tooling. On-site attendance can be arranged where it genuinely helps, such as architecture workshops or handover periods.
Read access to the systems in question, someone technical who can answer questions, and honesty about constraints. That is genuinely all. A first conversation is useful, but it is not a prerequisite for us looking at the problem.
Tell us what you are running, what is breaking, and what you want it to look like. You will get a straight answer about whether we are the right fit.
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