GitHub Actions, GitLab CI, or CircleCI -- which should we use?

GitHub Actions is the right default if your code is already in GitHub -- it's tightly integrated, the marketplace has actions for most common tasks, and the pricing is reasonable for most team sizes. GitLab CI is the natural choice if you're using GitLab for source control and want everything in one platform. CircleCI and Buildkite have stronger performance optimisation features for large pipelines with many parallel jobs. We use whichever platform your team is already in, or recommend based on your pipeline complexity and team size if you're starting fresh.

How do you handle database migrations in a CI/CD pipeline?

Database migrations run as a pipeline step before the new application version starts serving traffic. The standard pattern: run migrations against the target database as part of the deployment, then start the new application. For zero-downtime deployments, migrations must be backwards-compatible -- the old version of the application must work against the new schema during the transition window. This means avoiding breaking changes like column renames or removals in the same deployment as the code change. We design the migration strategy alongside the pipeline so the deployment order is correct.

How long does CI/CD pipeline setup take?

A pipeline for a single service -- test, build, deploy to staging, with production approval gate -- typically takes 2 to 4 weeks depending on the existing codebase and infrastructure. A more complete setup covering multiple services, multiple environments, deployment approvals, rollback automation, and secrets management typically takes 6 to 10 weeks. We assess your current deployment process and codebase before scoping.

What happens when a test in the CI pipeline is flaky?

Flaky tests -- tests that sometimes pass and sometimes fail for reasons unrelated to code changes -- are one of the biggest sources of CI friction. The standard approach is to quarantine the flaky test (move it to a separate suite that doesn't block merge) while the root cause is investigated, rather than retrying until it passes. Retrying flaky tests masks the problem and trains developers to ignore red pipelines. We include a flaky test triage process as part of CI setup so the team has a clear process rather than working around the failures.

GitHub Actions, GitLab CI, or CircleCI -- which should we use?

GitHub Actions is the right default if your code is already in GitHub -- it's tightly integrated, the marketplace has actions for most common tasks, and the pricing is reasonable for most team sizes. GitLab CI is the natural choice if you're using GitLab for source control and want everything in one platform. CircleCI and Buildkite have stronger performance optimisation features for large pipelines with many parallel jobs. We use whichever platform your team is already in, or recommend based on your pipeline complexity and team size if you're starting fresh.

How do you handle database migrations in a CI/CD pipeline?

Database migrations run as a pipeline step before the new application version starts serving traffic. The standard pattern: run migrations against the target database as part of the deployment, then start the new application. For zero-downtime deployments, migrations must be backwards-compatible -- the old version of the application must work against the new schema during the transition window. This means avoiding breaking changes like column renames or removals in the same deployment as the code change. We design the migration strategy alongside the pipeline so the deployment order is correct.

How long does CI/CD pipeline setup take?

A pipeline for a single service -- test, build, deploy to staging, with production approval gate -- typically takes 2 to 4 weeks depending on the existing codebase and infrastructure. A more complete setup covering multiple services, multiple environments, deployment approvals, rollback automation, and secrets management typically takes 6 to 10 weeks. We assess your current deployment process and codebase before scoping.

What happens when a test in the CI pipeline is flaky?

Flaky tests -- tests that sometimes pass and sometimes fail for reasons unrelated to code changes -- are one of the biggest sources of CI friction. The standard approach is to quarantine the flaky test (move it to a separate suite that doesn't block merge) while the root cause is investigated, rather than retrying until it passes. Retrying flaky tests masks the problem and trains developers to ignore red pipelines. We include a flaky test triage process as part of CI setup so the team has a clear process rather than working around the failures.

How many steps in your current deployment process require a developer to manually SSH into a server, run a command, and watch the output to verify it worked?
When a deployment goes wrong, how long does it take to roll back to the previous working version -- and is the rollback process documented anywhere?

A deployment that requires a developer to manually run steps and watch for errors is a deployment that will eventually go wrong at the worst possible moment.

Continuous integration and continuous deployment pipelines automate the steps between a developer pushing code and that code running in production. Tests run automatically on every push. Builds are reproducible. Deployments to staging happen without intervention. Production deployments happen through a controlled, auditable process.

We design and set up CI/CD pipelines on GitHub Actions, GitLab CI, CircleCI, and Buildkite for web applications, mobile apps, APIs, and data services. From the first pipeline to a mature multi-environment setup with approval gates, rollback capability, and deployment tracking.

Automated test and build pipeline triggered on every pull request -- failures block merge
Zero-downtime deployment to staging on merge to main, with manual approval gate before production
Rollback to any previous deployment in under 5 minutes from the pipeline dashboard
Pipeline runs that complete in under 15 minutes so developers get feedback without waiting half a day

RaftLabs designs and builds CI/CD pipelines on GitHub Actions, GitLab CI, CircleCI, and Buildkite -- automated testing, reproducible builds, zero-downtime deployments, and rollback capability. For web apps, APIs, mobile apps, and data services. Most CI/CD projects deliver in 4 to 8 weeks at a fixed cost.

Every manual deployment step is a risk. Someone forgets a step, runs a command in the wrong environment, or skips the verification check because it's late and the hotfix needs to go out. CI/CD pipelines eliminate that risk by encoding the deployment process as code -- the same steps run the same way every time, against every commit, without anyone watching over it. The deployment process stops being something that lives in a runbook or a senior engineer's memory.

Beyond reliability, automated pipelines change the economics of shipping software. When deploying takes two hours of senior engineering time and carries real risk of breaking production, teams batch changes into large releases to amortize the cost. When deploying takes five minutes and is fully automated, teams ship smaller changes more often -- which means fewer things in flight at once, faster detection of problems, and faster recovery when something goes wrong.

What we build

CI pipeline (test and build)

Pipeline triggered on every pull request: unit tests, integration tests, linting, static analysis, security dependency scanning. Build step that produces a reproducible artifact -- Docker image, compiled binary, or packaged deployment. Pipeline result visible in the PR before merge is allowed, so broken builds never reach the main branch. Artifact stored and versioned so the same artifact that passed tests is the one that gets deployed.

CD pipeline (deploy to staging)

Automated deployment to staging on merge to the main branch. Environment promotion that uses the same artifact built by CI rather than building again -- so staging runs exactly what passed the test suite. Smoke tests after deployment to verify the service started correctly and is serving traffic. Slack or Teams notification when deployment completes or fails, so the team knows without checking the pipeline dashboard.

Production deployment with approval gates

Promotion from staging to production requiring explicit approval from a designated reviewer. Deployment window enforcement for services with change management requirements -- no production deploys on Friday afternoons. Deployment record capturing who approved, when, and what version was deployed. Full audit trail for compliance and incident investigation without separate tooling.

Rollback and deployment history

Every deployment tagged with the exact commit and artifact version so there is no ambiguity about what is running in each environment. One-click rollback to any previous deployment from the pipeline dashboard. Automated rollback trigger when post-deployment health checks fail -- the pipeline detects the problem and reverts without requiring manual intervention. Deployment history retained for audit and incident investigation.

Pipeline performance optimisation

Caching of dependencies and build artifacts across pipeline runs to avoid repeating work that hasn't changed. Parallel job execution for independent test suites so the full test pass completes faster. Selective test execution for monorepos that only runs tests affected by changed files. Target pipeline completion time under 15 minutes -- developer feedback loops that require waiting half a day create pressure to skip tests or batch changes.

Secret and environment variable management

Secrets stored in GitHub Secrets, AWS Secrets Manager, HashiCorp Vault, or GCP Secret Manager rather than hardcoded in pipeline config or checked into source control. Environment-specific variable injection at deploy time so the same pipeline configuration serves dev, staging, and production. Rotation procedures for secrets that expire or need periodic rotation. Audit log of who accessed which secrets and when.

Have a deployment process that needs fixing?

Tell us your current deployment steps, how long they take, and what breaks most often. We'll scope the CI/CD pipeline and give you a fixed cost.

Talk about your CI/CD project

DevOps as a Service -- full DevOps capability overview
Kubernetes Infrastructure -- container orchestration that CI/CD deploys into
Infrastructure as Code -- the infrastructure your pipelines deploy to, version-controlled
Cloud Monitoring and Observability -- monitoring what your pipelines deploy

Cloud Migration -- move existing infrastructure to cloud before adding CI/CD
Custom Software Development -- software projects that ship with CI/CD from day one
Quality Assurance -- automated testing that feeds into your CI pipeline

Frequently asked questions

: GitHub Actions is the right default if your code is already in GitHub -- it's tightly integrated, the marketplace has actions for most common tasks, and the pricing is reasonable for most team sizes. GitLab CI is the natural choice if you're using GitLab for source control and want everything in one platform. CircleCI and Buildkite have stronger performance optimisation features for large pipelines with many parallel jobs. We use whichever platform your team is already in, or recommend based on your pipeline complexity and team size if you're starting fresh.
: Database migrations run as a pipeline step before the new application version starts serving traffic. The standard pattern: run migrations against the target database as part of the deployment, then start the new application. For zero-downtime deployments, migrations must be backwards-compatible -- the old version of the application must work against the new schema during the transition window. This means avoiding breaking changes like column renames or removals in the same deployment as the code change. We design the migration strategy alongside the pipeline so the deployment order is correct.
: A pipeline for a single service -- test, build, deploy to staging, with production approval gate -- typically takes 2 to 4 weeks depending on the existing codebase and infrastructure. A more complete setup covering multiple services, multiple environments, deployment approvals, rollback automation, and secrets management typically takes 6 to 10 weeks. We assess your current deployment process and codebase before scoping.
: Flaky tests -- tests that sometimes pass and sometimes fail for reasons unrelated to code changes -- are one of the biggest sources of CI friction. The standard approach is to quarantine the flaky test (move it to a separate suite that doesn't block merge) while the root cause is investigated, rather than retrying until it passes. Retrying flaky tests masks the problem and trains developers to ignore red pipelines. We include a flaky test triage process as part of CI setup so the team has a clear process rather than working around the failures.