CI/CD automation and deployment control in your tenant workspace

Running in production today: CI/CD pipelines, the deployment control panel, the approvals queue, and the InfroOps AI assistant.

Most teams do not have one CI system — they have a GitHub Actions setup someone started, a Jenkins server that predates everyone, and a GitLab project from an acquisition. Each has its own screen, its own login and its own notification noise, which in practice means nobody watches all of them. The first failure of a multi-CI setup is simply not seeing a red build until it blocks a release.

Connecting each provider by webhook puts every run on a single dashboard that updates live over WebSockets. The point is not to replace the CI engines — they keep doing the building — but to give engineering leads one place where run status and failure patterns across all of them are visible at a glance, tenant-scoped to your workspace.

That shared view also changes conversations: instead of "was that fixed?" across three tools, the team looks at one run list, sees which pipelines fail repeatedly, and decides what to stabilise first.

Shipping is a control problem as much as a speed problem. Infronest treats a deployment as a first-class request: it names a target — VPS, Docker, Kubernetes or cloud — carries a rollout strategy, and enters an approvals queue where the owner signs off before anything moves. That single gate is often the difference between a deliberate release and a Friday-evening surprise.

Strategy is chosen to fit the risk. A rolling update replaces instances gradually; blue-green stands the new version up alongside the old and switches over; canary sends a slice of traffic to the new version first; recreate tears down and redeploys when simplicity matters more than zero downtime. Because rollback policies are declared before the rollout, reversing a bad release is a decision already made, not a debate held mid-incident.

And when a build or deploy does fail, the InfroOps AI assistant is on hand to help triage it, while the audit trail records the whole sequence — submission, approval, rollout, rollback — for the post-mortem.

Pipeline control answers "what is being built and deployed?"; it deliberately does not answer "who can touch the code?". That is the job of the Git governance module, which covers provider configuration, repository visibility, user and access views, and security posture analytics across your repositories.

Used together, the two give a tenant a clean separation of concerns: governance keeps repository access reviewable, while CI/CD automation keeps what flows out of those repositories visible and approval-gated. Both sit inside the same workspace as your monitoring and reporting, so the deploy that caused a CPU spike and the alert that caught it are two tabs apart, not two products apart.