DevOps and delivery engineering
Most DevOps requests arrive named after a tool. The useful conversation is one layer down: what actually makes a release slow, where the risk really sits, who owns the platform after we leave, and which of these five technologies you can safely leave alone.
01Capabilities
The fix for one layer is rarely the fix for another
Four layers, and they need separating: the release path from a code change to production, the packaging that makes a build run the same everywhere, the platform underneath, and the network layer in front. This work sits inside DevOps consulting and cloud infrastructure engineering. Which cloud you run on is cloud consulting, not a tooling choice.
Release paths that are boring on purpose
One pipeline in version control, one tested package promoted through each environment rather than rebuilt at every stage, keys pulled from a vault, and approvals nobody can grant themselves. In fintech and healthcare that trail is a compliance record, not housekeeping.
Builds and environments that reproduce
Containers with fixed base images, no build tooling left in the running system, and local setups that match production minus the scale. Most works-on-my-machine incidents turn out to be configuration and leftover state on a server rather than code.
Runtime platforms sized to the team
A managed container service, meaning one your cloud provider runs for you, or a cluster you run yourself. The choice comes from how many independent teams you have and who takes the call at three in the morning. We build both, and recommend the smaller one more often than the market does.
The request path and the edge
Cache rules that reflect what is genuinely shareable, protection against bots and abusive traffic, rate limits, and domain moves with a rehearsed way back. This matters most in e-commerce work, where blocking real customers is the expensive failure rather than letting a bot through.
02Stack
What we reach for here, and what we would leave alone
One row per page in this cluster, with the verdict we would give you on a call. Every row has exactly one destination, so the whole row is the link.
| Technology | What that means in practice |
|---|---|
| Azure DevOps | The release pathWhere most Microsoft-based teams already are, and where a slow, manual release is usually fixed. It ships to any cloud, and to your own servers.Azure DevOps engineeringOr book a meeting |
| Docker | ReproducibilityThe problem containers genuinely solve. Where nobody can copy production closely enough to debug it, this is the layer to start at rather than a bigger platform.Docker containerizationOr book a meeting |
| Kubernetes | At real scaleExcellent at what it does, and it charges rent in attention every week whether or not you use it. The test is several teams releasing on their own, not traffic volume.Kubernetes engineeringOr book a meeting |
| Cloudflare | Only in frontFits when the problem really does sit between your visitors and your application. Where the wait is your own database, caching hides it until real customers find it again.Cloudflare edge engineeringOr book a meeting |
| Git | ReferenceThe foundation under every row above. What a repository looks like decides whether we can take a codebase on safely, which is why we read it first.Git version controlOr book a meeting |
03Fit
Which layer your problem is actually in
Almost every request here arrives named after a tool, and the tool is usually not the problem. This is the call we would have with you: what the symptom is, which layer it lives in, and which of these five you can leave alone. Two rows start with a diagnosis before anything is bought.
| Your situation | What we recommend |
|---|---|
| Releases are slow, manual, and slightly different every time | Fix the path firstIn whichever toolchain your code and your staff sign-ins already live in: Azure DevOps where that is Microsoft, GitHub Actions where the code is on GitHub. Moving between the two for tidiness spends real capacity and produces nothing a user can see. |
| Nobody can copy production closely enough to debug it | ContainersReproducibility is what Docker genuinely solves, and matching local and test setups is where it pays back fastest. A container does not make a manual release automatic, so this rarely replaces the row above. |
| One team, a handful of services, traffic that does not swing wildly | Managed containersA managed container service (ECS with Fargate, Azure Container Apps, Cloud Run) runs the same images with a fraction of the operational surface, and you keep the option to move later. Kubernetes pays off once the load and the team grow into it. |
| Dozens of services, several teams releasing independently, and a named owner for the platform itself | KubernetesOn a control plane your provider runs. This is the case it was built for. The test is independent releases plus somebody whose job description includes reading upgrade notes. |
| The site feels slow, or bot traffic is winning | Measure firstIf the wait is your own database, fix that, because caching would hide the problem until real customers find it again. Where it genuinely sits in front of the application, Cloudflare fits, provided somebody reads the logs and tunes the rules. |
| Shipping feels slow and nobody can name the reason | Repository firstRead the repository first. Month-old branches, no automatic build on the main branch, credentials sitting in the history and no agreed way to merge slow a team more than any tool, and they are fixed in the workflow itself. That diagnosis is version control and review discipline. |
Scope
What we own is whether releasing gets safer and duller, measured by how often you ship and how often a release has to be undone. That includes the parts nobody enjoys. Where keys live. Whether the package that was tested is the one that shipped. Whether a rule change in front of the site can lock out real customers. Whether your team can add a service or upgrade the platform without us in the room. If a handover only works while we are still available, we have not finished. We work to ISO 27001:2022 and ISO 9001:2015, audited by Quay Audit UK. Want an independent verdict on how you deliver today rather than a proposal? That is a quality audit. Where the platform is fine and the question is who watches it, that is maintenance and support.
We start DevOps work by timing a real release end to end. Within an afternoon, that shows which layer needs the work, whether the pipeline, the containers, the platform or the edge. Then we size the platform, Kubernetes included, to your team.
Ihor PrudyvusDelivery Director, unicrew04Delivery
How a platform engagement sizes itself before it builds
The first step measures the problem, and everything after it is sized to what that measurement shows.
- Measure the release, not the diagramTime a real release end to end, including the waiting and the person who has to be online, then read the last few incidents. Incidents tell the truth faster than any architecture document, and the constraint they reveal is usually not the tool anyone named.
- Get to one deploy pathEstates that hurt usually have three ways to deploy and no agreement on which is correct. One reference path in version control, one tested package promoted forward, tests that block a bad release rather than decorate it, and the old paths retired instead of left available.
- Put the workload on the least platform that fitsBoth options costed against your real load, with the obligations written down: who upgrades what, who is on call, what breaks at three in the morning. Foundations go in before workloads, because retrofitting access rules onto a busy platform is a worse job.
- Hand over the operational realityRunbooks, an upgrade calendar rather than an upgrade intention, dashboards someone will actually open, how to undo a release, and an honest conversation about who carries the pager. We scope the ongoing side as carefully as the build, because a handover starts the operating phase rather than ending it.
05Case studies
A booking platform, containerized and moved
06Client voices
Two clients, on what delivery felt like from their side
I’ve been impressed by their work ethic and how they put me as the customer first. They’re always ready to jump in and go the extra mile. They put great effort into communicating to ensure that tasks are updated in a timely manner. The team keeps us apprised of exactly what they’re working on.
unicrew met deadlines and stayed on budget. The team went above and beyond what I expected; unicrew was excellent. It was more of a full-service provision than expected, so I was delighted.
07Questions
Five answers we give before anyone buys a platform
When you have enough independently released services and teams to need scheduling, plus a named owner for the platform. Traffic volume is not the test, and we settle the real one early, before anything is built. One team with a handful of services gets the same result from a managed container service. The full argument is on the Kubernetes page.
With a measurement rather than a purchase. We time a real release, find the manual steps and the stages that wait on each other, and check whether the main branch even builds from a clean copy. The wins are usually caching, splitting tests across machines, and one tested package promoted instead of rebuilt per stage. Sometimes the finding is that the real problem is test coverage, which is QA and test automation.
Yours, unless there is a concrete reason to move. Nothing we earn depends on which tool you use, and a migration between tools spends real delivery time while producing nothing a customer can see. So we build in Azure DevOps, GitHub Actions, GitLab CI or Jenkins as we find them, and recommend a change only when the current tool is blocking something you need.
You can bring our engineers onto your team, and on platform work that is often the sensible arrangement, because your people hold the incident history. Every engineer comes with ownership of the result: an architect outside the delivery team reviews the platform and pipeline design, and the work goes through the same QA practice as our own projects. Team extension is managed teams; the outcome is DevOps consulting.
A scoping call with an engineer. For anything that already exists we ask for read access to the code and the release setup, plus an honest description of how the last release went, because that reveals the manual steps no diagram shows. What comes back is written: what to change first, what to delete, and what to leave alone. Work usually starts two to four weeks after we agree scope.
Services we deliver in DevOps
All servicesReleases painful, or weighing up which platform fits?
Send us how a release happens today, step by step, and what you run it on. You will get an engineer's read on which layer your problem is in, what we would fix first, and the platform size that fits your team and your bill.