From CI/CD platform to AI factory
AI fabrics — fleets of agents that plan, code, test, and ship — don't replace delivery infrastructure. They multiply the demand for it. KubeRocketCI is the factory floor: the harness, guardrails, and disposable environments your agents need to produce software you can trust.
The market already moved
In 2026 agentic development stopped being a pilot. The numbers from GitHub alone show a delivery layer under more load than at any point in its history.
commits processed by GitHub weekly — on pace for 14 billion in 2026
pull requests opened by AI agents in a single month — 4x growth in six months
GitHub Actions CI minutes in one week — up from 500M weekly in 2023
the infrastructure capacity GitHub discovered it needed — it had planned for 10x
Sources: GitHub platform reports, 2026 · Gartner Hype Cycle for Platform Engineering, 2026
The layer that didn't vanish
When coding agents arrived, some predicted pipelines and quality gates would fade away. The opposite happened: every agent-opened pull request triggers a pipeline, a review, a scan, a deployment. The delivery layer transformed from a developer convenience into the control point of the whole factory — and it has never been more active.
Agents don't get tired, but they do get things wrong — at machine speed. A fabric only compounds value when every hypothesis it produces is validated by infrastructure that can spin up guardrailed environments in minutes, run the gates, promote what passes, and destroy the rest.
of agentic AI projects will be canceled by 2027, Gartner predicts — not because models fail, but because governance wasn't built for autonomous actors. The platforms that survive route agents through the same golden paths as humans.
What an AI fabric needs from its factory
Six capabilities separate a fleet that ships from a fleet that floods your review queue.
Execution harness
A standing loop every change runs through: build, test, lint, scan, review. Agents produce output; the harness turns it into evidence.
Quality gates
Autotests and code-quality thresholds decide what gets promoted. When changes arrive at machine speed, the gate — not the author — is the trust boundary.
Guardrails and governance
Agents are a new class of platform user. RBAC, scoped permissions, and policy-aware self-service keep the fleet on the paved road.
Audit trail by design
GitOps stores every configuration and every change as a commit. Everything an agent does is reviewable, revertible, and attributable.
Ephemeral environments
A disposable, production-like environment per hypothesis: create, validate, tear down clean. Fast enough that agents never queue.
Fleet observability
Logs, metrics, and alerts across every pipeline run — so you notice drift, flakiness, and runaway costs before they compound.
How KubeRocketCI delivers it today
No roadmap promises — each capability maps to a platform feature you can use right now.
Execution harness
Predefined Tekton pipelines for polyglot microservices, plus custom pipelines when your flow needs its own steps.
Read the docsQuality gates
Autotests as quality gates in CD pipelines — reliable versions get promoted, failures stop at the gate.
Read the docsGuardrails and governance
Single Sign-On with OIDC/SAML identity providers and Kubernetes RBAC across the whole platform.
Read the docsAudit trail by design
The GitOps approach stores platform and application configuration as code in Git — every change is a commit.
Read the docsEphemeral environments
Deploy any feature branch into its own environment, test it deeply, and destroy it when the hypothesis is answered.
Read the docsFleet observability
Logging, monitoring, and alerting stacks with code-quality and vulnerability scanning built into the platform.
Read the docs