DevOps & CI/CD – From Development to Production

Automated pipelines, container orchestration and test automation – so software is deployed faster and more reliably.

DevOps from real projects – in production since 2016

We did not learn DevOps as a concept – we built it in real projects: from the first Jenkins pipeline through Docker containerisation to Kubernetes clusters in medical-technology and industrial production environments. What we use has proven itself under real pressure.

CI/CD pipelines with Jenkins, GitLab CI, GitHub Actions
Docker containerisation for all deployment environments
Kubernetes orchestration (K8s, Helm, Portainer)
Build automation: Maven, Gradle, CMake, Ant
Artifact management: JFrog Artifactory, Gitea, Nexus
Test automation: JUnit, GTest, Cucumber/Gherkin, Squish (Qt UI)

What you get from it

Shorter release cycles

Automated pipelines reduce manual deploy steps to zero. Features reach customers faster, errors are caught earlier.

Reproducible builds

Docker containers and defined build scripts ensure every environment is identical – no more “works on my machine”.

Full traceability

JFrog Artifactory and Gitea secure every build artifact. You always know what was deployed when and where.

Technologies & tools

CI/CD platforms

Jenkins (Pipelines, shared libraries), GitLab CI, GitHub Actions, Gitea Actions

Declarative pipelines, shared libraries, quality gates, SonarQube integration

Containers & orchestration

Docker, Docker Compose, Kubernetes (K8s), Helm, Portainer

Multi-stage builds, container registries, rolling updates, auto-scaling

Build & artifact

Maven, Gradle, CMake, Ant, Conan (C++)

JFrog Artifactory, Gitea Artifactory, Nexus – versioned artifacts for all projects

Test Automation

JUnit 5, Mockito, GTest, Squish (Qt/QML UI-Tests), Cucumber/Gherkin (BDD), SonarQube

Unit, integration and UI tests directly in the pipeline, coverage targets and quality gates

Our approach

1
Pipeline analysis

Analyse existing build and deploy processes, identify bottlenecks and assess automation potential.

2
Pipeline design

Design the CI/CD workflow: triggers, stages, parallelisation, rollback strategies and notification logic.

3
Container strategy

Dockerfile creation, multi-stage builds, container registry setup and Kubernetes configuration for all target environments.

4
Automated tests

Integrate test suites into the pipeline, define quality gates and set coverage targets – no deployment without green tests.

5
Monitoring & alerting

Set up deployment monitoring, configure rollback automation and enable notifications for errors and anomalies.

FAQ

Common questions about DevOps & CI/CD

It depends on your infrastructure. Jenkins offers maximum flexibility and is unmatched for self-hosted setups; GitLab CI is more tightly integrated if you already use GitLab. We have used both in production projects and can advise you based on your situation.

Yes. We know Jenkins from years of production use. We migrate freestyle jobs to declarative pipelines, add shared libraries and integrate quality gates (SonarQube, test coverage).

Docker Compose is suited to local development environments and simple multi-container setups. Kubernetes (K8s) is for production, highly available deployments with auto-scaling, rolling updates and service discovery. We have used both in production projects.

Squish is a UI test framework specifically for Qt/QML applications. It enables fully automated UI tests of embedded UIs – in our current projects (HMI for household appliances) we use Squish to automate regression tests for touch interfaces.

A simple Jenkins pipeline for build + test + deploy: 1–3 days. A full DevOps infrastructure with Docker, Kubernetes, artifact management and test automation: 2–6 weeks, depending on complexity.

Deploy faster, deliver more safely

Let us automate your build and deployment processes. Initial assessment within 24 hours.

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