Visual Deploy Pipelines

Design Git-triggered deployment flows from repositories to cloud environments with an intuitive, visual canvas.

What it is

A drag-and-drop interface that maps your actual infrastructure to CI/CD pipelines. No more guessing what YAML does. We visualize the Directed Acyclic Graph (DAG) of your resources, showing exactly how data flows from your Git repository through build steps and into production infrastructure.

When to use it

Migrating legacy monoliths to microservices where dependency mapping is critical.
Onboarding new engineers who need to understand the system architecture in minutes, not weeks.
Debugging complex multi-region deployment failures by visualizing the exact blast radius.

Use Cases

Real-world scenarios

Microservices Dependency Hell

The Problem

A fintech startup had 15+ microservices with complex boot-order dependencies defined in spaghetti YAML. Deployments frequently failed because Service B started before Service A was ready.

The Solution

They imported their repo into DeployN. The Visual Pipeline automatically detected service mesh dependencies and generated a topological sort for the deployment order.

Result: reduced deployment incidents by 90% and eliminated "boot loops" entirely.

Multi-Region DR Rollout

The Problem

Replicating the US-East production stack to EU-Central for GDPR compliance was a manual, error-prone process involving copy-pasting Terraform files and manually updating region variables.

The Solution

Used "Clone to Region" in the visual canvas. DeployN duplicated the entire topology, automatically injecting the correct region-specific AMI IDs and VPC configurations.

Result: Provisioned a fully compliant EU disaster recovery site in 15 minutes instead of 3 days.

Blue/Green Deployment at Scale

The Problem

The team wanted zero-downtime deployments but writing the load balancer traffic-shifting logic in raw HCL was too risky for junior devs.

The Solution

Dragged a "Blue/Green Strategy" node onto the pipeline canvas. DeployN auto-generated the target groups, listeners and weighted routing rules.

Result: Achieved true zero-downtime updates with a visual "Rollback" button available at every stage.

How It Works

Step 1:Connect Repo

Link your GitHub/GitLab repository. We scan for Dockerfiles, Kubernetes manifests and Terraform modules.

Step 2:Visualize DAG

We render your infrastructure as a graph. Drag resources (EC2, RDS, S3) to connect dependencies.

Step 3:Define Logic

Add approval gates, manual steps, or automated tests directly between deployment nodes.

Step 4:Generate & Deploy

We commit the generated workflow file back to your repo and trigger the run.

Measurable Outcomes

Deployment Speed

Faster pipeline setup time compared to writing raw YAML configuration.

90%

Error Reduction

Fewer misconfigurations due to visual validation and pre-flight checks.

2 Days

Onboarding

Time for new hires to ship code, down from 2 weeks.

Technical Implementation

Pro Tip

You can drag a "Manual Approval" node between "Plan" and "Apply" to require a manager's sign-off before production changes go live.

Generated Workflow (Example)

YAML

name: Deploy to Production
on:
  push:
    branches: [ "main" ]

jobs:
  plan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: DeployN Plan
        uses: deployn/action@v1
        with:
          api-key: ${{ secrets.DEPLOYN_API_KEY }}
          command: plan
          
  apply:
    needs: plan
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    steps:
      - name: DeployN Apply
        uses: deployn/action@v1
        with:
          command: apply --auto-approve

ARCHITECTURE FLOW

This diagram represents the logical flow of data within the Visual Deploy Pipelines module, demonstrating how it integrates with your existing stack.

Common Questions

Does this replace Terraform/OpenTofu?

No. We generate standard Terraform/OpenTofu code under the hood. You own the code and can export it anytime.

Can I edit the generated YAML manually?

Yes. DeployN features bi-directional sync. Changes in the visual editor update the code and code pushes update the visual editor.

How do you handle secrets?

We integrate with AWS Secrets Manager, HashiCorp Vault and GitHub Secrets. We never store raw credentials.

Does it support custom runners?

Yes. You can attach your own self-hosted runners for strict compliance requirements.

What if I delete a node visually?

DeployN will create a PR to remove the resource from your Terraform state and code, following a safe "Plan > Apply" workflow.

Ready to implement Visual Deploy Pipelines?

Join the waitlist to get early access and start building your visual infrastructure today.

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