CI/CD and GitOps pipelines that ship safely

What does a CI/CD engagement deliver?

A pipeline design that separates build, test, publish and deploy so each stage can be reasoned about and timed. GitOps delivery where the cluster state is what the repository says it is, with Argo CD or Flux reconciling it and a reviewable pull request as the only way to change production. Builds on GitHub Actions or GitLab CI, with caching, parallelism and self-hosted runners where they pay off. A migration plan off Jenkins or any pipeline that has become the thing everyone is afraid to touch. And the guards: required checks that cannot be skipped, protected branches, and pipelines that prove their own correctness.

Argo CD or Flux: how do we choose?

On who operates it and what they need to see. Argo CD gives a web interface, application sets for many clusters, and RBAC organised around applications; teams with many services and a platform team to run the control plane tend to choose it. Flux is a set of controllers with no interface, drives everything from Git, and suits teams that already live in the terminal and want fewer moving parts. Both reconcile, both roll back, both work with Helm and Kustomize. We have run both in production and the assessment names which one fits you and why.

How do we migrate off Jenkins without stopping releases?

One pipeline at a time, newest or simplest first. Each pipeline is rebuilt on the target system, run in parallel with the Jenkins job for a few releases, and compared on outcomes and duration. Shared Jenkins libraries become reusable workflows or templates. Secrets move to the target’s own store with short-lived credentials where the cloud allows it. When the last job has shipped from the new system, Jenkins is read-only for a month and then gone. Releases never stop because no pipeline is cut over until its replacement has proven itself.

How do we run GitHub Actions and GitLab runners cheaply?

Self-hosted, autoscaled, and sized for the job. Hosted minutes are the right choice for small teams; past a certain volume, or for jobs that need private network access, arm64 builds or large memory, a pool of self-hosted runners that scales to zero between jobs costs a fraction. We set up the pool, the images, the autoscaling and the alerts that tell you when jobs queue, and we measure the before-and-after on your own pipelines.

How does an engagement run?

A discovery call to understand what ships today and what slows it. An assessment of the pipelines with timings, failure rates and the migration order. The implementation with your team, one pipeline at a time, with the old path alive until the new one has earned trust. A handover with the runner operations, the guards and the runbooks. Pricing follows the discovery call, once we know the scope.