CI/CD (Continuous Integration / Continuous Delivery)

Continuous Integration means every developer commits code to the shared main branch frequently (ideally multiple times per day) rather than working in long-lived branches. Each commit triggers an automated pipeline that: compiles the code, runs the full unit and integration test suite, performs static analysis and linting, builds a deployable artifact, and reports success or failure within minutes. The critical cultural rule of CI: broken builds are the team's highest priority to fix — a failing main branch blocks everyone and immediately reports the team's readiness to deploy. CI prevents the "integration hell" that occurs when developers work in isolated branches for weeks and then must merge all their changes simultaneously, causing conflicts and bugs that take days to untangle. Product Ops supports CI by ensuring product specifications include clear, testable criteria that engineers can translate into automated tests.

Both involve the automated preparation of release artifacts after CI passes, but differ in the final step. Continuous Delivery means the software is always in a deployable state — passing all automated checks, packaged and ready to ship — but a human makes the explicit decision to deploy to production. A deployment is a one-click action taken when the business is ready. Continuous Deployment goes one step further: every commit that passes the CI pipeline is automatically deployed to production without human intervention. Most SaaS companies use Continuous Delivery (human-triggered deployment) combined with feature flags for controlled rollout. Continuous Deployment is adopted by teams with extremely mature testing infrastructure and monitoring. Product Ops influences the deployment decision cadence — aligning deployment timing with the release calendar to ensure GTM readiness accompanies production changes.

A production-grade CI/CD pipeline (implemented in GitHub Actions, CircleCI, GitLab CI, or Jenkins) includes these stages: Trigger (on every pull request and merge to main branch); Build (compile source code, resolve dependencies, create Docker image); Unit Tests (fast tests covering individual functions and components, target runtime < 5 minutes); Integration Tests (test interactions between components, some external services mocked, target < 15 minutes); End-to-End Tests (browser automation testing critical user flows against a staging environment, target < 30 minutes); Security Scan (SAST tools scan for vulnerable dependencies and code-level security issues); Artifact Build and Push (production-ready artifact pushed to container registry); Staging Deployment (automatic deployment to staging environment for human QA verification); and Production Deployment (manual trigger or fully automated, with feature flag enabling as the rollout control). Product Ops monitors pipeline health metrics (build success rate, pipeline duration trends) as engineering velocity indicators.