DevOps & CI/CD
We set up the path from a code change to production: a build and test run on every commit, environments defined as code, a deployment anyone on the team can run, and alerts on errors and slow responses.
DevOps and CI/CD means automating the way a code change reaches production: the build, the tests, the deployment and the environments the system runs in, plus the monitoring that shows when something breaks.
It is for teams whose releases take an evening or a weekend, or depend on one or two people who know the steps. We start with one application and hand the pipeline and runbooks to your team as we go.
Is this the right fit?
You may need this if
Releases are manual and run late
Each deployment follows a checklist, takes an evening, and needs several people on a call.
Only one person can deploy
The steps live in someone's head, so releases wait whenever that person is on leave.
Test and production environments differ
A change passes in UAT and fails in production because servers were configured by hand.
Users report problems first
There is no alerting on errors or slow responses, so users find failures before your team does.
What we deliver
CI/CD pipelines
Build, test and deploy on every change, the same way to every environment, with a rehearsed rollback.
Infrastructure as code
Servers, networks and databases described in Terraform, so environments can be rebuilt and every change is reviewed.
Containers, and Kubernetes where it fits
Docker images for each service, and Kubernetes only where scale justifies the operating work.
Monitoring and alerting
Central logs and error tracking, with alerts on a few signals such as error rate and response time.
Secrets and access
Credentials in a secrets store with rotation and least-privilege access, out of config files and chat threads.
How we work
Every engagement runs through the same six-stage fitting process, from the first consultation to long-term care. The stages stay in the same order; how deep each one goes depends on the project.
See the full fitting process- ConsultationDiscover
- MeasureAnalyze and architect
- PatternDesign
- FittingBuild with you
- FinishingHarden and launch
- AftercareMaintain and support
How we decide what to automate first
We begin by tracing how one change reaches production today and noting where time goes and incidents start. The delay may sit in the pipeline, in thin test coverage, in servers configured by hand, or in an approval step nobody owns.
From there the order is usually the same. A build that runs on every change comes first. Environments come next, defined as code so test and production match. Then the deployment, scripted so anyone on the team can run it, with a rollback we try out before go-live.
We keep the tooling as simple as the workload allows. A managed container service with a plain pipeline is enough for many systems, while Kubernetes adds daily operating work your team would carry after we leave. Monitoring goes in before launch, with alerts on the few signals that mean users are affected.
Organizations we work with
Engagements span build, integration and long-term support. Named with permission; clients under NDA are not listed.
Related services
- Cloud Migration & Architecture: when the move to AWS happens at the same time.
- Software Testing & QA: when automated tests are too thin to catch problems.
- Application Modernization: when the application itself is hard to deploy.
- Maintenance & Support: when you want us to run the platform after handover.
Frequently asked questions
How much does DevOps and CI/CD work cost?
It depends on how many applications and environments are in scope, how much automated testing exists, your current tools and hosting, and whether you want ongoing platform work afterwards. We give a written estimate after a short scoping call, or price against the TOR for public-sector work.
How long before we see a difference?
A working build and deployment pipeline for one application usually takes four to eight weeks. Smaller, more frequent releases tend to follow once deployments stop taking an evening. How quickly depends mostly on your team and its approval process.
Do we need Kubernetes?
Probably not, unless you run many services or need to move between providers. Kubernetes brings daily operating work, including cluster upgrades, security patches and capacity planning. For many systems a managed container platform with a simple pipeline is easier to run, and we recommend Kubernetes when the scale justifies it.
Can you work with our existing tools and cloud setup?
Yes. If you use GitLab, Azure DevOps or Jenkins, we build on it, and we improve an existing cloud setup step by step without a migration. Our deepest experience is with AWS; the same practices apply on other providers, and we will tell you where our experience is thinner.
How do you handle production access and separation of duties?
We design it explicitly, because auditors ask. Once releases run through a pipeline, developers no longer need production credentials to deploy. Approvals can be built into the pipeline, each deployment is logged with the person who triggered it, and direct access is limited to a small group for emergencies.
Next step
Start with a conversation
Tell us about the problem you are trying to solve. A senior person reads every inquiry and replies with our view of fit, scope and cost, including when another option would suit you better.