DevOps Tools
GitLab CI/CD Setup
GitLab CI/CD is one of the most powerful CI systems available — deep integration with GitLab's SCM, container registry, package registry, and deployment environments. We configure production-grade GitLab CI pipelines with multi-stage workflows, review apps, Auto DevOps features, and optimized runner infrastructure.
Need this done for your project?
We implement, you ship. Async, documented, done in days.
What We Deliver
Production-ready .gitlab-ci.yml with multi-stage pipelines (build, test, security, deploy), environment configurations (review, staging, production), container building and registry push, deployment to Kubernetes or cloud services, include/extend patterns for DRY configuration, runner configuration (shared or dedicated), and pipeline optimization for speed.
Pipeline Architecture
We design pipelines with clear stages: build (compile, bundle, container image), test (unit, integration, e2e), security (SAST, dependency scanning, container scanning), deploy-staging (automatic on main branch), and deploy-production (manual trigger or tag-based). DAG (directed acyclic graph) mode runs independent jobs in parallel. Rules and conditions control which jobs run for which events.
Environments & Review Apps
GitLab environments track what's deployed where. Review apps spin up per-merge-request preview environments with dynamic URLs. Staging deploys automatically on merge to main. Production deploys on manual trigger or tag. Environment dashboards show deployment history with one-click rollback. Auto-stop cleans up review apps after merge.
Container & Package Registry
GitLab's built-in container registry stores Docker images alongside your code. We configure multi-stage Docker builds with layer caching, image scanning for vulnerabilities, and tag-based versioning. Package registry stores npm, PyPI, Maven, or NuGet packages for internal distribution. Both registries integrate natively with CI pipeline authentication.
Runner Optimization
GitLab runners execute pipeline jobs. We configure dedicated runners on your infrastructure for faster builds and cost control. Docker executor provides job isolation. Kubernetes executor auto-scales runners as pods. Caching (S3 or GCS-backed distributed cache) shares build artifacts across jobs and pipelines. Runner tags route specific jobs to appropriate hardware.
How It Works
Purchase the engagement, submit your async brief with your repository and deployment requirements, and receive production-ready GitLab CI configuration within 5–7 business days. Pipeline files, runner setup, and documentation included.
Why Anubiz Engineering
100% async — no calls, no meetings
Delivered in days, not weeks
Full documentation included
Production-grade from day one
Security-first approach
Post-delivery support included
Ready to get started?
Skip the research. Tell us what you need, and we'll scope it, implement it, and hand it back — fully documented and production-ready.