Client Story

This is the simplest version of the platform story.

Use this page when you want to explain the product to a client without too much technical detail.

One-minute explanation

The user signs in, chooses a project, clicks deploy, and the platform does the rest:

1. It checks the code.
2. It builds the app.
3. It saves the image.
4. It writes the deployment plan.
5. It deploys the app to Kubernetes.
6. It gives the user a live link.
7. If needed, it can roll back to an older version.

Simple flow

flowchart LR
  Client["Client / User"]
  Frontend["Frontend"]
  Backend["Backend"]
  Jenkins["Build System"]
  GitOps["Deployment Plan"]
  Argo["Auto Deploy"]
  K8s["Live App"]
  URL["Live URL"]

  Client --> Frontend
  Frontend -->|sign in / click deploy| Backend
  Backend -->|start build| Jenkins
  Jenkins -->|build app image| GitOps
  GitOps -->|sync changes| Argo
  Argo -->|run app| K8s
  K8s --> URL
  URL --> Client

What each step means

1. Sign in

The user opens the platform and signs in.

2. Create or choose a project

The user chooses what to deploy:

• monolithic app
• database
• spring microservice

3. Click deploy

The platform starts the build automatically.

4. Build and publish

The build system creates the app image and stores it safely.

5. Update deployment plan

The platform writes the new version into Git so the deployment is recorded.

6. Auto deploy

The deployment system watches Git and updates the cluster automatically.

7. Open the live app

After deployment, the user gets the public URL and can open the app.

How to explain it to a client

You can say:

“The platform turns code into a live app automatically.
The user clicks deploy, the system builds it, stores it, deploys it, and gives back a live link.”

Why this is useful

• no manual Kubernetes work
• no manual server setup
• easy rollback
• clear deployment history
• works for multiple project types

Summary

This is a simple deploy platform:

• frontend for the user
• backend for the logic
• build system for packaging
• Git for deployment history
• auto deploy system for syncing
• Kubernetes for running the app