Local Dev to Production

    From Minikube to prod.
    Same stack. Every time.

    Build on your laptop, clone to staging, promote to production. Visual Stack Builder, AI-generated manifests, and environment variables that keep every cluster in sync.

    Day 1
    Engineer ships
    1 click
    Promote env
    0 YAML
    Required

    The gap between dev and prod is still too wide

    Most teams build fast locally, then hit a wall when it is time to ship. Sound familiar?

    Works on my machine

    Dev uses Minikube, staging runs on EKS, production is GKE. Different configs, different behavior, different bugs.

    Onboarding takes weeks

    New engineers spend 1-2 weeks learning kubectl, Helm, ArgoCD, and the team's bespoke deploy scripts before they can ship anything.

    Manual manifest copying

    Promoting from dev to staging means copying YAML, tweaking values, hoping you got the diffs right. One missed env var breaks prod.

    Tribal knowledge bottleneck

    Only the engineer who built the pipeline knows how it works. When they are on vacation, deployments stall.

    How Ankra closes the dev-to-prod gap

    Build locally, promote confidently, ship consistently.

    Visual Stack Builder

    Drag-and-drop your entire environment. Namespaces, databases, apps, ingress. See the dependency graph, not raw YAML.

    AI Generates Your Manifests

    Press Cmd+J: "Create a backend deployment, 2 replicas, port 8080, health check." The AI writes manifests aware of your existing cluster state.

    Clone Dev to Staging to Prod

    Build your stack on Minikube. Clone it to staging with one click. Promote to production. Same blueprint, environment-specific variables.

    Variables per Environment

    Organisation, cluster, and stack-level variables. Dev uses localhost domains, staging uses staging.example.com. The Stack template stays identical.

    GitOps from Day One

    Every deploy commits to Git. New engineers read the repo to understand the infra. PR reviews for every change. Full audit trail.

    New Engineers Deploy on Day One

    No kubectl expertise required. The visual builder and AI assistant mean anyone can understand, modify, and deploy stacks immediately.

    Minikube / Kind
    Local dev
    Dev Cluster
    Shared testing
    Staging
    Pre-production
    Production
    Live traffic
    One-click clone at each stageSame Stack, different variables
    Real-world walkthrough

    Tuesday: New payment service, local to prod

    Watch what happens when a team builds a new service on Minikube and promotes it to production using Ankra.

    09:00Local Dev

    Build the service on Minikube

    A junior engineer opens the Visual Stack Builder, adds a new namespace, a Postgres addon, and a backend deployment. The AI generates the manifests when she types: "2 replicas, port 8080, /healthz check, 256Mi memory."

    AI auto-sets resource limits based on cluster capacity
    Every change commits to Git -- full history from minute one
    10:30Dev Cluster

    Clone to shared dev for team testing

    One click clones the stack to the shared dev cluster. Cluster variables swap localhost for dev.internal domain. The database connection string updates automatically.

    Variables cascade: org defaults, cluster overrides, stack overrides
    Registry credentials inherited from org-level variables
    14:00Staging

    Promote to staging -- drift caught before it lands

    Clone from dev to staging. Ankra orchestrates the deployment: configures ArgoCD with SOPS-encrypted secrets, injects staging variables, and schedules resources in dependency order. The AI flags that staging's ingress controller is outdated before the first pod starts.

    Ankra configures and triggers ArgoCD -- secrets, variables, and sync handled automatically
    AI catches version mismatches before they become incidents
    16:00Production

    Ship to prod with confidence

    Final clone to production. The stack arrives as a draft for review. Production cluster variables (domain, TLS certs, alerting channel) are picked up automatically. Click deploy.

    Draft mode -- review every manifest before it touches prod
    Same template across all 4 environments, zero config drift
    End of day

    New payment service is live in production. Four environments, one template, zero YAML copying. The junior engineer never touched kubectl. The entire journey is in Git.

    1 day
    Time to production
    0
    Manual YAML edits
    0
    Config drift incidents
    4 / 4
    Environments in sync

    Ship faster from day one

    TaskLegacy ApproachWith Ankra
    Onboard new engineer1-2 weeksDay one
    Promote dev to stagingHours of YAML copyingOne-click clone
    Set up CI/CD for new service4-6 hours30 minutes
    Debug a failed deploy1-2 hours (kubectl + logs)5 minutes (AI)
    Free tier available

    Close the gap between dev and prod

    Build on your laptop, promote to production. New engineers ship on day one.