CI/CD pipelines that take each merge to production with tests, approvals and a way back

A CI/CD pipeline usually includes stages that build the code, run linting and automated tests, package a versioned artefact such as a Docker image, and deploy it through staging to production. Around those stages sit caching for speed, approval gates where your process needs a sign-off, notifications and a rollback path. We design the stages around your stack and risk, so a marketing site and a payments API get very different pipelines.

Timelines depend mainly on how many services you run, how much test coverage already exists and how far your environments have drifted apart. For a single application with some tests, a first working pipeline from commit to staging is often in place within a few weeks of discovery. Production deployment, preview environments and progressive releases are then added in stages, so you see value early rather than waiting for a finished platform.

Use the CI tool closest to where your code already lives, unless there is a strong reason not to. Teams on GitHub usually do well with GitHub Actions and teams on GitLab with GitLab CI, because permissions, pull requests and pipelines stay in one place. Jenkins still suits organisations with heavy on-premises build needs or large plugin investments, but it needs more upkeep. Whichever you choose, we keep pipeline logic in versioned files and small scripts rather than tool-specific plugins, so a later move stays manageable.

We run database migrations as a controlled pipeline step and design them to be backward compatible, so the previous application version still works if we need to roll back. In practice that means expand-and-contract changes: add new columns or tables first, deploy code that uses them, then remove old structures in a later release. Destructive migrations require an explicit approval and a verified backup before they run.

Rollback means redeploying the previous known-good artefact, not rebuilding old code under pressure. Because every build produces an immutable, versioned image or package, the pipeline can return production to the last release in a single step. With blue-green or canary deployments, a failing release can often be stopped before most users see it. We rehearse rollbacks during setup so your team knows the process works before it is needed.

Our pipelines can deploy to virtual machines, managed container services, Kubernetes clusters, serverless functions and front-end platforms such as Vercel, on AWS, Microsoft Azure or Google Cloud. You do not need Kubernetes to benefit from CI/CD, and for a single application a simpler target is often cheaper and easier to maintain. We match the release method to the platform, for example rolling updates on virtual machines or canary releases on a cluster.

Usually because staging is not running the same thing as production: a different build, different configuration, different dependency versions or very different data. We close those gaps by building each artefact once and promoting it unchanged, injecting only the configuration values that must differ, and creating both environments from the same Terraform modules and images. Post-deployment smoke tests then confirm the release works in production before all traffic moves to it.

Continuous delivery keeps every change ready to release, with a person deciding when it goes to production, while continuous deployment releases every change that passes the pipeline automatically. Both build, test and package each commit the same way. Continuous deployment needs dependable automated tests, monitoring and fast rollback, because nobody checks a release before customers see it. A common pattern is continuous delivery for core transactional systems and continuous deployment for lower-risk services and front ends.

Costs depend on scope: the number of applications and environments, your cloud provider, the current state of tests and infrastructure, and whether you need ongoing support. We start with a discovery call and a short audit of how you release today, then give a fixed quote for the agreed pipeline work. We also estimate running costs for CI minutes, container registries and environments so there are no surprises later.

Yes, we change delivery systems incrementally so your team keeps shipping throughout. New pipelines usually run alongside the existing process first, deploying to a non-production environment until the results match. We then switch one service or environment at a time and keep the old path available until the new one has handled several real releases. Changes to shared pipeline templates go through pull requests and review like any other code.

We track the four DORA metrics: deployment frequency, lead time for changes, change failure rate and time to restore service. They are calculated from your repository, pipeline and incident data rather than surveys or estimates. We record a baseline during the audit and review the trend with you as the work progresses. Developer feedback on build times and flaky tests completes the picture, because slow feedback rarely shows up in headline numbers.

Your team does, with as much or as little support from us as you want. Pipelines, Terraform and scripts are committed to your repositories, documented and reviewed with your engineers during the project, so they are comfortable changing them. Before handover we walk through common tasks such as adding a service, upgrading a runtime version or changing an approval rule. Ongoing support and further improvements can be agreed separately.